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Frontiers of Computer Science

Front. Comput. Sci.    2018, Vol. 12 Issue (6) : 1105-1124
Change profile analysis of open-source software systems to understand their evolutionary behavior
Munish SAINI(), Kuljit Kaur CHAHAL()
Department of Computer Science, Guru Nanak Dev University, Amritsar 143005, India
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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     
Corresponding Authors: Munish SAINI,Kuljit Kaur CHAHAL   
Just Accepted Date: 16 November 2016   Online First Date: 24 January 2018    Issue Date: 04 December 2018
 Cite this article:   
Munish SAINI,Kuljit Kaur CHAHAL. Change profile analysis of open-source software systems to understand their evolutionary behavior[J]. Front. Comput. Sci., 2018, 12(6): 1105-1124.
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Munish SAINI
Kuljit Kaur CHAHAL
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