# Assessing and Comparing Mutation-based Fault Localization Techniques

arXiv: https://arxiv.org/abs/1607.05512 · HTML: https://mlsanity.com/paper/1607.05512/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jul 2016.

## Built on by (most cited first, 1 of 1)

- [Large Language Models for Test-Free Fault Localization](https://mlsanity.com/paper/2310.01726/) (2023)

## Abstract (arXiv)

Recent research demonstrated that mutation-based fault localization techniques are relatively accurate and practical. However, these methods have never been compared and have only been assessed with simple hand-seeded faults. Therefore, their actual practicality is questionable when it comes to real-wold faults. To deal with this limitation we asses and compare the two main mutation-based fault localization methods, named Metallaxis and MUSE, on a set of real-world programs and faults. Our results based on three typical evaluation metrics indicate that mutation-based fault localization methods are relatively accurate and provide relevant information to developers. Overall, our result indicate that Metallaxis and MUSE require 18% and 37% of the program statements to find the sought faults. Additionally, both methods locate 50% and 80% of the studied faults when developers inspect 10 and 25 statements.