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Mining Version Histories to Guide Software Changes
Thomas Zimmermann · Peter Weißgerber · Stephan Diehl · Andreas Zeller

 Lehrstuhl für Softwaretechnik (Prof. Zeller)
Universität des Saarlandes – Informatik
Informatik Campus des Saarlandes
Campus E9 1 (CISPA)
66123 Saarbrücken
E-mail: zeller @ cs.uni-saarland.de
Telefon: +49 681 302-70970

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   Thomas Zimmermann, Peter Weißgerber, Stephan Diehl, and Andreas Zeller. Mining Version Histories to Guide Software Changes. Saarland University, September 2003. Proc. 26th International Conference on Software Engineering (ICSE), Edinburgh, UK, May 2004.
"After the programmer has made some changes to the ECLIPSE source, ROSE suggests locations where, in similar transactions in the past, further changes were made." (Introduction)

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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, such rules
  • suggest and predict likely further changes,
  • show up item coupling that is indetectable by program analysis, and
  • 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%.

Contents

  1. Introduction
  2. Processing Change Data
  3. Grouping Changes to Transactions
  4. From Transactions to Rules
    • Applying Rules
    • Computing Rules
  5. Some Rule Examples
  6. Evaluation
    • Evaluation Setup
    • Precision vs. Recall
    • Likelihood
    • Results: Navigation through Source Code
    • Results: Error Prevention
    • Results: Closure
    • Results: Granularity
    • Threats to Validity
  7. Related Work
  8. Conclusion and Consequences
  9. References

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<webmaster@st.cs.uni-saarland.de> · http://www.st.cs.uni-saarland.de/papers/icse2004/?lang=de · Stand: 2018-04-05 13:41