Simultaneous debugging of software faults

  • Authors:

  • Rui Abreu;Peter Zoeteweij;Arjan J. C. van Gemund

  • Affiliations:

  • Department of Informatics Engineering, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias s/n, 4200-465 Porto, Portugal;IntelliMagic B.V., The Netherlands;Embedded Software Department, Faculty of Electronics, Math, and CS, Delft University of Technology, The Netherlands

  • Venue:
  • Journal of Systems and Software
  • Year:
  • 2011

  • OCE: an online colaborative editor

    ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part II

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Abstract

(Semi-)automated diagnosis of software faults can drastically increase debugging efficiency, improving reliability and time-to-market. Current automatic diagnosis techniques are predominantly of a statistical nature and, despite typical defect densities, do not explicitly consider multiple faults, as also demonstrated by the popularity of the single-fault benchmark set of programs. We present a reasoning approach, called Zoltar-M(ultiple fault), that yields multiple-fault diagnoses, ranked in order of their probability. Although application of Zoltar-M to programs with many faults requires heuristics (trading-off completeness) to reduce the inherent computational complexity, theory as well as experiments on synthetic program models and multiple-fault program versions available from the software infrastructure repository (SIR) show that for multiple-fault programs this approach can outperform statistical techniques, notably spectrum-based fault localization (SFL). As a side-effect of this research, we present a new SFL variant, called Zoltar-S(ingle fault), that is optimal for single-fault programs, outperforming all other variants known to date.