Metallaxis‐FL: mutation‐based fault localization

TLDR

Fault localization methods identify faulty program statements from failing and passing test executions, with spectrum‑based techniques assigning suspiciousness scores to statements based on their likelihood of being faulty. The study introduces Metallaxis, a mutation‑based fault localization technique. Metallaxis links mutants to faulty program locations, using mutants killed primarily by failing tests as indicators of fault position. Experiments show Metallaxis outperforms statement‑based methods, remains effective with mutant sampling, benefits from mutation testing, improves localization over block/branch suites, and scales well. © 2013 John Wiley & Sons, Ltd.

Abstract

Summary Fault localization methods seek to identify faulty program statements based on the information provided by the failing and passing test executions. Spectrum‐based methods are among the most popular ones and assist programmers by assigning suspiciousness values on program statements according to their probability of being faulty. This paper proposes Metallaxis, a fault localization approach based on mutation analysis. The innovative part of Metallaxis is that it uses mutants and links them with the faulty program places. Thus, mutants that are killed mostly by failing tests provide a good indication about the location of a fault. Experimentation using Metallaxis suggests that it is significantly more effective than statement‐based approaches. This is true even in the case where mutation cost‐reduction techniques, such as mutant sampling, are facilitated. Additionally, results from a controlled experiment show that the use of mutation as a testing technique provides benefits to the fault localization process. Therefore, fault localization is significantly improved by using mutation‐based tests instead of block‐based or branch‐based test suites. Finally, evidence in support of the methods’ scalability is also given. Copyright © 2013 John Wiley & Sons, Ltd.