IIIT-Delhi Institutional Repository

MIMANSA : process mining software repositories from student projects in an undergraduate software engineering course

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dc.contributor.author Mittal, Megha
dc.contributor.author Sureka, Ashish (Advisor)
dc.date.accessioned 2014-01-24T04:21:36Z
dc.date.available 2014-01-24T04:21:36Z
dc.date.issued 2014-01-24T04:21:36Z
dc.identifier.uri https://repository.iiitd.edu.in/jspui/handle/123456789/115
dc.description.abstract An undergraduate level Software Engineering course generally consists of a team-based semester long project and emphasizes on both technical and managerial skills. Software Engineering is a practice-oriented and applied discipline and hence there is an emphasis on hands-on de- velopment, process, usage of tools in addition to theory and basic concepts. We present an approach for mining the process data (process mining) from software repositories archiving data generated as a result of constructing software by student teams in an educational setting. We present an application of mining three software repositories: team wiki (used during require- ment engineering), version control system (development and maintenance) and issue tracking system (corrective and adaptive maintenance) in the context of an undergraduate Software En- gineering course. We propose visualizations, metrics and algorithms to provide an insight into practices and procedures followed during various phases of a software development life-cycle. The proposed visualizations and metrics (learning analytics) provide a multi-faceted view to the instructor serving as a feedback tool on development process and quality by students. We mine the event logs produced by software repositories and derive insights such as degree of individual contributions in a team, quality of commit messages, intensity and consistency of commit activi- ties, bug xing process trend and quality, component and developer entropy, process compliance and veri cation. We present our empirical analysis on a software repository dataset consisting of 19 teams of 5 members each and discuss challenges, limitations and recommendations. en_US
dc.language.iso en_US en_US
dc.subject Mining Software Repositories en_US
dc.subject Process Mining en_US
dc.subject Education Data Mining en_US
dc.subject Learning Analytic en_US
dc.subject Software Engineering Education en_US
dc.title MIMANSA : process mining software repositories from student projects in an undergraduate software engineering course en_US
dc.type Thesis en_US

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