Spectrum-based Software Fault Localization: A Survey of Techniques, Advances, and Challenges

Despite being one of the most basic tasks in software development, debugging is still performed in a mostly manual way, leading to high cost and low performance. To address this problem, researchers have studied promising approaches, such as Spectrum-based Fault Localization (SFL) techniques, which pinpoint program elements more likely to contain faults. This survey discusses the state-of-the-art of SFL techniques, including their costs, the type and number of faults they address, the programs they utilize in their validation, the testing information that support them, and their use at industrial settings. Notwithstanding the advances, there are still challenges for the industry to adopt these techniques, which we analyze in this paper. This includes using program analysis to generate reduced sets of suspicious entities; combining different spectra to fine-tune the fault localization ability; using strategies to collect fine-grained coverage levels from suspicious coarser levels for balancing execution costs and output precision; and proposing new techniques to cope with multiple-fault programs. Moreover, additional user studies are needed to better understand how SFL techniques can be used in practice. We conclude by presenting a concept map about topics and challenges for future research in SFL.