Reference : TBar: Revisiting Template-based Automated Program Repair
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
Computational Sciences
http://hdl.handle.net/10993/39778
TBar: Revisiting Template-based Automated Program Repair
English
Liu, Kui mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Koyuncu, Anil mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Kim, Dongsun []
Bissyande, Tegawendé François D Assise mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Jul-2019
28th ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA)
Yes
International
28th ACM SIGSOFT International Symposium on Software Testing and Analysis
from 15-07-2019 to 19-07-2019
[en] Automated program repair ; fix pattern ; empirical assessment
[en] We revisit the performance of template-based APR to build com-prehensive knowledge about the effectiveness of fix patterns, andto highlight the importance of complementary steps such as faultlocalization or donor code retrieval. To that end, we first investi-gate the literature to collect, summarize and label recurrently-usedfix patterns. Based on the investigation, we buildTBar, a straight-forward APR tool that systematically attempts to apply these fixpatterns to program bugs. We thoroughly evaluateTBaron the De-fects4J benchmark. In particular, we assess the actual qualitative andquantitative diversity of fix patterns, as well as their effectivenessin yielding plausible or correct patches. Eventually, we find that,assuming a perfect fault localization,TBarcorrectly/plausibly fixes74/101 bugs. Replicating a standard and practical pipeline of APRassessment, we demonstrate thatTBarcorrectly fixes 43 bugs fromDefects4J, an unprecedented performance in the literature (includ-ing all approaches, i.e., template-based, stochastic mutation-basedor synthesis-based APR).
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Security Design and Validation Research Group (SerVal)
Fonds National de la Recherche - FnR
Researchers ; Professionals ; Students ; General public
http://hdl.handle.net/10993/39778
FnR ; FNR10449467 > Tegawendé François D'Assise Bissyandé > RECOMMEND > Automatic Bug Fix Recommendation: Improving Software Repair and Reducing Time-to-Fix Delays in Software Development Projects > 01/02/2016 > 31/01/2019 > 2015

File(s) associated to this reference

Fulltext file(s):

FileCommentaryVersionSizeAccess
Open access
TBar.pdfAuthor preprint1.34 MBView/Open

Bookmark and Share SFX Query

All documents in ORBilu are protected by a user license.