Mining Version Histories to Guide Software Changes – ICSE 2004

by Thomas Zimmermann, Peter Weißgerber, Stephan Diehl, Andreas Zeller

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, such rules (a) suggest and predict likely further changes, (b) show up item coupling that is indetectable by program analysis, and (c) prevent errors due to incomplete changes. After an initial change, our ROSE prototype can correctly predict 26% of further files to be changed—and 15% of the precise functions or variables. The topmost three suggestions contain a correct location with a likelihood of 64%.

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See also: http://www.softevo.org/

Reference

Thomas Zimmermann, Peter Weißgerber, Stephan Diehl, Andreas Zeller. Mining Version Histories to Guide Software Changes. In Proceedings of the 26th International Conference on Software Engineering (ICSE 2004), Edinburgh, United Kingdom, May 2004, pp. 563-572.

BibTeX Entry

@inproceedings{zimmermann-icse-2004,
    title = "Mining Version Histories to Guide Software Changes",
    author = "Thomas Zimmermann and Peter Weißgerber and Stephan Diehl and Andreas Zeller",
    year = "2004",
    month = "May",
    booktitle = "Proceedings of the 26th International Conference on Software Engineering",
    location = "Edinburgh, United Kingdom",
    pages = "563--572",
    publisher = "IEEE Computer Society",
    ISBN = "0769521630",
}