On the Prediction of Software Merge Conflicts: A Systematic Review and Meta-analysis


Context: Predicting software merge conflicts plays a chief role in many software engineering tasks. Prediction techniques can be used to identify and anticipate potential conflicts between source code snippets that may arise when merging changes made by multiple developers. Problem: When multiple developers are working on the same source code, they may make changes to the same code snippets, which can cause conflicts when the changes are brought together. The problem is that typically these conflicts are difficult and time-consuming to resolve, and can potentially cause serious problems if not addressed properly. Solution: Predicting when conflicts will help in prioritizing or better managing the changes to be made in the code, in order to mitigate the emergence of conflicts. In this sense, developers can use tools that exam source codes to pinpoint potential snippets where conflicts are likely to occur. Theory of IS: This work was conceived under the aegis of the General Theory of Systems, in particular with regard to the interfaces between the parts of a system within its borders. In this case, the parts are themselves independent systems, called constituents, which include some information systems (IS). Method: This article focus on providing a systematic review and meta-analysis of published studies on the prediction of software conflicts. For this, we follow the PRISMA method. Contributions and Impact in the IS area: Development of a database knowledge of the historical context over predicting conflicts that will help in the development of future work and other research.
Palavras-chave: Literature Review, Merge Conflicts, Prediction, Virtual Teams, Software Merge


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GRAEFF, César Augusto; FARIAS, Kleinner; CARBONERA, Carlos Eduardo. On the Prediction of Software Merge Conflicts: A Systematic Review and Meta-analysis. In: SIMPÓSIO BRASILEIRO DE SISTEMAS DE INFORMAÇÃO (SBSI), 19. , 2023, Maceió/AL. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 .

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