The effectiveness of spectrum-based fault localization techniques primarily relies on the accuracy of their fault localization formulas. Theoretical studies prove the relative accuracy orders of selected formulas under certain assumptions,… Click to show full abstract
The effectiveness of spectrum-based fault localization techniques primarily relies on the accuracy of their fault localization formulas. Theoretical studies prove the relative accuracy orders of selected formulas under certain assumptions, forming a graph of their theoretical accuracy relations. However, it is unclear whether in such a graph the relative positions of these formulas may change when some assumptions are relaxed. On the other hand, empirical studies can measure the actual accuracy of any formula in controlled settings that more closely approximate practical scenarios but in less general contexts. In this paper, we propose an empirical framework of accuracy graphs and their construction that reveal the relative accuracy of formulas. Our work not only evaluates the association between certain assumptions and the theoretical relations among formulas, but also expands our knowledge to reveal new potential accuracy relationships of other formulas which have not been discovered by theoretical analysis. Using our proposed framework, we identified a list of formula pairs in which a formula is consistently statistically more accurate than or similar in accuracy to another, enlightening directions for further theoretical analysis.
               
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