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http://repository.iiitd.edu.in/xmlui/handle/123456789/115Full metadata record
| DC Field | Value | Language |
|---|---|---|
| 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 |
| Appears in Collections: | Year-2013 | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| IIIT-D-MTech-CS-DE-12-043.pdf | 851.77 kB | Adobe PDF | View/Open |
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