{'fraction_non_alphanumeric': 0.014492753623188406, 'fraction_numerical': 0.0, 'mean_word_length': 5.426356589147287, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A Preliminary Investigation on the Performance of SBFL Techniques and Distance Metrics in Parallel Fault Localization

To locate multiple bugs in parallel, one common practice is to generate fault-focused clusters where failed test cases that are likely caused by the same bug are grouped together. With respect to the fault-focused clustering and fault localization, Spectrum-based fault localization (SBFL) technique and distance metric are two critical impact factors. This article proposes a method to evaluate the parallel fault localization performance of SBFL techniques and distance metrics where the fault-focused information for each failed test case is already given. Case studies are conducted using the proposed method to evaluate five SBFL techniques and five distance metrics on three programs with multiple bugs.