Prevalence of Single-Fault Fixes and Its Impact on Fault Localization

Abstract

Several fault predictors were proposed in the context of Spectrum-based Fault Localization approaches to rank software components in order of suspiciousness of being the root-cause of observed failures. Previous work has also shown that some of the fault predictors (near-)optimally rank software components, provided that there is one fault in the system. Despite this, further work is being spent on creating more complex, computationally expensive, model-based techniques that can handle multiple-faulted scenarios accurately. However, our hypothesis is that when software is being developed, bugs arise one-at-a-time and therefore can be considered as single-faulted scenarios. We describe an approach to mine repositories, find bug-fixes, and catalog them according to the number of faults they fix, to assess the prevalence of single-fault fixes. Our empirical study using 279 open-source projects reveals that there is a prevalence of single-fault fixes, with over 82% of all fixes only eliminating one bug from the system, enabling the use of simpler, (near-)optimal, fault predictors. Moreover, we draw on the practical implications of our findings to influence and set direction for future research.