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How to Write a Literature Review | Guide, Examples, & Templates

Published on January 2, 2023 by Shona McCombes . Revised on September 11, 2023.

What is a literature review? A literature review is a survey of scholarly sources on a specific topic. It provides an overview of current knowledge, allowing you to identify relevant theories, methods, and gaps in the existing research that you can later apply to your paper, thesis, or dissertation topic .

There are five key steps to writing a literature review:

  • Search for relevant literature
  • Evaluate sources
  • Identify themes, debates, and gaps
  • Outline the structure
  • Write your literature review

A good literature review doesn’t just summarize sources—it analyzes, synthesizes , and critically evaluates to give a clear picture of the state of knowledge on the subject.

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Table of contents

What is the purpose of a literature review, examples of literature reviews, step 1 – search for relevant literature, step 2 – evaluate and select sources, step 3 – identify themes, debates, and gaps, step 4 – outline your literature review’s structure, step 5 – write your literature review, free lecture slides, other interesting articles, frequently asked questions, introduction.

  • Quick Run-through
  • Step 1 & 2

When you write a thesis , dissertation , or research paper , you will likely have to conduct a literature review to situate your research within existing knowledge. The literature review gives you a chance to:

  • Demonstrate your familiarity with the topic and its scholarly context
  • Develop a theoretical framework and methodology for your research
  • Position your work in relation to other researchers and theorists
  • Show how your research addresses a gap or contributes to a debate
  • Evaluate the current state of research and demonstrate your knowledge of the scholarly debates around your topic.

Writing literature reviews is a particularly important skill if you want to apply for graduate school or pursue a career in research. We’ve written a step-by-step guide that you can follow below.

Literature review guide

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Writing literature reviews can be quite challenging! A good starting point could be to look at some examples, depending on what kind of literature review you’d like to write.

  • Example literature review #1: “Why Do People Migrate? A Review of the Theoretical Literature” ( Theoretical literature review about the development of economic migration theory from the 1950s to today.)
  • Example literature review #2: “Literature review as a research methodology: An overview and guidelines” ( Methodological literature review about interdisciplinary knowledge acquisition and production.)
  • Example literature review #3: “The Use of Technology in English Language Learning: A Literature Review” ( Thematic literature review about the effects of technology on language acquisition.)
  • Example literature review #4: “Learners’ Listening Comprehension Difficulties in English Language Learning: A Literature Review” ( Chronological literature review about how the concept of listening skills has changed over time.)

You can also check out our templates with literature review examples and sample outlines at the links below.

Download Word doc Download Google doc

Before you begin searching for literature, you need a clearly defined topic .

If you are writing the literature review section of a dissertation or research paper, you will search for literature related to your research problem and questions .

Make a list of keywords

Start by creating a list of keywords related to your research question. Include each of the key concepts or variables you’re interested in, and list any synonyms and related terms. You can add to this list as you discover new keywords in the process of your literature search.

  • Social media, Facebook, Instagram, Twitter, Snapchat, TikTok
  • Body image, self-perception, self-esteem, mental health
  • Generation Z, teenagers, adolescents, youth

Search for relevant sources

Use your keywords to begin searching for sources. Some useful databases to search for journals and articles include:

  • Your university’s library catalogue
  • Google Scholar
  • Project Muse (humanities and social sciences)
  • Medline (life sciences and biomedicine)
  • EconLit (economics)
  • Inspec (physics, engineering and computer science)

You can also use boolean operators to help narrow down your search.

Make sure to read the abstract to find out whether an article is relevant to your question. When you find a useful book or article, you can check the bibliography to find other relevant sources.

You likely won’t be able to read absolutely everything that has been written on your topic, so it will be necessary to evaluate which sources are most relevant to your research question.

For each publication, ask yourself:

  • What question or problem is the author addressing?
  • What are the key concepts and how are they defined?
  • What are the key theories, models, and methods?
  • Does the research use established frameworks or take an innovative approach?
  • What are the results and conclusions of the study?
  • How does the publication relate to other literature in the field? Does it confirm, add to, or challenge established knowledge?
  • What are the strengths and weaknesses of the research?

Make sure the sources you use are credible , and make sure you read any landmark studies and major theories in your field of research.

You can use our template to summarize and evaluate sources you’re thinking about using. Click on either button below to download.

Take notes and cite your sources

As you read, you should also begin the writing process. Take notes that you can later incorporate into the text of your literature review.

It is important to keep track of your sources with citations to avoid plagiarism . It can be helpful to make an annotated bibliography , where you compile full citation information and write a paragraph of summary and analysis for each source. This helps you remember what you read and saves time later in the process.

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To begin organizing your literature review’s argument and structure, be sure you understand the connections and relationships between the sources you’ve read. Based on your reading and notes, you can look for:

  • Trends and patterns (in theory, method or results): do certain approaches become more or less popular over time?
  • Themes: what questions or concepts recur across the literature?
  • Debates, conflicts and contradictions: where do sources disagree?
  • Pivotal publications: are there any influential theories or studies that changed the direction of the field?
  • Gaps: what is missing from the literature? Are there weaknesses that need to be addressed?

This step will help you work out the structure of your literature review and (if applicable) show how your own research will contribute to existing knowledge.

  • Most research has focused on young women.
  • There is an increasing interest in the visual aspects of social media.
  • But there is still a lack of robust research on highly visual platforms like Instagram and Snapchat—this is a gap that you could address in your own research.

There are various approaches to organizing the body of a literature review. Depending on the length of your literature review, you can combine several of these strategies (for example, your overall structure might be thematic, but each theme is discussed chronologically).


The simplest approach is to trace the development of the topic over time. However, if you choose this strategy, be careful to avoid simply listing and summarizing sources in order.

Try to analyze patterns, turning points and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred.

If you have found some recurring central themes, you can organize your literature review into subsections that address different aspects of the topic.

For example, if you are reviewing literature about inequalities in migrant health outcomes, key themes might include healthcare policy, language barriers, cultural attitudes, legal status, and economic access.


If you draw your sources from different disciplines or fields that use a variety of research methods , you might want to compare the results and conclusions that emerge from different approaches. For example:

  • Look at what results have emerged in qualitative versus quantitative research
  • Discuss how the topic has been approached by empirical versus theoretical scholarship
  • Divide the literature into sociological, historical, and cultural sources


A literature review is often the foundation for a theoretical framework . You can use it to discuss various theories, models, and definitions of key concepts.

You might argue for the relevance of a specific theoretical approach, or combine various theoretical concepts to create a framework for your research.

Like any other academic text , your literature review should have an introduction , a main body, and a conclusion . What you include in each depends on the objective of your literature review.

The introduction should clearly establish the focus and purpose of the literature review.

Depending on the length of your literature review, you might want to divide the body into subsections. You can use a subheading for each theme, time period, or methodological approach.

As you write, you can follow these tips:

  • Summarize and synthesize: give an overview of the main points of each source and combine them into a coherent whole
  • Analyze and interpret: don’t just paraphrase other researchers — add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
  • Critically evaluate: mention the strengths and weaknesses of your sources
  • Write in well-structured paragraphs: use transition words and topic sentences to draw connections, comparisons and contrasts

In the conclusion, you should summarize the key findings you have taken from the literature and emphasize their significance.

When you’ve finished writing and revising your literature review, don’t forget to proofread thoroughly before submitting. Not a language expert? Check out Scribbr’s professional proofreading services !

This article has been adapted into lecture slides that you can use to teach your students about writing a literature review.

Scribbr slides are free to use, customize, and distribute for educational purposes.

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If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

  • Sampling methods
  • Simple random sampling
  • Stratified sampling
  • Cluster sampling
  • Likert scales
  • Reproducibility


  • Null hypothesis
  • Statistical power
  • Probability distribution
  • Effect size
  • Poisson distribution

Research bias

  • Optimism bias
  • Cognitive bias
  • Implicit bias
  • Hawthorne effect
  • Anchoring bias
  • Explicit bias

A literature review is a survey of scholarly sources (such as books, journal articles, and theses) related to a specific topic or research question .

It is often written as part of a thesis, dissertation , or research paper , in order to situate your work in relation to existing knowledge.

There are several reasons to conduct a literature review at the beginning of a research project:

  • To familiarize yourself with the current state of knowledge on your topic
  • To ensure that you’re not just repeating what others have already done
  • To identify gaps in knowledge and unresolved problems that your research can address
  • To develop your theoretical framework and methodology
  • To provide an overview of the key findings and debates on the topic

Writing the literature review shows your reader how your work relates to existing research and what new insights it will contribute.

The literature review usually comes near the beginning of your thesis or dissertation . After the introduction , it grounds your research in a scholarly field and leads directly to your theoretical framework or methodology .

A literature review is a survey of credible sources on a topic, often used in dissertations , theses, and research papers . Literature reviews give an overview of knowledge on a subject, helping you identify relevant theories and methods, as well as gaps in existing research. Literature reviews are set up similarly to other  academic texts , with an introduction , a main body, and a conclusion .

An  annotated bibliography is a list of  source references that has a short description (called an annotation ) for each of the sources. It is often assigned as part of the research process for a  paper .  

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Software Development Analytics in Practice: A Systematic Literature Review

  • Review article
  • Published: 10 January 2023
  • Volume 30 , pages 2041–2080, ( 2023 )

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sample literature review of software project

  • João Caldeira   ORCID: orcid.org/0000-0003-0960-0179 1 ,
  • Fernando Brito e Abreu   ORCID: orcid.org/0000-0002-9086-4122 1 ,
  • Jorge Cardoso   ORCID: orcid.org/0000-0001-8992-3466 2 , 3 ,
  • Rachel Simões   ORCID: orcid.org/0000-0002-6046-8620 4 ,
  • Toacy Oliveira   ORCID: orcid.org/0000-0001-8184-2442 4 &
  • José Pereira dos Reis   ORCID: orcid.org/0000-0002-2505-9565 5  

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Software development analytics is a research area concerned with providing insights to improve product deliveries and processes. Many types of studies, data sources and mining methods have been used for that purpose. This systematic literature review aims at providing an aggregate view of the relevant studies on Software Development Analytics in the past decade, with an emphasis on its application in practical settings. Definition and execution of a search string upon several digital libraries, followed by a quality assessment criteria to identify the most relevant papers. On those, we extracted a set of characteristics (study type, data source, study perspective, development life-cycle activities covered, stakeholders, mining methods, and analytics scope) and classified their impact against a taxonomy. Source code repositories, exploratory case studies, and developers are the most common data sources, study types, and stakeholders, respectively. Testers also get moderate attention from researchers. Product managers’ concerns are being addressed frequently and project managers are also present but with less prevalence. Mining methods are rapidly evolving, as reflected in their identified long list. Descriptive statistics are the most usual method followed by correlation analysis. Being software development an important process in every organization, it was unexpected to find that process mining was present in only one study. Most contributions to the software development life cycle were given in the quality dimension. Time management and costs control were less prevalent. The analysis of security aspects is even more reduced, however, evidences suggest it is an increasing topic of concern. Risk management contributions are also scarce. There is a wide improvement margin for software development analytics in practice. For instance, mining and analyzing the activities performed by software developers in their actual workbench, i.e., in their IDEs. Together with mining developers’ behaviors, based on the evidences and trend, in a short term period we expect an increase in the volume of studies related with security and risks management.

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The sum of frequencies might be bigger than the total number of selected studies(n = 42) because some publications have been classified with more than one Study Type, Data Source, SDLC Activity, Stakeholder, Mining Method and/or Analytics Scope.

