TBAR: Revisiting template-based automated program repair

Kui Liu, Anil Koyuncu, Dongsun Kim, Tegawendé F. Bissyandé

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

227 Scopus citations

Abstract

We revisit the performance of template-based APR to build comprehensive knowledge about the effectiveness of fix patterns, and to highlight the importance of complementary steps such as fault localization or donor code retrieval. To that end, we first investigate the literature to collect, summarize and label recurrently-used fix patterns. Based on the investigation, we build TBar, a straightforward APR tool that systematically attempts to apply these fix patterns to program bugs. We thoroughly evaluate TBar on the De-fects4J benchmark. In particular, we assess the actual qualitative and quantitative diversity of fix patterns, as well as their effectiveness in yielding plausible or correct patches. Eventually, we find that, assuming a perfect fault localization, TBar correctly/plausibly fixes 74/101 bugs. Replicating a standard and practical pipeline of APR assessment, we demonstrate that TBar correctly fixes 43 bugs from Defects4J, an unprecedented performance in the literature (including all approaches, i.e., template-based, stochastic mutation-based or synthesis-based APR).

Original languageEnglish
Title of host publicationISSTA 2019 - Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis
EditorsDongmei Zhang, Anders Moller
PublisherAssociation for Computing Machinery, Inc
Pages43-54
Number of pages12
ISBN (Electronic)9781450362245
DOIs
StatePublished - 10 Jul 2019
Event28th ACM SIGSOFT International Symposium on Software Testing and Analysis, ISSTA 2019 - Beijing, China
Duration: 15 Jul 201919 Jul 2019

Publication series

NameISSTA 2019 - Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis

Conference

Conference28th ACM SIGSOFT International Symposium on Software Testing and Analysis, ISSTA 2019
Country/TerritoryChina
CityBeijing
Period15/07/1919/07/19

Keywords

  • Automated program repair
  • Empirical assessment
  • Fix pattern

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