Representativeness Analysis of Injected Software Faults in Complex Software

Despite of the existence of several techniques for emulating software faults, there are still open issues regarding representativeness of the faults being injected. An important aspect, not considered by existing techniques, is the non-trivial activation condition (trigger) of real faults, which causes them to elude testing and remain hidden until operation. In this paper, we investigate how the representativeness of injected software faults can be improved regarding the representativeness of triggers, by proposing a set of generic criteria to select representative faults from afaultload. We used the G-SWFIT technique to inject software faults in a DBMS, resulting in over 40 thousands faults and 2 million runs of a real test suite. We analyzed faults with respect to their triggers, and concluded that a non-negligible share (15%) would not realistically elude testing. Our proposed criteria decreased the percentage of non-elusive faults in the faultload, improving its representativeness.