Abdellatif M, Capretz F, Ho D (2015) Software Analytics to software practice: a systematic literature review. In: 1st International workshop on big data software engineering, IEEE/ACM, New York, pp 30–36. https://doi.org/10.1109/BIGDSE.2015.14 . https://www.eng.uwo.ca/Electrical/faculty/capretz_l/docs/publications/Tamer-BIGDSE-v2.pdf

AlOmar EA, Mkaouer MW, Ouni A (2021) Toward the automatic classification of self-affirmed refactoring. J Syst Softw 171:110821. https://doi.org/10.1016/J.JSS.2020.110821

Anwar H, Pfahl D (2017) Towards greener software engineering using software analytics: a systematic mapping. In: Proceedings of 43rd Euromicro conference on software engineering and advanced applications, SEAA 2017. Institute of Electrical and Electronics Engineers Inc., pp 157–166. https://doi.org/10.1109/SEAA.2017.56

Avila SDG, Cano PO, Mejia AM, Moreno IS, Lepe AN (2020) A data driven platform for improving performance assessment of software defined storage solutions. Adv Intell Syst Comput 1071:266–275. https://doi.org/10.1007/978-3-030-33547-2_20

Article   Google Scholar  

Bangash AA, Sahar H, Hindle A, Ali K (2020) On the time-based conclusion stability of cross-project defect prediction models. Empir Softw Eng 25:5047–5083. https://doi.org/10.1007/S10664-020-09878-9

Buse RPL, Zimmermann T (2010) Analytics for software development. Tech. rep., Microsoft Research. https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/MSR-TR-2010-111.pdf

Buse RP, Zimmermann T (2012) Information needs for software development analytics. In: Proceedings - International Conference on Software Engineering, pp 987–996, https://doi.org/10.1109/ICSE.2012.6227122

Cai KY (2002) Optimal software testing and adaptive software testing in the context of software cybernetics. Inf Softw Technol 44(14):841–855. https://doi.org/10.1016/S0950-5849(02)00108-8

Cai KY, Chen T, Tse T (2002) Towards research on software cybernetics. In: 7th IEEE international symposium on high assurance systems engineering, 2002. Proceedings, pp 240–241. https://doi.org/10.1109/HASE.2002.1173129

Capizzi A, Distefano S, Araújo LJ, Mazzara M, Ahmad M, Bobrov E (2020) Anomaly detection in devops toolchain. Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and Lecture notes in bioinformatics), vol 12055, pp 37–51. https://doi.org/10.1007/978-3-030-39306-9_3

Chen L, Babar MA (2011) A systematic review of evaluation of variability management approaches in software product lines. Inf Softw Technol 53(4):344–362

Chen C, Xing Z, Liu Y (2019) What’s Spain’s Paris? Mining analogical libraries from Q & A discussions. Empir Softw Eng 24(3):1155–1194. https://doi.org/10.1007/s10664-018-9657-y

Cosentino V, Izquierdo JL, Cabot J (2017) A systematic mapping study of software development with GitHub. IEEE Access 5:7173–7192. https://doi.org/10.1109/ACCESS.2017.2682323

Cruz L, Abreu R, Lo D (2019) To the attention of mobile software developers: guess what, test your app! Empir Softw Eng 24:2438–2468. https://doi.org/10.1007/s10664-019-09701-0

Dasanayake S, Markkula J, Oivo M (2014) Concerns in software development: a systematic mapping study. In: Proceedings of the 18th International conference on evaluation and assessment in software engineering. Association for Computing Machinery, pp 1–4. https://doi.org/10.1145/2601248.2601290

Davenport TH, Harris JG, Morison R (2010) Analytics at work: smarter decisions, better results. Harvard Business Press. http://discovery.uoc.edu/iii/encore/record/C__Rb1049687__SAnalytics%20at%20Work__Orightresult__U__X7?lang=spi

D’Avila LF, Farias K, Barbosa JLV (2020) Effects of contextual information on maintenance effort: a controlled experiment. J Syst Softw. https://doi.org/10.1016/J.JSS.2019.110443

Dybå T, Dingsøyr T (2008) Strength of evidence in systematic reviews in software engineering. In: ESEM’08: proceedings of the 2008 ACM-IEEE international symposium on empirical software engineering and measurement, pp 178–187. https://doi.org/10.1145/1414004.1414034

Emam KE, Koru AG (2008) A replicated survey of IT software project failures. IEEE Softw 25(5):84–90. https://doi.org/10.1109/MS.2008.107 . ( ieeexplore.ieee.org/document/4602680/ )

Fan Y, Xia X, Lo D, Li S (2018) Early prediction of merged code changes to prioritize reviewing tasks. Empir Softw Eng 23(6):3346–3393. https://doi.org/10.1007/s10664-018-9602-0

Fucci D, Turhan B (2014) On the role of tests in test-driven development: a differentiated and partial replication. Empir Softw Eng 19(2):277–302. https://doi.org/10.1007/s10664-013-9259-7

Garcia CdS, Meincheim A, Faria Junior ER, Dallagassa MR, Sato DMV, Carvalho DR, Santos EAP, Scalabrin EE (2019) Process mining techniques and applications—a systematic mapping study. Expert Syst Appl 133:260–295. https://doi.org/10.1016/j.eswa.2019.05.003

Gomes TL, Oliveira TC, Cowan D, Alencar P (2014) Mining reuse processes. In: CIBSE 2014: proceedings of the 17th Ibero-American conference software engineering. Curran Associates, Pucon, pp 179–191. https://dblp.org/rec/bib/conf/cibse/GomesOCA14

Guerrouj L, Kermansaravi Z, Arnaoudova V, Fung BC, Khomh F, Antoniol G, Guéhéneuc YG (2017) Investigating the relation between lexical smells and change- and fault-proneness: an empirical study. Softw Qual J 25(3):641–670. https://doi.org/10.1007/s11219-016-9318-6

Hassan S, Shang W, Hassan AE (2017) An empirical study of emergency updates for top android mobile apps. Empir Softw Eng 22(1):505–546. https://doi.org/10.1007/s10664-016-9435-7

Hassan S, Tantithamthavorn C, Bezemer CP, Hassan AE (2018) Studying the dialogue between users and developers of free apps in the Google Play Store. Empir Softw Eng 23(3):1275–1312. https://doi.org/10.1007/s10664-017-9538-9

IEEE Computer Society (2014) SWEBOK V3.0. No. V3.0 in 1. IEEE Computer Society. https://doi.org/10.1234/12345678 , http://www4.ncsu.edu/~tjmenzie/cs510/pdf/SWEBOKv3.pdf

Izquierdo-Cortazar D, Sekitoleko N, Gonzalez-Barahona JM, Kurth L (2017) Using metrics to track code review performance. In: ACM international conference proceeding series. Association for Computing Machinery, vol Part F128635, pp 214–223. https://doi.org/10.1145/3084226.3084247

Jha AK, Lee S, Lee WJ (2019) An empirical study of configuration changes and adoption in Android apps. J Syst Softw 156:164–180. https://doi.org/10.1016/j.jss.2019.06.095

Jiang J, Lo D, He J, Xia X, Kochhar PS, Zhang L (2017) Why and how developers fork what from whom in GitHub. Empirical Softw Eng 22(1):547–578. https://doi.org/10.1007/s10664-016-9436-6

Kitchenham B, Brereton P (2013) A systematic review of systematic review process research in software engineering. Inf Softw Technol 55(12):2049–2075. https://doi.org/10.1016/j.infsof.2013.07.010

Kitchenham B, Pearl Brereton O, Budgen D, Turner M, Bailey J, Linkman S (2009) Systematic literature reviews in software engineering—a systematic literature review. Inf Softw Technol 5:7–15

Krishna R, Menzies T (2020) Learning actionable analytics from multiple software projects. Empir Softw Eng 25:3468–3500. https://doi.org/10.1007/S10664-020-09843-6

Li H, Shang W, Zou Y, Hassan E, A, (2017) Towards just-in-time suggestions for log changes. Empir Softw Eng 22(4):1831–1865. https://doi.org/10.1007/s10664-016-9467-z

Li H, Chen THP, Shang W, Hassan AE (2018) Studying software logging using topic models. Empir Softw Eng 23(5):2655–2694. https://doi.org/10.1007/s10664-018-9595-8

Liu Y, Wang J, Wei L, Xu C, Cheung SC, Wu T, Yan J, Zhang J (2019) DroidLeaks: a comprehensive database of resource leaks in Android apps. Empir Softw Eng 24(6):3435–3483. https://doi.org/10.1007/s10664-019-09715-8

McIlroy S, Ali N, Hassan AE (2016) Fresh apps: an empirical study of frequently-updated mobile apps in the Google play store. Empir Softw Eng 21(3):1346–1370. https://doi.org/10.1007/s10664-015-9388-2

Menzies T, Bird C, Zimmermann T, Schulte W, Kocaganeli E (2011) The inductive software engineering manifesto: principles for industrial data mining. In: Proceedings of the international workshop on machine learning technologies in software engineering. Association for Computing Machinery, pp 19–26. http://bit.ly/o02QZJ

Menzies T, Minku L, Peters F (2015) The art and science of analyzing software data; quantitative methods. In: Proceedings of the international conference on software engineering, vol 2. IEEE Computer Society, pp 959–960. https://doi.org/10.1109/ICSE.2015.306

Mittal M, Sureka A (2014a) MIMANSA: process mining software repositories from student projects in an undergraduate software engineering course categories and subject descriptors. Softw Eng Educ Train ICSE 2014:344–353

Google Scholar  

Mittal M, Sureka A (2014b) Process mining software repositories from student projects in an undergraduate software engineering course. In: 36th International conference on software engineering, ICSE Companion 2014—proceedings. Association for Computing Machinery, pp 344–353. https://doi.org/10.1145/2591062.2591152

Mohagheghi P, Conradi R (2007) Quality, productivity and economic benefits of software reuse: a review of industrial studies. Empir Softw Eng 12(5):471–516. https://doi.org/10.1007/s10664-007-9040-x

Mohagheghi P, Jorgensen M (2017) What contributes to the success of IT projects? Success factors, challenges and lessons learned from an empirical study of software projects in the Norwegian public sector. In: 2017 IEEE/ACM 39th international conference on software engineering companion (ICSE-C). IEEE, pp 371–373. https://doi.org/10.1109/ICSE-C.2017.146 , http://ieeexplore.ieee.org/document/7965362/

Morales-Ramirez I, Kifetew FM, Perini A (2018) Speech-acts based analysis for requirements discovery from online discussions. Inf Syst 86:94–112. https://doi.org/10.1016/j.is.2018.08.003

Munaiah N, Meneely A (2016) Vulnerability severity scoring and bounties: why the disconnect. In: SWAN 2016 - Proceedings of the 2nd international workshop on software analytics, co-located with FSE 2016. Association for Computing Machinery, pp 8–14. https://doi.org/10.1145/2989238.2989239

Nakamoto S (2009) Bitcoin: A Peer-to-Peer Electronic Cash System. Tech. rep., http://www.bitcoin.org , www.bitcoin.org

Nayebi M, Ruhe G, Mota RC, Mufti M (2016) Analytics for software project management—wWhere are we and where do we go? In: Proceedings—2015 30th IEEE/ACM international conference on automated software engineering workshops, ASEW 2015. Institute of Electrical and Electronics Engineers, pp 18–21. https://doi.org/10.1109/ASEW.2015.28

Poncin W, Serebrenik A, Brand MVD (2011) Process mining software repositories. In: 2011 15th European conference on software maintenance and reengineering, pp 5–14. https://doi.org/10.1109/CSMR.2011.5

Prana GAA, Treude C, Thung F, Atapattu T, Lo D (2019) Categorizing the content of GitHub README files. Empir Softw Eng 24(3):1296–1327. https://doi.org/10.1007/s10664-018-9660-3

Qu Y, Yin H (2021) Evaluating network embedding techniques’ performances in software bug prediction. Empir Softw Eng. https://doi.org/10.1007/S10664-021-09965-5

Rakha MS, Shang W, Hassan AE (2016) Studying the needed effort for identifying duplicate issues. Empir Softw Eng 21(5):1960–1989. https://doi.org/10.1007/s10664-015-9404-6

Rakha MS, Bezemer CP, Hassan AE (2018) Revisiting the performance of automated approaches for the retrieval of duplicate reports in issue tracking systems that perform just-in-time duplicate retrieval. Empir Softw Eng 23(5):2597–2621. https://doi.org/10.1007/s10664-017-9590-5

Rana G, Haq EU, Bhatia E, Katarya R (2020) A study of hyper-parameter tuning in the field of software analytics. In: Proceedings of the 4th international conference on electronics, communication and aerospace technology, ICECA 2020, pp 455–459. https://doi.org/10.1109/ICECA49313.2020.9297613

Rodriguez D, Herraiz I, Harrison R (2012) On software engineering repositories and their open problems. In: 2012 1st International workshop on realizing AI synergies in software engineering, RAISE 2012—pProceedings, pp 52–56. https://doi.org/10.1109/RAISE.2012.6227971

Saborido R, Morales R, Khomh F, Guéhéneuc YG, Antoniol G (2018) Getting the most from map data structures in Android. Empir Softw Eng 23(5):2829–2864. https://doi.org/10.1007/s10664-018-9607-8

Salza P, Palomba F, Nucci DD, D’uva C, De Lucia A, Ferrucci F (2018) Do developers update third-party libraries in mobile apps. In: Proceedings of the 26th conference on program comprehension, vol 12. Association for Computing Machinery, pp 255–265

Sawant AA, Robbes R, Bacchelli A (2019) To react, or not to react: patterns of reaction to API deprecation. Empir Softw Eng 24(6):3824–3870. https://doi.org/10.1007/s10664-019-09713-w

Sultana KZ, Williams BJ, Bhowmik T (2019) A study examining relationships between micro patterns and security vulnerabilities. Softw Qual J 27(1):5–41. https://doi.org/10.1007/s11219-017-9397-z

Taba SES, Keivanloo I, Zou Y, Wang S (2017) An exploratory study on the usage of common interface elements in android applications. J Syst Softw 131:491–504. https://doi.org/10.1016/j.jss.2016.07.010

Tapscott D, Tapscott A (2016) Blockchain revolution: how the technology behind bitcoin is changing money, business, and the world. Portfolio

Thongtanunam P, Shang W, Hassan AE (2019) Will this clone be short-lived? Towards a better understanding of the characteristics of short-lived clones. Empir Softw Eng 24(2):937–972. https://doi.org/10.1007/s10664-018-9645-2

Tian Y, Nagappan M, Lo D, Hassan AE (2015) What are the characteristics of high-rated apps? A case study on free Android Applications. In: 2015 IEEE 31st International conference on software maintenance and evolution, ICSME 2015—proceedings. Institute of Electrical and Electronics Engineers, pp 301–310. https://doi.org/10.1109/ICSM.2015.7332476

