SOBER: Statistical model-based bug localization

Chao Liu, Xifeng Yan, Long Fei, Jiawei Han, Samuel P. Midkiff

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Automated localization of software bugs is one of the essential issues in debugging aids. Previous studies indicated that the evaluation history of program predicates may disclose important clues about underlying bugs. In this paper, we propose a new statistical model-based approach, called SOBER, which localizes software bugs without any prior knowledge of program semantics, Unlike existing statistical debugging approaches that select predicates correlated with program failures, SOBER models evaluation patterns of predicates in both correct and incorrect runs respectively and regards a predicate as bug-relevant if its evaluation pattern in incorrect runs differs significantly from that in correct ones, SOBER features a principled quantification of the pattern difference that measures the bug-relevance of program predicates, We systematically evaluated our approach under the same setting as previous studies. The result demonstrated the power of our approach in bug localization: SOBER can help programmers locate 68 out of 130 bugs in the Siemens suite when programmers are expected to examine no more than 10% of the code, whereas the best previously reported is 52 out of 130. Moreover, with the assistance of SOBER, we found two bugs in bc 1.06 (an arbitrary precision calculator on UNIX/Linux), one of which has never been reported before.

Original languageEnglish (US)
Title of host publicationESEC/FSE'05 - Proceedings of the Joint 10th European Software Engineering Conference (ESEC) and 13th ACM SIGSOFT Symposium on the Foundations of Software Engineering (FSE-13)
EditorsH. Gall
Pages286-295
Number of pages10
StatePublished - 2005
EventESEC/FSE'05 - Joint 10th European Software Engineering Conference (ESEC) and 13th ACM SIGSOFT Symposium on the Foundations of Software Engineering (FSE-13) - Lisbon, Portugal
Duration: Sep 5 2005Sep 9 2005

Publication series

NameESEC/FSE'05 - Proceedings of the Joint 10th European Software Engineering Conference (ESEC) and 13th ACM SIGSOFT Symposium on the Foundations of Software Engineering (FSE-13)

Other

OtherESEC/FSE'05 - Joint 10th European Software Engineering Conference (ESEC) and 13th ACM SIGSOFT Symposium on the Foundations of Software Engineering (FSE-13)
Country/TerritoryPortugal
CityLisbon
Period9/5/059/9/05

Keywords

  • Localization metrics
  • Statistical debugging

ASJC Scopus subject areas

  • General Engineering

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