Poster: A Novel Variable-centric Fault Localization Technique

Fault localization is one of the most important debugging tasks. Therefore, many techniques have already been developed to improve the efficiency. Among them, the spectrum-based fault localization technique is the most popular, and it has been the subject of 35% of total fault localization-related studies. SFL techniques leverage coverage spectra and localize a fault based on the coverage difference between passed and failed test cases. However, it is difficult to localize faults effectively when coverage differences are not clear. Therefore, we propose a novel variable-centric fault localization technique to improve performance of existing techniques. Proposed technique extracts suspicious variables and uses them to generate a suspicious ranked list. In an evaluation with 120 C faults, the proposed technique outperforms SFL techniques with the same similarity coefficient. The average exam scores of proposed techniques are reduced by 55% compared to SFL techniques.