Tim Menzies LW, Zimmermann T (2016) Perspectives on data science for software engineering. Elsevier, Amsterdam. https://doi.org/10.1016/C2015-0-00521-4

Van Der Aalst W (2016) Process mining: data science in action, 2nd edn. Springer, Berlin. https://doi.org/10.1007/978-3-662-49851-4

Van Der Aalst W, Adriansyah A, De Medeiros AKA, Arcieri F, Baier T, Blickle T, Bose JC, Van Den Brand P, Brandtjen R, Buijs J, Burattin A, Carmona J, Castellanos M, Claes J, Cook J, Costantini N, Curbera F, Damiani E, De Leoni M, Delias P, Van Dongen BF, Dumas M, Dustdar S, Fahland D, Ferreira DR, Gaaloul W, Van Geffen F, Goel S, Günther C, Guzzo A, Harmon P, Ter Hofstede A, Hoogland J, Ingvaldsen JE, Kato K, Kuhn R, Kumar A, La Rosa M, Maggi F, Malerba D, Mans RS, Manuel A, McCreesh M, Mello P, Mendling J, Montali M, Motahari-Nezhad HR, Zur Muehlen M, Munoz-Gama J, Pontieri L, Ribeiro J, Rozinat A, Seguel Pérez H, Seguel Pérez R, Sepúlveda M, Sinur J, Soffer P, Song M, Sperduti A, Stilo G, Stoel C, Swenson K, Talamo M, Tan W, Turner C, Vanthienen J, Varvaressos G, Verbeek E, Verdonk M, Vigo R, Wang J, Weber B, Weidlich M, Weijters T, Wen L, Westergaard M, Wynn M (2012) Process mining manifesto. Lecture notes in business information processing 99 (LNBIP), pp 169–194. https://doi.org/10.1007/978-3-642-28108-2_19

Vashisht R, Rizvi SAM (2021) An empirical study of heterogeneous cross-project defect prediction using various statistical techniques. Int J e-Collaboration 17:55–71. https://doi.org/10.4018/IJEC.2021040104

Wani ZH, Bhat JI, Giri KJ (2021) A generic analogy-centered software cost estimation based on differential evolution exploration process. Comput J 64:462–472. https://doi.org/10.1093/COMJNL/BXAA199

Article   MathSciNet   Google Scholar  

Wohlin C (2014) Guidelines for snowballing in systematic literature studies and a replication in software engineering. In: Proceedings of the 18th international conference on evaluation and assessment in software engineering (EASE ’14), pp 1–10. https://doi.org/10.1145/2601248.2601268

Wu R, Wen M, Cheung SC, Zhang H (2018) ChangeLocator: locate crash-inducing changes based on crash reports. Empir Softw Eng 23(5):2866–2900. https://doi.org/10.1007/s10664-017-9567-4

Wu W, Khomh F, Adams B, Guéhéneuc YG, Antoniol G (2016) An exploratory study of api changes and usages based on apache and eclipse ecosystems. Empir Softw Eng 21(6):2366–2412. https://doi.org/10.1007/s10664-015-9411-7

Yan M, Xia X, Lo D, Hassan AE, Li S (2019) Characterizing and identifying reverted commits. Empir Softw Eng 24(4):2171–2208. https://doi.org/10.1007/s10664-019-09688-8

Yang XL, Lo D, Xia X, Wan ZY, Sun JL (2016) What security questions do developers ask? A large-scale study of stack overflow posts. J Comput Sci Technol 31(5):910–924. https://doi.org/10.1007/s11390-016-1672-0 . ( archive.org/details/stackexchange )

Yang H, Chen F, Aliyu S (2017) Modern software cybernetics: new trends. J Syst Softw 124:169–186. https://doi.org/10.1016/j.jss.2016.08.095

Ye D, Xing Z, Kapre N (2017) The structure and dynamics of knowledge network in domain-specific Q &A sites: a case study of stack overflow. Empir Softw Eng 22(1):375–406. https://doi.org/10.1007/s10664-016-9430-z

Zannier C, Melnik G, Maurer F (2006) On the success of empirical studies in the international conference on software engineering. In: Proceedings of international conference on software engineering, pp 341–350. https://doi.org/10.1145/1134285.1134333

Zhang D, Han S, Dang Y, Lou JG, Zhang H, Research Asia M, Xie T (2013a) Software analytics in practice. IEEE Softw. http://channel9.msdn

Zhang D, Han S, Dang Y, Lou JG, Zhang H, Xie T (2013b) Software analytics in practice. IEEE Softw 30(5):30–37. https://doi.org/10.1109/MS.2013.94

Zhang L, Tian JH, Jiang J, Liu YJ, Pu MY, Yue T (2018) Empirical research in software engineering—a literature survey. J Comput Sci Technol 33(5):876–899. https://doi.org/10.1007/s11390-018-1864-x

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This work was partially funded by the Portuguese Foundation for Science and Technology, under ISTAR’s projects UIDB/04466/2020 and UIDP/04466/2020.

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1.1 Appendix 1: Data Extraction

1.1.1 selection process.

See Fig. 8 , Table 10 .

figure 8

Study selection process stages

Appendix 2: Studies List

See Table 11 .

1.1 Comments on Studies

[ S01 ] explores the correlation between software vulnerabilities and code-level constructs called micro patterns. The authors analyzed the correlation between vulnerabilities and micro patterns from different viewpoints and explored whether they are related. The conclusion shows that certain micro patterns are frequently present in vulnerable classes and that there is a high correlation between certain patterns that coexist in a vulnerable class [ 58 ].

[ S02 ] presents an empirical study to analyze commit histories of Android manifest files of hundreds of apps to understand their evolution through configuration changes. The results is a contribution to help developers in identifying change-proneness attributes, including the reasons behind the changes and associated patterns and understanding the usage of different attributes introduced in different versions of the Android platform. In summary, the results show that most of the apps extend core functionalities and improve user interface over time. It detected that significant effort is wasted in changing configuration and then reverting back the change, and that very few apps adopt new attributes introduced by the platform and when they do, they are slow in adopting new attributes. Configuration changes are mostly influenced by functionalities extension, platform evolution and bug reports [ 29 ].

[ S03 ] studied updates in the Google Play Store by examining more than 44,000 updates of over 10,000 mobile apps, from where 1,000 were identified as emergency updates. After studying the characterirstics of the updates, the authors found that the emergency updates often have a long lifetime (i.e., they are rarely followed by another emergency update) and that updates preceding emergency updates often receive a higher ratio of negative reviews than the emergency updates [ 25 ].

[ S04 ] analyzed and classified API changes and usages together in 22 framework releases from the Apache and Eclipse ecosystems and their client programs. The authors conclude that missing classes and methods happen more often in frameworks and affect client programs more often than the other API change types do, and that missing interfaces occur rarely in frameworks but affect client programs often. In summary, framework APIs are used on average in 35% of client classes and interfaces and most of such usages could be encapsulated locally and reduced in number. Around 11% of APIs usages could cause ripple effects in client programs when these APIs change. Some suggestions for developers and researchers were made to mitigate the impact of API evolution through language mechanisms and design strategies [ 70 ].

[ S05 ] extracted commonly used UI elements, denoted as Common Element Sets (CESs), from user interfaces of applications. The highlight the characteristics of CESs that can result in a high user-perceived quality by proposing various metrics. From an empirical study on 1292 mobile applications, the authors observed that CESs of mobile applications widely occur among and across different categories, whilst certain characteristics of CESs can provide a high user-perceived quality. A recommendation is made, aiming to improve the quality of mobile applications, consisting on the adoption of reusable UI templates that are extracted and summarized from CESs for developers [ 59 ].

[ S06 ] performed a qualitative study involving the manual annotation of 4,226 README file sections from 393 randomly sampled GitHub repositories and design and evaluate a classifier and a set of features that can categorize these sections automatically. The findings show that information discussing the ’What’ and ’How’ of a repository hapens very often, while at the same time, many README files lack information regarding the purpose and status of a repository. A classifier was built to predict multiple categories and the F1 score obtained encourages its usage by software repositories owners. The approach presented is said to improve the quality of software repositories documentation and it has the potential to make it easier for the software development community to discover relevant information in GitHub README files [ 49 ].

[ S07 ] conducted an empirical study on characterizing the bug inducing changes for crashing bugs (denoted as crash-inducing changes). ChangeLocator was also proposed as a method to automatically locate crash-inducing changes for a given bucket of crash reports. The study approach is based on a learning model that uses features originated from the empirical study itself and a model was trained using the data from the historical fixed crashes. ChangeLocator was evaluated with six release versions of the Netbeans project. The analysis and results show that it can locate the crash-inducing changes for 44.7%, 68.5%, and 74.5% of the bugs by examining only top 1, 5 and 10 changes in the recommended list, respectively, which is said to outperform other approaches [ 69 ].

[ S08 ] explored if one can characterize and identify which commits will be reverted. The authors characterized commits using 27 commit features and build an identification model to identify commits that will be reverted. Reverted commits were identified by analyzing commit messages and comparing the changed content, and extracted 27 commit features that were divided into three dimensions: change, developer and message. An identification model (e.g., random forest) was built and evaluated on an empirical study on ten open source projects including a total of 125,241 commits. The findings show that the ’developer’ is the most discriminative dimension among the three dimensions of features for the identification of reverted commits. However, using all the three dimensions of commit features leads to better performance of the created models [ 71 ].

[ S09 ] conducted an empirical study on the evolution history of almost three hundred mobile apps, by investigating whether mobile developers actually update third-party libraries, checking which are the categories of libraries with respect to the developers’ proneness to update their apps, looking for what are the common patterns followed by developers when updating a software library, and whether high- and low-rated apps present any particular update patterns. Results showed that mobile developers rarely update their apps with respect to the used libraries, and when they do, they mainly tend to update the libraries related to the Graphical User Interface, with the aim of keeping the mobile apps updated with the latest design trends. In some cases developers ignore updates because of a poor awareness of the benefits, or a too high cost/benefit ratio [ 56 ].

[ S10 ] extracted real resource leak bugs from a bug database named DROIDLEAKS. It consisted in mining 34 popular open-source Android apps, which resulted in a dataset having a total of 124,215 code revisions. After filtering and validating the data, the authors found, on 32 analyzed apps, 292 fixed resource leak bugs, which cover a diverse set of resource classes. To fully comprehend these bugs, they performed an empirical study, which revealed the characteristics of resource leaks in Android apps and common patterns of resource management mistakes made by developers [ 36 ].

[ S11 ] built a merged code change prediction tool leveraging machine learning techniques, and extracted 34 features from code changes, which were grouped into 5 dimensions: code, file history, owner experience, collaboration network, and text. Experiments were executed on three open source projects (i.e., Eclipse, LibreOffice, and OpenStack), containing a total of 166,215 code changes. Across three datasets, the results show statistically significantly improvements in detecting merged code changes and in distinguishing important features on merged code changes from abandoned ones [ 20 ].

[ S12 ] studied the frequency of updates of 10,713 mobile apps (the top free 400 apps at the start of 2014 in each of the 30 categories in the Google Play store). It was found that only \(\sim \) 1% of the studied apps are updated at a very frequent rate - more than one update per week and 14% of the studied apps are updated on a bi-weekly basis (or more frequently). Results also show that 45% of the frequently-updated apps do not provide the users with any information about the rationale for the new updates and updates exhibit a median growth in size of 6%. The authors conclude that developers should not shy away from updating their apps very frequently, however the frequency should vary across store categories. It was observed that developers do not need to be too concerned about detailing the content of new updates as it appears that users are not too concerned about such information and, that users highly rank frequently-updated apps instead of being annoyed about the high update frequency [ 37 ].

[ S13 ] studied the use of map data structure implementations by Android developers and how that relates with saving CPU, memory, and energy as these are major concerns of users wanting to increase battery life. The authors initially performed an observational study of 5713 Android apps in GitHub and then conducted a survey to assess developers’ perspective on Java and Android map implementations. Finally, they performed an experimental study comparing HashMap, ArrayMap, and SparseArray variants map implementations in terms of CPU time, memory usage, and energy consumption. The conclusions provide guidelines for choosing among the map implementations: HashMap is preferable over ArrayMap to improve energy efficiency of apps, and SparseArray variants should be used instead of HashMap and ArrayMap when keys are primitive types [ 55 ].

[ S14 ] detected 29 smells consisting of 13 design smells and 16 lexical smells in 30 releases of three projects: ANT, ArgoUML, and Hibernate. Further, the authors analyzed to what extent classes containing lexical smells have higher (or lower) odds to change or to be subject to fault fixing than other classes containing design smells. The results obtained bring empirical evidence on the fact that lexical smells can make, in some cases, classes with design smells more fault-prone. In addition, it was empirically demonstrated that classes containing design smells only are more change- and fault-prone than classes with lexical smells only [ 24 ].

