Fault Localization Using Function Call Sequences

Fault localization techniques locate faults in a program. Many predicate based statistical fault localization techniques have been proposed in order to locate faults effectively and efficiently. Most of the faults exist in independent functions rather than independent predicates in a program and the majority of these faults will cause abnormal sequences of function calls. This paper proposes a novel function-level sequence matching fault localization technique called SMFL, which use abnormal start points of function call sequences between normal traces and faulty traces. Our approach runs a program to calculate the suspiciousness of each function, and gives a ranking list of all functions in descending order of the suspiciousness. The disparities of function call sequences in different versions of the same software program on a test case are very small and these disparities provide information about faulty functions. We use Siemens program as our subjects. The experimental results show that our approach can improve the effectiveness of fault localization.