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Automated Fault Localization with Statistically Suspicious Program States by Tai-Yi Huang; Pin-Chuan Chou; Cheng-Han Tsai; Hsin-An Chen is a Computer Science article available to read on EtoBox.

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A number of fault localization techniques have been developed to reduce the time in manually debugging a faulty program. The technique of code coverage [8] has been recognized by its effectiveness in identifying suspicious statements that may contain the fault. However, a programmer still needs to manually examine each variable referenced in a suspicious statement and such a process can become extremely time-consuming if this suspicious statement is part of a loop. In this paper, we propose a novel technique called state coverage to significantly reduce the time in examining variables. We first insert a set of checkpoints to record the state of each variable referenced in a branching statement. We next execute the faulty program by a test suite consisting of both passed and failed cases. A state is statistically considered to be more suspicious if it appears more in failed cases and less in passed cases. We implemented both code coverage and state coverage in a debugging tool and used a commonly-used benchmark consisting of 58 faulty programs to evaluate their performance. For 34% of these programs, their faults are within 20 statement steps of the most suspicious statement identif

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Author

Tai-Yi Huang; Pin-Chuan Chou; Cheng-Han Tsai; Hsin-An Chen

Publisher

ACM

Published

2007

Language

EN

Field

Computer Science (Physical Sciences)