[ S15 ] examined the nature of the relationship between tests and external code quality as well as programmers’ productivity in order to verify/refute the results of a previous study. With the focus on the role of tests, a differentiated and partial replication of the original study and related analysis was conducted. The replication involved 30 students, working in pairs or as individuals, in the context of a graduate course, and resulted in 16 software artifacts developed. Significant correlation was found between the number of tests and productivity. No significant correlation found between the number of tests and external code quality. For both cases we observed no statistically significant interaction caused by the subject units being individuals or pairs. Results obtained are consistent with the original study although, as the authors admit, there were changes in the timing constraints for finishing the task and the enforced development processes [ 21 ].

[ S16 ] presented an application of mining three software repositories: team wiki (used during requirement engineering), version control system (development and maintenance) and issue tracking system (corrective and adaptive maintenance) in the context of an undergraduate Software Engineering course. Visualizations, metrics and algorithms to provide an insight into practices and procedures followed during various phases of a software development life-cycle were proposed and these provided a multi-faceted view to the instructor serving as a feedback tool on development process and quality by students. Event logs produced by software repositories were mined and derived insights such as degree of individual contributions in a team, quality of commit messages, intensity and consistency of commit activities, bug fixing process trend and quality, component and developer entropy, process compliance and verification. Experimentation revealed that not only product but process quality varies signicantly between student teams and mining process aspects can help the instructor in giving directed and specific feedback. Authors, observed that commit patterns characterizing equal and un-equal distribution of workload between team members, patterns indicating consistent activity in contrast to spike in activity just before the deadline, varying quality of commit messages, developer and component entropy, variation in degree of process compliance and bug fixing quality [ 41 ].

[ S17 ] investigated the impact of the just-in-time duplicate retrieval on the duplicate reports that end up in the ITS of several open source projects, namelly Mozilla-Firefox, Mozilla-Core and Eclipse-Platform. The differences between duplicate reports for open source projects before and after the activation of this new feature were studied. Findings showed that duplicate issue reports after the activation of the just-in-time duplicate retrieval feature are less textually similar, have a greater identification delay and require more discussion to be retrieved as duplicate reports than duplicates before the activation of the feature [ 52 ].

[ S18 ] exploited a linguistic technique based on speech-acts for the analysis of online discussions with the ultimate goal of discovering requirements-relevant information. The datasets used in the experimental evaluation, which are publicly available, were taken from a widely used open source software project (161120 textual comments), as well as from an industrial project in the home energy management domain. The approach used was able to successfully classify messages into Feature/Enhancement and Other, with significant accuracy. Evidence was found to support the rationale, that there is an association between types of speech-acts and categories of issues, and that there is correlation between some of the speechacts and issue priority, which could open other streams of research [ 44 ].

[ S19 ] studied the relationship between the topics of a code snippet and the likelihood of a code snippet being logged (i.e., to contain a logging statement). The intuition driving this research, was that certain topics in the source code are more likely to be logged than others. To validate the assumptions a case study was conducted on six open source systems. The analysis gathered evidences that i) there exists a small number of “log-intensive” topics that are more likely to be logged than other topics; ii) each pair of the studied systems share 12% to 62% common topics, and the likelihood of logging such common topics has a statistically significant correlation of 0.35 to 0.62 among all the studied systems. In summary, the findings highlight the topics containing valuable information that can help guide and drive developers’ logging decisions [ 35 ].

[ S20 ] revisits a previous work in more depth by studying 4.5 million reviews with 126,686 responses for 2,328 top free-to-download apps in the Google Play Store. One of the major findings is that the assumption that reviews are static is incorrect. In particular, it is found that developers and users in some cases use this response mechanism as a rudimentary user support tool, where dialogues emerge between users and developers through updated reviews and responses. In addition, four patterns of developers were identified: 1) developers who primarily respond to only negative reviews, 2) developers who primarily respond to negative reviews or to reviews based on their contents, 3) developers who primarily respond to reviews which are posted shortly after the latest release of their app, and 4) developers who primarily respond to reviews which are posted long after the latest release of their app. To perform a qualitative analysis of developer responses to understand what drives developers to respond to a review, the authors analyzed a statistically representative random sample of 347 reviews with responses for the top ten apps with the highest number of developer responses. Seven drivers that make a developer respond to a review were identified, of which the most important ones are to thank the users for using the app and to ask the user for more details about the reported issue. In summary, there were significant evidences found, that it can be worthwhile for app owners to respond to reviews, as responding may lead to an increase in the given rating and that studying the dialogue between user and developer can provide valuable insights which may lead to improvements in the app store and the user support process [ 26 ].

[ S21 ] empirically examined the effort that is needed for manually identifying duplicate reports in four open source projects, i.e., Firefox, SeaMonkey, Bugzilla and Eclipse-Platform. Results showed that: (i) More than 50% of the duplicate reports are identified within half a day. Most of the duplicate reports are identified without any discussion and with the involvement of very few people; (ii) A classification model built using a set of factors that are extracted from duplicate issue reports classifies duplicates according to the effort that is needed to identify them with significant values for precision, recall and ROC area; and (iii) Factors that capture the developer awareness of the duplicate issues’ peers (i.e., other duplicates of that issue) and textual similarity of a new report to prior reports are the most influential factors found. The results highlight the need for effort-aware evaluation of approaches that identify duplicate issue reports, since the identification of a considerable amount of duplicate reports (over 50%) appear to be a relatively trivial task for developers. As a conclusion, the authors highlight the fact that, to better assist developers, research on identifying duplicate issue reports should put greater emphasis on assisting developers in identifying effort-consuming duplicate issues [ 51 ].

[ S22 ] analyzed URL sharing activities in Stack Overflow. The approach was to use open coding method to analyze why users share URLs in Stack Overflow, and develop a set of quantitative analysis methods to study the structural and dynamic properties of the emergent knowledge network in Stack Overflow. The findings show: i) Users share URLs for diverse categories of purposes. ii) These URL sharing behaviors create a complex knowledge network with high modularity, assortative mixing of semantic topics, and a structure skeleton consisting of highly recognized knowledge units. iii) The structure of the knowledge network with respect to indegree distribution is scale-free (i.e., stable), in spite of the ad-hoc and opportunistic nature of URL sharing activities, while the outdegree distribution of the knowledge network is not scale-free. iv) The indegree distributions of the knowledge network converge quickly, with small changes over time after the convergence to the stable distribution. The conclusions highlight the fact that the knowledge network is a natural product of URL sharing behavior that Stack Overflow supports and encourages, and proposed an explanatory model based on information value and preferential attachment theories to explain the underlying factors that drive the formation and evolution of the knowledge network in Stack Overflow [ 74 ].

[ S23 ] questioned if there was really a strong argument for the Java 9 language designers to change the implementation of the deprecation warnings feature after they notice no one was taking seriously those and continued using outdated features. The goal was to start by identifying the various ways in which an API consumer can react to deprecation and then to create a dataset of reaction patterns frequency consisting of data mined from 50 API consumers totalling 297,254 GitHub based projects and 1,322,612,567 type-checked method invocations. Findings show that predominantly consumers do not react to deprecation and a survey on API consumers was done to try to explain this behavior and by analyzing if the APIs deprecation policy had an impact on the consumers’ decision to react. The manual inspection of usages of deprecated API artifacts lead to the discovery of six reaction patterns. Only 13% of API consumers update their API versions and 88% of reactions to deprecation is doing nothing. However the survey got a different result, where 69% of respondents say they replace it with the recommended repalcement. Over 75% of the API barelly affect consumers with deprecation and 15% of the consumers are affected only by 2 APIs(hibernate-core and mongo-java-driver) [ 57 ].

[ S24 ] investigated working habits and challenges of mobile software developers with respect to testing. A key finding of this exhaustive study, using 1000 Android apps, demonstrates that mobile apps are still tested in a very ad hoc way, if tested at all. However, it is shown that, as in other types of software, testing increases the quality of apps (demonstrated in user ratings and number of code issues). Furthermore, there is evidence that tests are essential when it comes to engaging the community to contribute to mobile open source software. The authors discuss reasons and potential directions to address the findings. Yet another relevant finding of this study is that Continuous Integration and Continuous Deployment (CI/CD) pipelines are rare in the mobile apps world (only 26% of the apps are developed in projects employing CI/CD) - authors argue that one of the main reasons is due to the lack of exhaustive and automatic testing [ 14 ].

[ S25 ] tries to understand the reasons for log changes and, proposes an approach that can provide developers with log change suggestions as soon as they commit a code change, which is referred to as “just-in-time” suggestions for log changes. A set of measures is derived based on manually examining the reasons for log changes and individual experiences. Those measures were used as explanatory variables in random forest classifiers to model whether a code commit requires log changes. These classifiers can provide just-in-time suggestions for log changes and was evaluated with a case study on four open source projects: Hadoop, Directory Server, Commons HttpClient, and Qpid. Findings show that: i) the reasons for log changes can be grouped along four categories: block change, log improvement, dependence-driven change, and logging issue; ii) the random forest classifiers can effectively suggest whether a log change is needed; iii) the characteristics of code changes in a particular commit and the current snapshot of the source code are the most influential factors for determining the likelihood of a log change in a commit [ 34 ].

[ S26 ] designed and conducted, with the continuous feedback of the Xen Project Advisory Board, a detailed analysis focused on finding problems associated with the large increase over time in the number of messages related to code review. The increase was being perceived as a potential signal of problems with their code review process and the usage of metrics was suggested to track the performance of it. As a result, it was learned how in fact the Xen Project had some problems, but at the moment of the analysis those were already under control. It was found as well how diferent the Xen and Netdev projects were behaving with respect to code review performance, despite being so similar from many points of view. A comprehensive methodology, fully automated, to study Linux-style code review was proposed [ 28 ].

[ S27 ] analyzed the Common Vulnerability Scoring System (CVSS) scores and bounty awarded for 703 vulnerabilities across 24 products. CVSS is the de facto standard for vulnerability severity measurement today and is crucial in the analytics driving software fortification. It was found a weak correlation between CVSS scores and bounties, with CVSS being more likely to underestimate bounty. Such a negative result is suggested to be a cause for concern. The authors, investigated why the measurements were so discordant by i) analyzing the individual questions of CVSS with respect to bounties and ii) conducting a qualitative study to find the similarities and diferences between CVSS and the publicly-available criteria for awarding bounties. It was found that the bounty criteria were more explicit about code execution and privilege escalation whereas CVSS makes no explicit mention of those. Another lesson learnt was that bounty valuations are evaluated solely by project maintainers, whereas CVSS has little provenance in practice [ 45 ].

[ S28 ] through a case study on 1,492 high-rated and low-rated free apps mined from the Google Play store, investigated 28 factors along eight dimensions to understand how high-rated apps are different from low-rated apps. The search for the most influential factors was also addressed by applying a random-forest classifier to identify high-rated apps. The results show that high-rated apps are statistically significantly different in 17 out of the 28 factors that we considered. The experiment also presents eveidences for the fact that the size of an app, the number of promotional images that the app displays on its web store page, and the target SDK version of an app are the most influential factors [ 62 ].

[ S29 ] conducted a large-scale study on security-related questions on Stack Overflow. Two heuristics were used to extract from the dataset the questions that are related to security based on the tags of the posts. Later, to cluster different security-related questions based on their texts, an advanced topic model, Latent Dirichlet Allocation (LDA) tuned using Genetic Algorithm (GA) was used. Results show that security-related questions on Stack Overflow cover a wide range of topics, which belong to five main categories: web security, mobile security, cryptography, software security, and system security. Among them, most questions are about web security. In addition, it was found that the top four most popular topics in the security area are “Password”, “Hash”, “Signature” and “SQL Injection”, and the top eight most difficulty security-related topics are “JAVA Security”, “Asymetric Encryption”, “Bug”, “Browser Security”, “Windows Authority”, “Signature”, “ASP.NET” and “Password”, suggesting these are the ones in need for more attention [ 72 ].

[ S30 ] present an approach to recommend analogical libraries based on a knowledge base of analogical libraries mined from tags of millions of Stack Overflow questions. The approach was implemented in a proof-of-concept web application and more than 34.8 thousands of users visited the website from November 2015 to August 2017. Results show evidences that accurate recommendation of analogical libraries is not only possible but also a desirable solution. Authors validated the usefulness of their analogical-library recommendations by using them to answer analogical-library questions in Stack Overflow [ 12 ].

[ S31 ] explored why and how developers fork what from whom in GitHub. This approach was supported by collecting a dataset containing 236,344 developers and 1,841,324 forks. It was also validated by a survey in order to analyze the programming languages and owners of forked repositories. Among the main findings we have: i) Developers fork repositories to submit pull requests, fix bugs, add new features and keep copies etc. Developers find repositories to fork from various sources: search engines, external sites (e.g., Twitter, Reddit), social relationships, etc. More than 42% of developers that were surveyed agree that an automated recommendation tool is useful to help them pick repositories to fork, while more than 44.4% of developers do not value a recommendation tool. Developers care about repository owners when they fork repositories. ii) A repository written in a developers’ preferred programming language is more likely to be forked. iii) Developers mostly fork repositories from creators. In comparison with unattractive repository owners, attractive repository owners have higher percentage of organizations, more followers and earlier registration in GitHub. The results show that forking is mainly used for making contributions of original repositories, and it is beneficial for OSS community. In summary, there is evidence of the value of recommendation and provide important insights for GitHub to recommend repositories [ 30 ].

