Leveraging Contextual Information from Function Call Chains to Improve Fault Localization

In Spectrum Based Fault Localization, program elements such as statements or functions are ranked according to a suspiciousness score which can guide the programmer in finding the fault more efficiently. However, such a ranking does not include any additional information about the suspicious code elements. In this work, we propose to complement function-level spectrum based fault localization with function call chains – i.e., snapshots of the call stack occurring during execution – on which the fault localization is first performed, and then narrowed down to functions. Our experiments using defects from Defects4J show that (i) 69% of the defective functions can be found in call chains with highest scores, (ii) in 4 out of 6 cases the proposed approach can improve Ochiai ranking of 1 to 9 positions on average, with a relative improvement of 19-48%, and (iii) the improvement is substantial (66-98%) when Ochiai produces bad rankings for the faulty functions.

Keywords: Spectrum Based Fault Localization, Function Call Chains, Call Stack Traces, Testing and Debugging.