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Affiliation of Author(s):计算机科学与技术学院/人工智能学院/软件学院

Journal:IEEE ACCESS

Key Words:Fault localization absolute ranking testing debugging

Abstract:Spectrum-based fault localization (SFL) is a popular lightweight automatic software fault localization technique that uses coverage information of program execution to compute the likelihood of root cause of failure(s) for each program component and ranks them descending by their suspiciousness scores. However, some recent studies indicate an SFL technique to be useful only if the root cause(s) of failures is ranked at top k. Due to the nature of the SFL technique, it is impossible that the root fault(s) is always ranked at top k, which may interfere with the usefulness of SFL in practice. To solve this issue, an SFL technique via enlarging the non-fault region to further improve fault absolute ranking was proposed. The idea behind this is that we can intuitively improve fault absolute ranking for an SFL technique if some non-fault components ranked higher were excluded from the fault ranking list. In the approach, we enlarge the non-fault region iteratively to narrow down the suspicious region based on two scenarios, and then rank those components in the suspicious region using existing SFL techniques. The empirical results indicate that our approach significantly helps existing SFL techniques to further improve their usefulness.

ISSN No.:2169-3536

Translation or Not:no

Date of Publication:2018-01-01

Co-author:Wang, Yong,Huang ZhiQiu,Fang, Bingwu,ly

Correspondence Author:wyl,Huang ZhiQiu