[ S32 ] designed and executed an empirical study on six open source Java systems to better understand the life expectancy of clones. A random forest classifier was built with the aim of determining the life expectancy of a newly-introduced clone (i.e., whether a clone will be short-lived or longlived) and it was confimed to have good accuracy on that task. Results show that a large number of clones (i.e., 30% to 87%) lived in the systems for a short duration. Moreover, it finds that although short-lived clones were changed more frequently than long-lived clones throughout their lifetime, short-lived clones were consistently changed with their siblings less often than long-lived clones. Findings show that the churn made to the methods containing a newly-introduced clone, the complexity and size of the methods containing the newly- introduced clone are highly influential in determining whether the newly-introduced clone will be short-lived. Furthermore, the size of a newly-introduced clone shares a positive relationship with the likelihood that the newly introduced clone will be short-lived. Results suggest that, to improve the efficiency of clone management efforts, such as the planning of the most effective use of their clone management resources in advance, practitioners can leverage the presented classifiers and insights in order to determine the life expectancy of clones [ 61 ].

[ S33 ] This paper introduces DDP (Data Driven Plataform) platform, a scalable platform to analyze and exploit performance data. This platform centralizes, analyzes and visualizes the performance data produced during the software development cycle. DDP employs big data and analytics technology to collect, store and process performance data in an efficient and integrated way. They have demonstrated the successful application of DDP for Spectrum Scale, a software defined storage solution, where they have been able to implement performance regression data analysis to validate the performance consistency of new produced builds [ 4 ].

[ S34 ] To help the industry practitioners in these situations, a analogy-centered model based on differential evolution exploration process is proposed in this research study. The proposed model has been assessed on 676 projects from 5 different data sets and the results achieved are significantly better when compared with other benchmark analogy-based estimation studies [ 67 ].

[ S35 ] The paper attempts to analyze and compare various methodologies to tune the defect predictors. The research papers which are analyzed here have used data-set from the PROMISE repository, open-source [ 53 ].

[ S36 ] This paper evaluates empirically and theoretically heterogeneous Cross-project defect prediction (HCPDP) modeling, which comprises of three main phases: Feature ranking and feature selection, metric matching, and finally, predicting defects in the target application. The research work has been experimented on 13 benchmarked datasets of three open source projects. Results show that performance of HCPDP is very much comparable to baseline within project defect prediction [ 66 ].

[ S37 ] An anomaly detection system can operate in the staging environment to compare the current incoming release with previous ones according to predefined metrics. The analysis is conducted before going into production to identify anomalies. In this paper, they describe a prototypical implementation of the aforementioned idea in the form of a proof-of-concept [ 10 ].

[ S38 ] This article reports a controlled experiment that compares the effort to implement changes, the correctness and the maintainability of an existing application between two projects; one that uses qualitative dashboards depicting contextual information, and one that does not [ 17 ].

[ S39 ] In this paper conducts an extensive empirical study to evaluate network embedding algorithms in bug prediction by utilizing and extending node2defect, a newly proposed bug prediction model that combines the embedded vectors with traditional software engineering metrics through concatenation. Experiments are conducted based on seven network embedding algorithms,two effort-aware models, and 13 open-source Java systems [ 50 ].

[ S40 ] This paper presents a technology for prescriptive software analytics. Their planner offers users a guidance on what action to take in order to improve the quality of a software project. Our preferred planning tool is BELLTREE, which performs cross-project planning with encouraging results.With our BELLTREE planner, we show that it is possible to reduce several hundred defects in software projects [ 33 ].

[ S41 ] In this paper they investigate whether conclusions in the area of defect prediction, if the claims of the researchers are stable throughout time. This case study provides evidence that in the field of defect prediction the context of evaluation (in our case, time) plays an important role [ 5 ].

[ S42 ] In this paper, they propose a two-step approach to first identify whether a commit describes developer-related refactoring events, then to classify it according to the refactoring common quality improvement categories [ 2 ].

General Statistics

See Fig. 9 , 10 , 11 , 12 , 13 and Table 12 , 13 , 14 , and 15 .

figure 9

Number of studies published by each main author over the years

figure 10

Frequencies of studies per publisher over the years

figure 11

Frequencies of studies for data sources

figure 12

Frequencies of studies for mining methods

figure 13

Frequencies of studies combining multiple RQs in the SLR

Appendix 3: Studies Appraisal

The following acronyms were used for SLR results interpretation (see Table 16 ):

ACM —Analyze and Compare Methodologies, CS -Case Study, CE -Controlled Experiment

ECS —Exploratory Case Study, QE —Quasi-Experiment, S —Survey

SDLC Activities

D —Debugging, I —Implementation, M —Maintenance, O —Operations, T —Testing

Project Stakeholders

D —Developers, E —Educators, EU —End-Users, T —Testers, PM —Product Managers

PjM —Project Managers, R —Researchers, RE —Requirements Engineers

Analytics Scope

Des —Descriptive Analytics, Dia —Diagnostics Analytics

Pred —Predictive Analytics, Pres —Prescriptive Analytics

The following taxonomy was used to assess the SDLC contributions:

The benefit is:

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Caldeira, J., Brito e Abreu, F., Cardoso, J. et al. Software Development Analytics in Practice: A Systematic Literature Review. Arch Computat Methods Eng 30 , 2041–2080 (2023). https://doi.org/10.1007/s11831-022-09864-y

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Literature Review Example/Sample

Detailed Walkthrough + Free Literature Review Template

If you’re working on a dissertation or thesis and are looking for an example of a strong literature review chapter , you’ve come to the right place.

In this video, we walk you through an A-grade literature review from a dissertation that earned full distinction . We start off by discussing the five core sections of a literature review chapter by unpacking our free literature review template . This includes:

  • The literature review opening/ introduction section
  • The theoretical framework (or foundation of theory)
  • The empirical research
  • The research gap
  • The closing section

We then progress to the sample literature review (from an A-grade Master’s-level dissertation) to show how these concepts are applied in the literature review chapter. You can access the free resources mentioned in this video below.

PS – If you’re working on a dissertation, be sure to also check out our collection of dissertation and thesis examples here .

FAQ: Literature Review Example

Literature review example: frequently asked questions, is the sample literature review real.

Yes. The literature review example is an extract from a Master’s-level dissertation for an MBA program. It has not been edited in any way.

Can I replicate this literature review for my dissertation?

As we discuss in the video, every literature review will be slightly different, depending on the university’s unique requirements, as well as the nature of the research itself. Therefore, you’ll need to tailor your literature review to suit your specific context.

You can learn more about the basics of writing a literature review here .

Where can I find more examples of literature reviews?

The best place to find more examples of literature review chapters would be within dissertation/thesis databases. These databases include dissertations, theses and research projects that have successfully passed the assessment criteria for the respective university, meaning that you have at least some sort of quality assurance. 

The Open Access Thesis Database (OATD) is a good starting point. 

How do I get the literature review template?

You can access our free literature review chapter template here .

Is the template really free?

Yes. There is no cost for the template and you are free to use it as you wish. 

Literature Review Course

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This post is an extract from our bestselling short course, Literature Review Bootcamp . If you want to work smart, you don't want to miss this .

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How to make literature review for a software implementation project?

I don't know if this is out of the scope of this website. I'm a student in software engineering deparment and I am supposed to make a project for a course during the semester. The first step of it is to prepare a project proposal which consists of a short description of the project, a literature review and detailed flowcharts. My question is how to make literature review for a software implementation project. I already did some reviews from some articles which I found from sciencedirect, and already wrote an introduction for the review. I don't know whether I have to put web links as references when I mention already existing similar projects inside the body or if it should only contain academic citations.

Thank you in advance for your help.

  • academic-writing

VOLKAN BAKIR's user avatar

  • Related: writing.stackexchange.com/q/5376/14704 –  Galastel supports GoFundMonica Commented Oct 21, 2018 at 18:40

Any source that you use in your work, be it academic literature, websites, or even tv programs, needs to be cited. Similar projects are extremely relevant to what you're doing, and therefore if your source on them is a website rather than an academic work, it should definitely be cited.

When you cite a website, you include its name, link, date content was written (if stated), and the date you accessed it (since content might later be changed).

Or did you mean, do you need to include a link to the academic article you're citing? In that case, no, you don't.

Your department would have a standard for how they want citations formatted (formats vary somewhat between fields, and between journals etc. in the same field). You can ask your advisor, he'll point you to how exactly sources should be cited.

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sample literature review of software project

sample literature review of software project

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What is a Literature Review? How to Write It (with Examples)

literature review

A literature review is a critical analysis and synthesis of existing research on a particular topic. It provides an overview of the current state of knowledge, identifies gaps, and highlights key findings in the literature. 1 The purpose of a literature review is to situate your own research within the context of existing scholarship, demonstrating your understanding of the topic and showing how your work contributes to the ongoing conversation in the field. Learning how to write a literature review is a critical tool for successful research. Your ability to summarize and synthesize prior research pertaining to a certain topic demonstrates your grasp on the topic of study, and assists in the learning process. 

Table of Contents

  • What is the purpose of literature review? 
  • a. Habitat Loss and Species Extinction: 
  • b. Range Shifts and Phenological Changes: 
  • c. Ocean Acidification and Coral Reefs: 
  • d. Adaptive Strategies and Conservation Efforts: 

How to write a good literature review 

  • Choose a Topic and Define the Research Question: 
  • Decide on the Scope of Your Review: 
  • Select Databases for Searches: 
  • Conduct Searches and Keep Track: 
  • Review the Literature: 
  • Organize and Write Your Literature Review: 
  • How to write a literature review faster with Paperpal? 
  • Frequently asked questions 

What is a literature review?

A well-conducted literature review demonstrates the researcher’s familiarity with the existing literature, establishes the context for their own research, and contributes to scholarly conversations on the topic. One of the purposes of a literature review is also to help researchers avoid duplicating previous work and ensure that their research is informed by and builds upon the existing body of knowledge.

sample literature review of software project

What is the purpose of literature review?

A literature review serves several important purposes within academic and research contexts. Here are some key objectives and functions of a literature review: 2  

1. Contextualizing the Research Problem: The literature review provides a background and context for the research problem under investigation. It helps to situate the study within the existing body of knowledge. 

2. Identifying Gaps in Knowledge: By identifying gaps, contradictions, or areas requiring further research, the researcher can shape the research question and justify the significance of the study. This is crucial for ensuring that the new research contributes something novel to the field. 

Find academic papers related to your research topic faster. Try Research on Paperpal  

3. Understanding Theoretical and Conceptual Frameworks: Literature reviews help researchers gain an understanding of the theoretical and conceptual frameworks used in previous studies. This aids in the development of a theoretical framework for the current research. 

4. Providing Methodological Insights: Another purpose of literature reviews is that it allows researchers to learn about the methodologies employed in previous studies. This can help in choosing appropriate research methods for the current study and avoiding pitfalls that others may have encountered. 

5. Establishing Credibility: A well-conducted literature review demonstrates the researcher’s familiarity with existing scholarship, establishing their credibility and expertise in the field. It also helps in building a solid foundation for the new research. 

6. Informing Hypotheses or Research Questions: The literature review guides the formulation of hypotheses or research questions by highlighting relevant findings and areas of uncertainty in existing literature. 

Literature review example

Let’s delve deeper with a literature review example: Let’s say your literature review is about the impact of climate change on biodiversity. You might format your literature review into sections such as the effects of climate change on habitat loss and species extinction, phenological changes, and marine biodiversity. Each section would then summarize and analyze relevant studies in those areas, highlighting key findings and identifying gaps in the research. The review would conclude by emphasizing the need for further research on specific aspects of the relationship between climate change and biodiversity. The following literature review template provides a glimpse into the recommended literature review structure and content, demonstrating how research findings are organized around specific themes within a broader topic. 

Literature Review on Climate Change Impacts on Biodiversity:

Climate change is a global phenomenon with far-reaching consequences, including significant impacts on biodiversity. This literature review synthesizes key findings from various studies: 

a. Habitat Loss and Species Extinction:

Climate change-induced alterations in temperature and precipitation patterns contribute to habitat loss, affecting numerous species (Thomas et al., 2004). The review discusses how these changes increase the risk of extinction, particularly for species with specific habitat requirements. 

b. Range Shifts and Phenological Changes:

Observations of range shifts and changes in the timing of biological events (phenology) are documented in response to changing climatic conditions (Parmesan & Yohe, 2003). These shifts affect ecosystems and may lead to mismatches between species and their resources. 

c. Ocean Acidification and Coral Reefs:

The review explores the impact of climate change on marine biodiversity, emphasizing ocean acidification’s threat to coral reefs (Hoegh-Guldberg et al., 2007). Changes in pH levels negatively affect coral calcification, disrupting the delicate balance of marine ecosystems. 

d. Adaptive Strategies and Conservation Efforts:

Recognizing the urgency of the situation, the literature review discusses various adaptive strategies adopted by species and conservation efforts aimed at mitigating the impacts of climate change on biodiversity (Hannah et al., 2007). It emphasizes the importance of interdisciplinary approaches for effective conservation planning. 

sample literature review of software project

Strengthen your literature review with factual insights. Try Research on Paperpal for free!    

