Simultaneous debugging of software faults

doi:10.1016/j.jss.2010.11.915

Simultaneous debugging of software faults

2011-04-01

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Arjan J. C. van Gemund

DOI：10.1016/j.jss.2010.11.915

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(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. (C) 2010 Elsevier Inc. All rights reserved.

Keywords:

Software fault diagnosis

Program spectra

Statistical and reasoning approaches

Simultaneous debugging of software faults

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