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Mining Edge-Weighted Call Graphs to Localise Software Bugs

  • Frank Eichinger
  • Klemens Böhm
  • Matthias Huber
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5211)

Abstract

An important problem in software engineering is the automated discovery of noncrashing occasional bugs. In this work we address this problem and show that mining of weighted call graphs of program executions is a promising technique. We mine weighted graphs with a combination of structural and numerical techniques. More specifically, we propose a novel reduction technique for call graphs which introduces edge weights. Then we present an analysis technique for such weighted call graphs based on graph mining and on traditional feature selection schemes. The technique generalises previous graph mining approaches as it allows for an analysis of weights. Our evaluation shows that our approach finds bugs which previous approaches cannot detect so far. Our technique also doubles the precision of finding bugs which existing techniques can already localise in principle.

Keywords

Edge Weight Program Execution Call Frequency Call Graph Graph Mining 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Frank Eichinger
    • 1
  • Klemens Böhm
    • 1
  • Matthias Huber
    • 1
  1. 1.Institute for Program Structures and Data Organisation (IPD)Universität Karlsruhe (TH)Germany

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