Writing a literature review involves summarizing and synthesizing existing research on a particular topic. A good literature review format should include the following elements. 

Introduction: The introduction sets the stage for your literature review, providing context and introducing the main focus of your review. 

  • Opening Statement: Begin with a general statement about the broader topic and its significance in the field. 
  • Scope and Purpose: Clearly define the scope of your literature review. Explain the specific research question or objective you aim to address. 
  • Organizational Framework: Briefly outline the structure of your literature review, indicating how you will categorize and discuss the existing research. 
  • Significance of the Study: Highlight why your literature review is important and how it contributes to the understanding of the chosen topic. 
  • Thesis Statement: Conclude the introduction with a concise thesis statement that outlines the main argument or perspective you will develop in the body of the literature review. 

Body: The body of the literature review is where you provide a comprehensive analysis of existing literature, grouping studies based on themes, methodologies, or other relevant criteria. 

  • Organize by Theme or Concept: Group studies that share common themes, concepts, or methodologies. Discuss each theme or concept in detail, summarizing key findings and identifying gaps or areas of disagreement. 
  • Critical Analysis: Evaluate the strengths and weaknesses of each study. Discuss the methodologies used, the quality of evidence, and the overall contribution of each work to the understanding of the topic. 
  • Synthesis of Findings: Synthesize the information from different studies to highlight trends, patterns, or areas of consensus in the literature. 
  • Identification of Gaps: Discuss any gaps or limitations in the existing research and explain how your review contributes to filling these gaps. 
  • Transition between Sections: Provide smooth transitions between different themes or concepts to maintain the flow of your literature review. 

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Conclusion: The conclusion of your literature review should summarize the main findings, highlight the contributions of the review, and suggest avenues for future research. 

  • Summary of Key Findings: Recap the main findings from the literature and restate how they contribute to your research question or objective. 
  • Contributions to the Field: Discuss the overall contribution of your literature review to the existing knowledge in the field. 
  • Implications and Applications: Explore the practical implications of the findings and suggest how they might impact future research or practice. 
  • Recommendations for Future Research: Identify areas that require further investigation and propose potential directions for future research in the field. 
  • Final Thoughts: Conclude with a final reflection on the importance of your literature review and its relevance to the broader academic community. 

what is a literature review

Conducting a literature review

Conducting a literature review is an essential step in research that involves reviewing and analyzing existing literature on a specific topic. It’s important to know how to do a literature review effectively, so here are the steps to follow: 1  

Choose a Topic and Define the Research Question:

  • Select a topic that is relevant to your field of study. 
  • Clearly define your research question or objective. Determine what specific aspect of the topic do you want to explore? 

Decide on the Scope of Your Review:

  • Determine the timeframe for your literature review. Are you focusing on recent developments, or do you want a historical overview? 
  • Consider the geographical scope. Is your review global, or are you focusing on a specific region? 
  • Define the inclusion and exclusion criteria. What types of sources will you include? Are there specific types of studies or publications you will exclude? 

Select Databases for Searches:

  • Identify relevant databases for your field. Examples include PubMed, IEEE Xplore, Scopus, Web of Science, and Google Scholar. 
  • Consider searching in library catalogs, institutional repositories, and specialized databases related to your topic. 

Conduct Searches and Keep Track:

  • Develop a systematic search strategy using keywords, Boolean operators (AND, OR, NOT), and other search techniques. 
  • Record and document your search strategy for transparency and replicability. 
  • Keep track of the articles, including publication details, abstracts, and links. Use citation management tools like EndNote, Zotero, or Mendeley to organize your references. 

Review the Literature:

  • Evaluate the relevance and quality of each source. Consider the methodology, sample size, and results of studies. 
  • Organize the literature by themes or key concepts. Identify patterns, trends, and gaps in the existing research. 
  • Summarize key findings and arguments from each source. Compare and contrast different perspectives. 
  • Identify areas where there is a consensus in the literature and where there are conflicting opinions. 
  • Provide critical analysis and synthesis of the literature. What are the strengths and weaknesses of existing research? 

Organize and Write Your Literature Review:

  • Literature review outline should be based on themes, chronological order, or methodological approaches. 
  • Write a clear and coherent narrative that synthesizes the information gathered. 
  • Use proper citations for each source and ensure consistency in your citation style (APA, MLA, Chicago, etc.). 
  • Conclude your literature review by summarizing key findings, identifying gaps, and suggesting areas for future research. 

Whether you’re exploring a new research field or finding new angles to develop an existing topic, sifting through hundreds of papers can take more time than you have to spare. But what if you could find science-backed insights with verified citations in seconds? That’s the power of Paperpal’s new Research feature!  

How to write a literature review faster with Paperpal?

Paperpal, an AI writing assistant, integrates powerful academic search capabilities within its writing platform. With the Research feature, you get 100% factual insights, with citations backed by 250M+ verified research articles, directly within your writing interface with the option to save relevant references in your Citation Library. By eliminating the need to switch tabs to find answers to all your research questions, Paperpal saves time and helps you stay focused on your writing.   

Here’s how to use the Research feature:  

  • Ask a question: Get started with a new document on paperpal.com. Click on the “Research” feature and type your question in plain English. Paperpal will scour over 250 million research articles, including conference papers and preprints, to provide you with accurate insights and citations. 
  • Review and Save: Paperpal summarizes the information, while citing sources and listing relevant reads. You can quickly scan the results to identify relevant references and save these directly to your built-in citations library for later access. 
  • Cite with Confidence: Paperpal makes it easy to incorporate relevant citations and references into your writing, ensuring your arguments are well-supported by credible sources. This translates to a polished, well-researched literature review. 

The literature review sample and detailed advice on writing and conducting a review will help you produce a well-structured report. But remember that a good literature review is an ongoing process, and it may be necessary to revisit and update it as your research progresses. By combining effortless research with an easy citation process, Paperpal Research streamlines the literature review process and empowers you to write faster and with more confidence. Try Paperpal Research now and see for yourself.  

Frequently asked questions

A literature review is a critical and comprehensive analysis of existing literature (published and unpublished works) on a specific topic or research question and provides a synthesis of the current state of knowledge in a particular field. A well-conducted literature review is crucial for researchers to build upon existing knowledge, avoid duplication of efforts, and contribute to the advancement of their field. It also helps researchers situate their work within a broader context and facilitates the development of a sound theoretical and conceptual framework for their studies.

Literature review is a crucial component of research writing, providing a solid background for a research paper’s investigation. The aim is to keep professionals up to date by providing an understanding of ongoing developments within a specific field, including research methods, and experimental techniques used in that field, and present that knowledge in the form of a written report. Also, the depth and breadth of the literature review emphasizes the credibility of the scholar in his or her field.  

Before writing a literature review, it’s essential to undertake several preparatory steps to ensure that your review is well-researched, organized, and focused. This includes choosing a topic of general interest to you and doing exploratory research on that topic, writing an annotated bibliography, and noting major points, especially those that relate to the position you have taken on the topic. 

Literature reviews and academic research papers are essential components of scholarly work but serve different purposes within the academic realm. 3 A literature review aims to provide a foundation for understanding the current state of research on a particular topic, identify gaps or controversies, and lay the groundwork for future research. Therefore, it draws heavily from existing academic sources, including books, journal articles, and other scholarly publications. In contrast, an academic research paper aims to present new knowledge, contribute to the academic discourse, and advance the understanding of a specific research question. Therefore, it involves a mix of existing literature (in the introduction and literature review sections) and original data or findings obtained through research methods. 

Literature reviews are essential components of academic and research papers, and various strategies can be employed to conduct them effectively. If you want to know how to write a literature review for a research paper, here are four common approaches that are often used by researchers.  Chronological Review: This strategy involves organizing the literature based on the chronological order of publication. It helps to trace the development of a topic over time, showing how ideas, theories, and research have evolved.  Thematic Review: Thematic reviews focus on identifying and analyzing themes or topics that cut across different studies. Instead of organizing the literature chronologically, it is grouped by key themes or concepts, allowing for a comprehensive exploration of various aspects of the topic.  Methodological Review: This strategy involves organizing the literature based on the research methods employed in different studies. It helps to highlight the strengths and weaknesses of various methodologies and allows the reader to evaluate the reliability and validity of the research findings.  Theoretical Review: A theoretical review examines the literature based on the theoretical frameworks used in different studies. This approach helps to identify the key theories that have been applied to the topic and assess their contributions to the understanding of the subject.  It’s important to note that these strategies are not mutually exclusive, and a literature review may combine elements of more than one approach. The choice of strategy depends on the research question, the nature of the literature available, and the goals of the review. Additionally, other strategies, such as integrative reviews or systematic reviews, may be employed depending on the specific requirements of the research.

The literature review format can vary depending on the specific publication guidelines. However, there are some common elements and structures that are often followed. Here is a general guideline for the format of a literature review:  Introduction:   Provide an overview of the topic.  Define the scope and purpose of the literature review.  State the research question or objective.  Body:   Organize the literature by themes, concepts, or chronology.  Critically analyze and evaluate each source.  Discuss the strengths and weaknesses of the studies.  Highlight any methodological limitations or biases.  Identify patterns, connections, or contradictions in the existing research.  Conclusion:   Summarize the key points discussed in the literature review.  Highlight the research gap.  Address the research question or objective stated in the introduction.  Highlight the contributions of the review and suggest directions for future research.

Both annotated bibliographies and literature reviews involve the examination of scholarly sources. While annotated bibliographies focus on individual sources with brief annotations, literature reviews provide a more in-depth, integrated, and comprehensive analysis of existing literature on a specific topic. The key differences are as follows: 

 Annotated Bibliography Literature Review 
Purpose List of citations of books, articles, and other sources with a brief description (annotation) of each source. Comprehensive and critical analysis of existing literature on a specific topic. 
Focus Summary and evaluation of each source, including its relevance, methodology, and key findings. Provides an overview of the current state of knowledge on a particular subject and identifies gaps, trends, and patterns in existing literature. 
Structure Each citation is followed by a concise paragraph (annotation) that describes the source’s content, methodology, and its contribution to the topic. The literature review is organized thematically or chronologically and involves a synthesis of the findings from different sources to build a narrative or argument. 
Length Typically 100-200 words Length of literature review ranges from a few pages to several chapters 
Independence Each source is treated separately, with less emphasis on synthesizing the information across sources. The writer synthesizes information from multiple sources to present a cohesive overview of the topic. 


  • Denney, A. S., & Tewksbury, R. (2013). How to write a literature review.  Journal of criminal justice education ,  24 (2), 218-234. 
  • Pan, M. L. (2016).  Preparing literature reviews: Qualitative and quantitative approaches . Taylor & Francis. 
  • Cantero, C. (2019). How to write a literature review.  San José State University Writing Center . 

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15 Literature Review Examples

15 Literature Review Examples

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

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literature review examples, types, and definition, explained below

Literature reviews are a necessary step in a research process and often required when writing your research proposal . They involve gathering, analyzing, and evaluating existing knowledge about a topic in order to find gaps in the literature where future studies will be needed.

Ideally, once you have completed your literature review, you will be able to identify how your research project can build upon and extend existing knowledge in your area of study.

Generally, for my undergraduate research students, I recommend a narrative review, where themes can be generated in order for the students to develop sufficient understanding of the topic so they can build upon the themes using unique methods or novel research questions.

If you’re in the process of writing a literature review, I have developed a literature review template for you to use – it’s a huge time-saver and walks you through how to write a literature review step-by-step:

Get your time-saving templates here to write your own literature review.

Literature Review Examples

For the following types of literature review, I present an explanation and overview of the type, followed by links to some real-life literature reviews on the topics.

1. Narrative Review Examples

Also known as a traditional literature review, the narrative review provides a broad overview of the studies done on a particular topic.

It often includes both qualitative and quantitative studies and may cover a wide range of years.

The narrative review’s purpose is to identify commonalities, gaps, and contradictions in the literature .

I recommend to my students that they should gather their studies together, take notes on each study, then try to group them by themes that form the basis for the review (see my step-by-step instructions at the end of the article).

Example Study

Title: Communication in healthcare: a narrative review of the literature and practical recommendations

Citation: Vermeir, P., Vandijck, D., Degroote, S., Peleman, R., Verhaeghe, R., Mortier, E., … & Vogelaers, D. (2015). Communication in healthcare: a narrative review of the literature and practical recommendations. International journal of clinical practice , 69 (11), 1257-1267.

Source: https://onlinelibrary.wiley.com/doi/pdf/10.1111/ijcp.12686  

Overview: This narrative review analyzed themes emerging from 69 articles about communication in healthcare contexts. Five key themes were found in the literature: poor communication can lead to various negative outcomes, discontinuity of care, compromise of patient safety, patient dissatisfaction, and inefficient use of resources. After presenting the key themes, the authors recommend that practitioners need to approach healthcare communication in a more structured way, such as by ensuring there is a clear understanding of who is in charge of ensuring effective communication in clinical settings.

