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Mining version histories to guide software changes
Abstract
We apply data mining to version histories in order to guide programmers along related changes: "Programmers who changed these functions also changed...." Given a set of existing changes, the mined association rules 1) suggest and predict likely further changes, 2) show up item coupling that is undetectable by program analysis, and 3) can prevent errors due to incomplete changes. After an initial change, our ROSE prototype can correctly predict further locations to be changed; the best predictive power is obtained for changes to existing software. In our evaluation based on the history of eight popular open source projects, ROSE's topmost three suggestions contained a correct location with a likelihood of more than 70 percent.
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Cited by
Predicting Faults from Cached History
Kim, S., Zimmermann, T., Whitehead Jr., E. J., & Zeller, A. (2007) · 29th International Conference on Software Engineering (ICSE'07) · doi:10.1109/icse.2007.66 · Cited by 486
Self-citationThe promises and perils of mining git
Bird, C., Rigby, P. C., Barr, E. T., Hamilton, D. J., German, D. M., & Devanbu, P. (2009) · 2009 6th IEEE International Working Conference on Mining Software Repositories · doi:10.1109/msr.2009.5069475 · Cited by 311
How Programmers Debug, Revisited: An Information Foraging Theory Perspective
Lawrance, J., Bogart, C., Burnett, M., Bellamy, R., Rector, K., & Fleming, S. D. (2013) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2010.111 · Cited by 142
A Survey of Machine Learning for Big Code and Naturalness
Allamanis, M., Barr, E. T., Devanbu, P., & Sutton, C. (2019) · ACM Computing Surveys · doi:10.1145/3212695 · Cited by 150
Using information scent to model the dynamic foraging behavior of programmers in maintenance tasks
Lawrance, J., Bellamy, R., Burnett, M., & Rector, K. (2008) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1357054.1357261 · Cited by 76
Metadata
- Authors
- Zimmermann, T., Zeller, A., Weissgerber, P., & Diehl, S.
- Venue
- IEEE Transactions on Software Engineering
- Published
- 2005-06
- Volume
- 31
- Issue
- 6
- Pages
- 429-445
- ISSN
- 0098-5589 (ISSN-L)
- 1939-3520
- 2326-3881
- OpenAlex
- W2141558501
- Cited by
- 856
- References
- 0
- FWCI
- 170.21
- Type
- journal article
- Language
- en
- Open access
- closed
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- Zimmermann, T., Zeller, A., Weissgerber, P., & Diehl, S. (2005). Mining version histories to guide software changes. IEEE Transactions on Software Engineering. https://doi.org/10.1109/tse.2005.72
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