A Strategy to Determine When to Stop Using Automatic Bug Localization

Zhendong Shi, Wai Jacky Keung, Kwabena Ebo Bennin, Nachai Limsettho, Qinbao Song

Research output: Conference PapersRGC 32 - Refereed conference paper (without host publication)peer-review

2 Citations (Scopus)

Abstract

Information retrieval based automatic bug localization techniques provide developers a ranked list of suspicious buggy source entities to aid locate the ones needed to be modified and to fix the bug. However, it is unavoidable that some buggy entities are ranked low in the result list using these automatic techniques. We assume a bug localization process to address this challenge. Each time a source code entity in the ranked list is examined; the developers will have the option as to whether to continue examining the automatic bug localization result, or simply switch to using a conventional localization approach. We propose a new evaluation metric called ETC (Expected Time Cost) in the localization process, which includes the time cost of using the conventional approach. Under our assumptions, we derived simple criteria to minimize ETC. We compared the time cost of a state-of-art automatic localization method, BugLocator, with and without using our strategy in two projects. The result shows that using our proposed strategy combining both automatic localization technique together with conventional approach performs better than using only either the automatic localization technique or the conventional approach.

Conference

ConferenceCOMPSAC 2016: The 40th IEEE Computer Society International Conference on Computers, Software & Applications
Country/TerritoryUnited States
CityAtlanta
Period10/06/1614/06/16
Internet address

Research Keywords

  • bug localization
  • information retrieval
  • bug reports
  • fault localization
  • feature location
  • evaluation metric

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