Other Examples

  • Burnout in United States Healthcare Professionals: A Narrative Review (Reith, 2018) – read here
  • Examining the Presence, Consequences, and Reduction of Implicit Bias in Health Care: A Narrative Review (Zestcott, Blair & Stone, 2016) – read here
  • A Narrative Review of School-Based Physical Activity for Enhancing Cognition and Learning (Mavilidi et al., 2018) – read here
  • A narrative review on burnout experienced by medical students and residents (Dyrbye & Shanafelt, 2015) – read here

2. Systematic Review Examples

This type of literature review is more structured and rigorous than a narrative review. It involves a detailed and comprehensive plan and search strategy derived from a set of specified research questions.

The key way you’d know a systematic review compared to a narrative review is in the methodology: the systematic review will likely have a very clear criteria for how the studies were collected, and clear explanations of exclusion/inclusion criteria. 

The goal is to gather the maximum amount of valid literature on the topic, filter out invalid or low-quality reviews, and minimize bias. Ideally, this will provide more reliable findings, leading to higher-quality conclusions and recommendations for further research.

You may note from the examples below that the ‘method’ sections in systematic reviews tend to be much more explicit, often noting rigid inclusion/exclusion criteria and exact keywords used in searches.

Title: The importance of food naturalness for consumers: Results of a systematic review  

Citation: Roman, S., Sánchez-Siles, L. M., & Siegrist, M. (2017). The importance of food naturalness for consumers: Results of a systematic review. Trends in food science & technology , 67 , 44-57.

Source: https://www.sciencedirect.com/science/article/pii/S092422441730122X  

Overview: This systematic review included 72 studies of food naturalness to explore trends in the literature about its importance for consumers. Keywords used in the data search included: food, naturalness, natural content, and natural ingredients. Studies were included if they examined consumers’ preference for food naturalness and contained empirical data. The authors found that the literature lacks clarity about how naturalness is defined and measured, but also found that food consumption is significantly influenced by perceived naturalness of goods.

  • A systematic review of research on online teaching and learning from 2009 to 2018 (Martin, Sun & Westine, 2020) – read here
  • Where Is Current Research on Blockchain Technology? (Yli-Huumo et al., 2016) – read here
  • Universities—industry collaboration: A systematic review (Ankrah & Al-Tabbaa, 2015) – read here
  • Internet of Things Applications: A Systematic Review (Asghari, Rahmani & Javadi, 2019) – read here

3. Meta-analysis

This is a type of systematic review that uses statistical methods to combine and summarize the results of several studies.

Due to its robust methodology, a meta-analysis is often considered the ‘gold standard’ of secondary research , as it provides a more precise estimate of a treatment effect than any individual study contributing to the pooled analysis.

Furthermore, by aggregating data from a range of studies, a meta-analysis can identify patterns, disagreements, or other interesting relationships that may have been hidden in individual studies.

This helps to enhance the generalizability of findings, making the conclusions drawn from a meta-analysis particularly powerful and informative for policy and practice.

Title: Cholesterol and Alzheimer’s Disease Risk: A Meta-Meta-Analysis

Citation: Sáiz-Vazquez, O., Puente-Martínez, A., Ubillos-Landa, S., Pacheco-Bonrostro, J., & Santabárbara, J. (2020). Cholesterol and Alzheimer’s disease risk: a meta-meta-analysis. Brain sciences, 10(6), 386.

Source: https://doi.org/10.3390/brainsci10060386  

O verview: This study examines the relationship between cholesterol and Alzheimer’s disease (AD). Researchers conducted a systematic search of meta-analyses and reviewed several databases, collecting 100 primary studies and five meta-analyses to analyze the connection between cholesterol and Alzheimer’s disease. They find that the literature compellingly demonstrates that low-density lipoprotein cholesterol (LDL-C) levels significantly influence the development of Alzheimer’s disease.

  • The power of feedback revisited: A meta-analysis of educational feedback research (Wisniewski, Zierer & Hattie, 2020) – read here
  • How Much Does Education Improve Intelligence? A Meta-Analysis (Ritchie & Tucker-Drob, 2018) – read here
  • A meta-analysis of factors related to recycling (Geiger et al., 2019) – read here
  • Stress management interventions for police officers and recruits (Patterson, Chung & Swan, 2014) – read here

Other Types of Reviews

  • Scoping Review: This type of review is used to map the key concepts underpinning a research area and the main sources and types of evidence available. It can be undertaken as stand-alone projects in their own right, or as a precursor to a systematic review.
  • Rapid Review: This type of review accelerates the systematic review process in order to produce information in a timely manner. This is achieved by simplifying or omitting stages of the systematic review process.
  • Integrative Review: This review method is more inclusive than others, allowing for the simultaneous inclusion of experimental and non-experimental research. The goal is to more comprehensively understand a particular phenomenon.
  • Critical Review: This is similar to a narrative review but requires a robust understanding of both the subject and the existing literature. In a critical review, the reviewer not only summarizes the existing literature, but also evaluates its strengths and weaknesses. This is common in the social sciences and humanities .
  • State-of-the-Art Review: This considers the current level of advancement in a field or topic and makes recommendations for future research directions. This type of review is common in technological and scientific fields but can be applied to any discipline.

How to Write a Narrative Review (Tips for Undergrad Students)

Most undergraduate students conducting a capstone research project will be writing narrative reviews. Below is a five-step process for conducting a simple review of the literature for your project.

  • Search for Relevant Literature: Use scholarly databases related to your field of study, provided by your university library, along with appropriate search terms to identify key scholarly articles that have been published on your topic.
  • Evaluate and Select Sources: Filter the source list by selecting studies that are directly relevant and of sufficient quality, considering factors like credibility , objectivity, accuracy, and validity.
  • Analyze and Synthesize: Review each source and summarize the main arguments  in one paragraph (or more, for postgrad). Keep these summaries in a table.
  • Identify Themes: With all studies summarized, group studies that share common themes, such as studies that have similar findings or methodologies.
  • Write the Review: Write your review based upon the themes or subtopics you have identified. Give a thorough overview of each theme, integrating source data, and conclude with a summary of the current state of knowledge then suggestions for future research based upon your evaluation of what is lacking in the literature.

Literature reviews don’t have to be as scary as they seem. Yes, they are difficult and require a strong degree of comprehension of academic studies. But it can be feasibly done through following a structured approach to data collection and analysis. With my undergraduate research students (who tend to conduct small-scale qualitative studies ), I encourage them to conduct a narrative literature review whereby they can identify key themes in the literature. Within each theme, students can critique key studies and their strengths and limitations , in order to get a lay of the land and come to a point where they can identify ways to contribute new insights to the existing academic conversation on their topic.

Ankrah, S., & Omar, A. T. (2015). Universities–industry collaboration: A systematic review. Scandinavian Journal of Management, 31(3), 387-408.

Asghari, P., Rahmani, A. M., & Javadi, H. H. S. (2019). Internet of Things applications: A systematic review. Computer Networks , 148 , 241-261.

Dyrbye, L., & Shanafelt, T. (2016). A narrative review on burnout experienced by medical students and residents. Medical education , 50 (1), 132-149.

Geiger, J. L., Steg, L., Van Der Werff, E., & Ünal, A. B. (2019). A meta-analysis of factors related to recycling. Journal of environmental psychology , 64 , 78-97.

Martin, F., Sun, T., & Westine, C. D. (2020). A systematic review of research on online teaching and learning from 2009 to 2018. Computers & education , 159 , 104009.

Mavilidi, M. F., Ruiter, M., Schmidt, M., Okely, A. D., Loyens, S., Chandler, P., & Paas, F. (2018). A narrative review of school-based physical activity for enhancing cognition and learning: The importance of relevancy and integration. Frontiers in psychology , 2079.

Patterson, G. T., Chung, I. W., & Swan, P. W. (2014). Stress management interventions for police officers and recruits: A meta-analysis. Journal of experimental criminology , 10 , 487-513.

Reith, T. P. (2018). Burnout in United States healthcare professionals: a narrative review. Cureus , 10 (12).

Ritchie, S. J., & Tucker-Drob, E. M. (2018). How much does education improve intelligence? A meta-analysis. Psychological science , 29 (8), 1358-1369.

Roman, S., Sánchez-Siles, L. M., & Siegrist, M. (2017). The importance of food naturalness for consumers: Results of a systematic review. Trends in food science & technology , 67 , 44-57.

Sáiz-Vazquez, O., Puente-Martínez, A., Ubillos-Landa, S., Pacheco-Bonrostro, J., & Santabárbara, J. (2020). Cholesterol and Alzheimer’s disease risk: a meta-meta-analysis. Brain sciences, 10(6), 386.

Vermeir, P., Vandijck, D., Degroote, S., Peleman, R., Verhaeghe, R., Mortier, E., … & Vogelaers, D. (2015). Communication in healthcare: a narrative review of the literature and practical recommendations. International journal of clinical practice , 69 (11), 1257-1267.

Wisniewski, B., Zierer, K., & Hattie, J. (2020). The power of feedback revisited: A meta-analysis of educational feedback research. Frontiers in Psychology , 10 , 3087.

Yli-Huumo, J., Ko, D., Choi, S., Park, S., & Smolander, K. (2016). Where is current research on blockchain technology?—a systematic review. PloS one , 11 (10), e0163477.

Zestcott, C. A., Blair, I. V., & Stone, J. (2016). Examining the presence, consequences, and reduction of implicit bias in health care: a narrative review. Group Processes & Intergroup Relations , 19 (4), 528-542


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Engineering: The Literature Review Process

  • How to Use This Guide

What is a literature review and why is it important?

Further reading ....

  • 2. Precision vs Retrieval
  • 3. Equip Your Tool Box
  • 4. What to look for
  • 5. Where to Look for it
  • 6. How to Look for it
  • 7. Keeping Current
  • 8. Reading Tips
  • 9. Writing Tips
  • 10. Checklist

A literature review not only summarizes the knowledge of a particular area or field of study, it also evaluates what has been done, what still needs to be done and why all of this is important to the subject.  

  • The Stand-Alone Literature Review A literature review may stand alone as an individual document in which the history of the topic is reported and then analyzed for trends, controversial issues, and what still needs to be studied.  The review could just be a few pages for narrow topics or quite extensive with long bibliographies for in-depth reviews.   In-depth review articles are valuable time-savers for professionals and researchers who need a quick introduction or analysis of a topic but they can be very time-consuming for authors to produce. Examples of review articles:   Walker, Sara Louise (2011)   Building mounted wind turbines and their suitability for the urban scale - a review of methods of estimating urban wind resource .   Energy and Buildings  43(8):1852-1862. For this review, the author focused on the different methodologies used to estimate wind speed in urban settings.  After introducing the theory, she explained the difficulty for in-situ measuring, and then followed up by describing each of the different estimation techniques that have been used instead.  Strengths and weaknesses of each method are discussed and suggestions are given on where more study is needed.   Length: 11 pages. References: 59. Calm, J.M. (2008)   The next generation of refrigerants - historical review, considerations, and outlook.   International Journal of Refrigeration  31(7):1123-1133. This review focuses on the evolution of refrigerants and divides the evolution into 4 generations.  In each generation the author describes which type of refrigerants were most popular and discusses how political, environmental, and economic issues as well as chemical properties effected choices.  Length: 11 pages.  References: 51.  
  • The Literature Review as a Section Within a Document Literature reviews are also part of dissertations, theses, research reports and scholarly journal articles; these types of documents include the review in a section or chapter that discusses what has gone before, how the research being presented in this document fills a gap in the field's knowledge and why that is important.   Examples of literature reviews within a journal article:  Jobert, Arthur, et al. (2007) Local acceptance of wind energy: factors of success identified in French and German case studies.  Energy Policy  35(5):2751-2760.  In this case, the literature review is a separate, labeled section appearing between the introduction and methodology sections.  Peel, Deborah and Lloyd, Michael Gregory (2007)   Positive planning for wind-turbines in an urban context.   Local Environment  12(4):343-354. In this case the literature review is incorporated into the article's introduction rather than have its own section.   Which version you choose (separate section or within the introduction) depends on format requirements of the publisher (for journal articles), the ASU Graduate College and your academic unit (for ASU dissertations and theses) and application instructions for grants.   If no format is specified choose the method in which you can best explain your research topic, what has come before and the importance of the knowledge you are adding to the field.    Examples of literature reviews within a dissertation or thesis :  Porter, Wayne Eliot (2011)   Renewable Energy in Rural Southeastern Arizona: Decision Factors: A Comparison of the Consumer Profiles of Homeowners Who Purchased Renewable Energy Systems With Those Who Performed Other Home Upgrades or Remodeling Projects .    Arizona State University, M.S. Thesis.  This author effectively uses a separate chapter for the literature review for his detailed analysis.  Magerman, Beth (2014)   Short-Term Wind Power Forecasts using Doppler Lidar.   Arizona State University, M.S. Thesis. The author puts the literature review within Chapter Two presenting it as part of the background information of her topic.   Note that the literature review within a thesis or dissertation more closely resembles the scope and depth of a stand- alone literature review as opposed to the briefer reviews appearing within journal articles.  Within a thesis or dissertation, the review not only presents the status of research in the specific area it also establishes the author's expertise and justifies his/her own research.   

