Journal article
Studying the evolution of software systems using change clusters
Drexel University. College of Engineering. Department of Computer Science. Faculty Research and Publications (Comp Sci)
09 Jul 2007
Abstract
In this paper, we present an approach that examines the evolution of code stored in source control repositories. The technique identifies Change Clusters which can help managers to classify different code change activities as software maintenance or new development. Furthermore, identifying the variations in Change Clusters over time exposes trends in the development of a software system. We present a case study, which uses a sequence of Change Clusters to track the evolution of the PostgreSQL software project. Our case study demonstrates that our technique reveals interesting patterns about the progress of code development within each release of PostgreSQL. We show that the increase in the number of clusters not only identifies the areas where development has occurred, but reflects the magnitude of change in code. We also compare how the Change Clusters vary over time in order to make generalizations about the focus of development.
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Details
- Title
- Studying the evolution of software systems using change clusters
- Creators
- Jay Kothari (Author) - Drexel University (1970-)Trip Denton (Author) - Drexel University (1970-)Ali Shokoufandeh 1965- (Author) - Drexel University (1970-)Spiros Mancoridis (Author) - Drexel University (1970-)Ahmed E. Hassan (Author) - Drexel University (1970-)
- Publication Details
- Drexel University. College of Engineering. Department of Computer Science. Faculty Research and Publications (Comp Sci)
- Publisher
- The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Computer Science [Historical]; Computer Science (Computing); College of Engineering; Drexel University (1970-)
- Web of Science ID
- WOS:000239773400005
- Scopus ID
- 2-s2.0-33845460255
- Other Identifier
- 991014632229504721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- International collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Software Engineering
- Computer Science, Theory & Methods