Factorising the Multiple Fault Localization Problem: Adapting Single-Fault Localizer to Multi-fault Programs

Abstract

Software failures are not rare and fault localizations always an important but laborious activity. Since there is no guarantee that no more than one fault exists in a faulty program, the approach to locate all the faults is necessary. Spectrum-based fault localization techniques collect dynamic program spectra as well as test results of program runs, and estimate the extent of program elements being related to fault(s). A popular solution into generate a ranked list of suspicious candidates, which are checked in order, stopping whenever a fault is found. Such single fault localizers locate one fault in one checking round, terminate, and wait to be triggered by the regression testing to validate the fixing of the located fault. In this paper, we study the manifestation of multiple faults in a program and propose an effective mechanism to indicate their presence. When a fault is reached during the checking round, we use it to interpret the failures observed, and update the indicator to judge whether there remain other faults in the program. Our indicator serves as a stopping criterion of checking the ranked list of suspicious candidates. Our work factories the multiple fault localization problem into developing single-fault localizers and adapting them to multi-fault programs. It both improves the fault localization efficiencies of single-fault localizers, and avoids the ineffective efforts of thoroughly abandoning the many single-fault localizers to develop multi-fault localizers.