Online tutorials:

  • Literature Reviews: An Overview for Graduate Students Created by the North Caroline State University Libraries

Other ASU Library Guides: 

  • Literature Reviews and Annotated Bibliographies More general information about the format and content of literature reviews; created by Ed Oetting, History and Political Science Librarian, Hayden Library. ​


  • The Literature Review: A Few Tips on Conducting It Written by Dena Taylor, Health Sciences Writing Centre, University of Toronto
  • Literature Reviews Created by The Writing Center at the University of North Carolina, Chapel Hill. 
  • << Previous: How to Use This Guide
  • Next: 2. Precision vs Retrieval >>
  • Last updated: Jan 2, 2024 8:27 AM
  • URL: https://libguides.asu.edu/engineeringlitreview

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All-in-one Literature Review Software

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MAXQDA The All-in-one Literature Review Software

MAXQDA is the best choice for a comprehensive literature review. It works with a wide range of data types and offers powerful tools for literature review, such as reference management, qualitative, vocabulary, text analysis tools, and more.

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Your analysis.

Literature Review Software MAXQDA Interface

As your all-in-one literature review software, MAXQDA can be used to manage your entire research project. Easily import data from texts, interviews, focus groups, PDFs, web pages, spreadsheets, articles, e-books, and even social media data. Connect the reference management system of your choice with MAXQDA to easily import bibliographic data. Organize your data in groups, link relevant quotes to each other, keep track of your literature summaries, and share and compare work with your team members. Your project file stays flexible and you can expand and refine your category system as you go to suit your research.

Developed by and for researchers – since 1989

sample literature review of software project

Having used several qualitative data analysis software programs, there is no doubt in my mind that MAXQDA has advantages over all the others. In addition to its remarkable analytical features for harnessing data, MAXQDA’s stellar customer service, online tutorials, and global learning community make it a user friendly and top-notch product.

Sally S. Cohen – NYU Rory Meyers College of Nursing

Literature Review is Faster and Smarter with MAXQDA

All-in-one Literature Review Software MAXQDA: Import of documents

Easily import your literature review data

With a literature review software like MAXQDA, you can easily import bibliographic data from reference management programs for your literature review. MAXQDA can work with all reference management programs that can export their databases in RIS-format which is a standard format for bibliographic information. Like MAXQDA, these reference managers use project files, containing all collected bibliographic information, such as author, title, links to websites, keywords, abstracts, and other information. In addition, you can easily import the corresponding full texts. Upon import, all documents will be automatically pre-coded to facilitate your literature review at a later stage.

Capture your ideas while analyzing your literature

Great ideas will often occur to you while you’re doing your literature review. Using MAXQDA as your literature review software, you can create memos to store your ideas, such as research questions and objectives, or you can use memos for paraphrasing passages into your own words. By attaching memos like post-it notes to text passages, texts, document groups, images, audio/video clips, and of course codes, you can easily retrieve them at a later stage. Particularly useful for literature reviews are free memos written during the course of work from which passages can be copied and inserted into the final text.

Using Literature Review Software MAXQDA to Organize Your Qualitative Data: Memo Tools

Find concepts important to your generated literature review

When generating a literature review you might need to analyze a large amount of text. Luckily MAXQDA as the #1 literature review software offers Text Search tools that allow you to explore your documents without reading or coding them first. Automatically search for keywords (or dictionaries of keywords), such as important concepts for your literature review, and automatically code them with just a few clicks. Document variables that were automatically created during the import of your bibliographic information can be used for searching and retrieving certain text segments. MAXQDA’s powerful Coding Query allows you to analyze the combination of activated codes in different ways.

Aggregate your literature review

When conducting a literature review you can easily get lost. But with MAXQDA as your literature review software, you will never lose track of the bigger picture. Among other tools, MAXQDA’s overview and summary tables are especially useful for aggregating your literature review results. MAXQDA offers overview tables for almost everything, codes, memos, coded segments, links, and so on. With MAXQDA literature review tools you can create compressed summaries of sources that can be effectively compared and represented, and with just one click you can easily export your overview and summary tables and integrate them into your literature review report.

Visual text exploration with MAXQDA's Word Tree

Powerful and easy-to-use literature review tools

Quantitative aspects can also be relevant when conducting a literature review analysis. Using MAXQDA as your literature review software enables you to employ a vast range of procedures for the quantitative evaluation of your material. You can sort sources according to document variables, compare amounts with frequency tables and charts, and much more. Make sure you don’t miss the word frequency tools of MAXQDA’s add-on module for quantitative content analysis. Included are tools for visual text exploration, content analysis, vocabulary analysis, dictionary-based analysis, and more that facilitate the quantitative analysis of terms and their semantic contexts.

Visualize your literature review

As an all-in-one literature review software, MAXQDA offers a variety of visual tools that are tailor-made for qualitative research and literature reviews. Create stunning visualizations to analyze your material. Of course, you can export your visualizations in various formats to enrich your literature review analysis report. Work with word clouds to explore the central themes of a text and key terms that are used, create charts to easily compare the occurrences of concepts and important keywords, or make use of the graphical representation possibilities of MAXMaps, which in particular permit the creation of concept maps. Thanks to the interactive connection between your visualizations with your MAXQDA data, you’ll never lose sight of the big picture.

Daten visualization with Literature Review Software MAXQDA

AI Assist: literature review software meets AI

AI Assist – your virtual research assistant – supports your literature review with various tools. AI Assist simplifies your work by automatically analyzing and summarizing elements of your research project and by generating suggestions for subcodes. No matter which AI tool you use – you can customize your results to suit your needs.

Free tutorials and guides on literature review

MAXQDA offers a variety of free learning resources for literature review, making it easy for both beginners and advanced users to learn how to use the software. From free video tutorials and webinars to step-by-step guides and sample projects, these resources provide a wealth of information to help you understand the features and functionality of MAXQDA for literature review. For beginners, the software’s user-friendly interface and comprehensive help center make it easy to get started with your data analysis, while advanced users will appreciate the detailed guides and tutorials that cover more complex features and techniques. Whether you’re just starting out or are an experienced researcher, MAXQDA’s free learning resources will help you get the most out of your literature review.

Free Tutorials for Literature Review Software MAXQDA

Free MAXQDA Trial for Windows and Mac

Get your maxqda license, compare the features of maxqda and maxqda analytics pro, faq: literature review software.

Literature review software is a tool designed to help researchers efficiently manage and analyze the existing body of literature relevant to their research topic. MAXQDA, a versatile qualitative data analysis tool, can be instrumental in this process.

Literature review software, like MAXQDA, typically includes features such as data import and organization, coding and categorization, advanced search capabilities, data visualization tools, and collaboration features. These features facilitate the systematic review and analysis of relevant literature.

Literature review software, including MAXQDA, can assist in qualitative data interpretation by enabling researchers to organize, code, and categorize relevant literature. This organized data can then be analyzed to identify trends, patterns, and themes, helping researchers draw meaningful insights from the literature they’ve reviewed.

Yes, literature review software like MAXQDA is suitable for researchers of all levels of experience. It offers user-friendly interfaces and extensive support resources, making it accessible to beginners while providing advanced features that cater to the needs of experienced researchers.

Getting started with literature review software, such as MAXQDA, typically involves downloading and installing the software, importing your relevant literature, and exploring the available features. Many software providers offer tutorials and documentation to help users get started quickly.

For students, MAXQDA can be an excellent literature review software choice. Its user-friendly interface, comprehensive feature set, and educational discounts make it a valuable tool for students conducting literature reviews as part of their academic research.

MAXQDA is available for both Windows and Mac users, making it a suitable choice for Mac users looking for literature review software. It offers a consistent and feature-rich experience on Mac operating systems.

When it comes to literature review software, MAXQDA is widely regarded as one of the best choices. Its robust feature set, user-friendly interface, and versatility make it a top pick for researchers conducting literature reviews.

Yes, literature reviews can be conducted without software. However, using literature review software like MAXQDA can significantly streamline and enhance the process by providing tools for efficient data management, analysis, and visualization.

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    The literature review, among other, has identified lack of standardization in terminology and concepts, lack of systematic domain modelling and use of ontologies mainly in prototype ontology systems that address rather limited aspects of software project management processes. Download Free PDF. RAJ TAPASE.

  5. Sample Literature Review of Software Project

    Sample Literature Review of Software Project - Free download as PDF File (.pdf), Text File (.txt) or read online for free. sample literature review of software project

  6. How To Write A Literature Review (+ Free Template)

    Okay - with the why out the way, let's move on to the how. As mentioned above, writing your literature review is a process, which I'll break down into three steps: Finding the most suitable literature. Understanding, distilling and organising the literature. Planning and writing up your literature review chapter.

  7. Software Development Analytics in Practice: A Systematic Literature Review

    Software development analytics is a research area concerned with providing insights to improve product deliveries and processes. Many types of studies, data sources and mining methods have been used for that purpose. This systematic literature review aims at providing an aggregate view of the relevant studies on Software Development Analytics in the past decade, with an emphasis on its ...

  8. Guidelines for performing Systematic Literature Reviews in Software

    The guidelines have been adapted to reflect the specific problems of software engineering research. The guidelines cover three phases of a systematic literature review: planning the review ...

  9. Literature Review Example (PDF + Template)

    The literature review opening/introduction section; The theoretical framework (or foundation of theory) The empirical research; The research gap; The closing section; We then progress to the sample literature review (from an A-grade Master's-level dissertation) to show how these concepts are applied in the literature review chapter. You can ...

  10. Best Practices for Software Development: A Systematic Literature Review

    Context: A Multivocal Literature Review (MLR) is a form of a Systematic Literature Review (SLR) which includes the grey literature (e.g., blog posts, videos and white papers) in addition to the ...

  11. PDF How to do a Structured Literature Review in computer science

    If a systematic literature review is conducted thoroughly it ful ls the advantages described above and thereby gains scienti c value. This documents attempts to give a short introduction to how to conduct a structured literature review within computer science. The examples used are taken from [3]. 2 Structure of a systematic literature review

  12. PDF Software Project Scheduling: A Systematic Literature Review

    The main sequences sequences is on. Software In this research m ls or scheduling (RQ2) of operations be performed. software come project question, scheduling software we have identified how many studies problem. of 41 By doing clearly defined studies [11-14] that software in.

  13. PDF Systematic Literature Review

    the project's life cycle is not better and more clearly understood. In addition, while the above papers are well established in the field, there is not yet a firm theoretical foundation for the topic. This study reports the findings of a systematic review of publications published primarily between 2006 and 2017 in front-end project literature.

  14. A Systematic Literature Review on Using Machine Learning Algorithms for

    1. Introduction. The RE activity is steered in the very first phase of software development lifecycle and plays a very pivotal role in ensuring the development of quality and secure software systems [1, 2].There are various activities (i.e., elicitation, specification, validation, and management) associated with it that need to be effectively performed to somehow guarantee developing a quality ...

  15. Preliminary Systematic Literature Review of Software and Systems

    In this paper, we report on the results of Systematic Literature Review (SLR) related to software and systems traceability. Our SLR is preliminary one because we only analyzed articles in ACM digital library and IEEE computer society digital library. We found several interesting trends in traceability research.

  16. How to make literature review for a software implementation project?

    I don't know if this is out of the scope of this website. I'm a student in software engineering deparment and I am supposed to make a project for a course during the semester. The first step of it is to prepare a project proposal which consists of a short description of the project, a literature review and detailed flowcharts.

  17. What is a Literature Review? How to Write It (with Examples)

    A literature review is a critical analysis and synthesis of existing research on a particular topic. It provides an overview of the current state of knowledge, identifies gaps, and highlights key findings in the literature. 1 The purpose of a literature review is to situate your own research within the context of existing scholarship ...

  18. 15 Literature Review Examples (2024)

    15 Literature Review Examples. Literature reviews are a necessary step in a research process and often required when writing your research proposal. They involve gathering, analyzing, and evaluating existing knowledge about a topic in order to find gaps in the literature where future studies will be needed. Ideally, once you have completed your ...

  19. Software Development Project Management: A Literature Review

    Abstract. The rapid and unprecedented growth in software has brought with it some of the most spectacular and costly project failures in modern history. How risk management is presented in the ...

  20. Engineering: The Literature Review Process

    The review could just be a few pages for narrow topics or quite extensive with long bibliographies for in-depth reviews. In-depth review articles are valuable time-savers for professionals and researchers who need a quick introduction or analysis of a topic but they can be very time-consuming for authors to produce. Examples of review articles:

  21. PDF A Literature Review on Project Management System

    1) Projects are to be completed within a specified time period. There are different types of project m. 2) used to handle projects .They are unique in operation, Projects have specific, measurable, achievable, and realistic objectives. depending on the kind of project one is managing. Mohamed, 3) Projects are completed within a specified budget.

  22. Literature Review Software MAXQDA

    All-in-one Literature Review Software. As your all-in-one literature review software, MAXQDA can be used to manage your entire research project. Easily import data from texts, interviews, focus groups, PDFs, web pages, spreadsheets, articles, e-books, and even social media data.

  23. 608 PDFs

    Software Quality Assurance (SQA) is a process that ensures that software products and processes meet the specified requirements and quality standards. The components of SQA typically include the ...