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Frontiers of Computer Science

, Volume 12, Issue 6, pp 1105–1124 | Cite as

Change profile analysis of open-source software systems to understand their evolutionary behavior

  • Munish SainiEmail author
  • Kuljit Kaur Chahal
Research Article

Abstract

Source code management systems (such as git) record changes to code repositories of Open-Source Software (OSS) projects. The metadata about a change includes a change message to record the intention of the change. Classification of changes, based on change messages, into different change types has been explored in the past to understand the evolution of software systems from the perspective of change size and change density only. However, software evolution analysis based on change classification with a focus on change evolution patterns is still an open research problem. This study examines change messages of 106 OSS projects, as recorded in the git repository, to explore their evolutionary patterns with respect to the types of changes performed over time. An automated keyword-based classifier technique is applied to the change messages to categorize the changes into various types (corrective, adaptive, perfective, preventive, and enhancement). Cluster analysis helps to uncover distinct change patterns that each change type follows. We identify three categories of 106 projects for each change type: high activity, moderate activity, and low activity. Evolutionary behavior is different for projects of different categories. The projects with high and moderate activity receive maximum changes during 76–81 months of the project lifetime. The project attributes such as the number of committers, number of files changed, and total number of commits seem to contribute the most to the change activity of the projects. The statistical findings show that the change activity of a project is related to the number of contributors, amount of work done, and total commits of the projects irrespective of the change type. Further, we explored languages and domains of projects to correlate change types with domains and languages of the projects. The statistical analysis indicates that there is no significant and strong relation of change types with domains and languages of the 106 projects.

Keywords

software evolution open-source software (OSS) cluster analysis change classification 

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Notes

Acknowledgements

This research work was performed under a UGC sanctioned research project. We acknowledge the UGC for providing the grant to perform the research work.

Supplementary material

11704_2016_6301_MOESM1_ESM.ppt (269 kb)
Supplementary material, approximately 269 KB.

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Copyright information

© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceGuru Nanak Dev UniversityAmritsarIndia

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