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iFixR : Bug Report driven Program Repair

Koyuncu, Anil (författare)
Univ Luxembourg, Luxembourg, Luxembourg.
Liu, Kui (författare)
Univ Luxembourg, Luxembourg, Luxembourg.
Bissyande, Tegawende F. (författare)
Univ Luxembourg, Luxembourg, Luxembourg.
visa fler...
Kim, Dongsun (författare)
Univ Luxembourg, Luxembourg, Luxembourg.;Furiosa Ai, Seoul, South Korea.
Monperrus, Martin (författare)
KTH,Teoretisk datalogi, TCS
Klein, Jacques (författare)
Univ Luxembourg, Luxembourg, Luxembourg.
Le Traon, Yves (författare)
Univ Luxembourg, Luxembourg, Luxembourg.
visa färre...
Univ Luxembourg, Luxembourg, Luxembourg Univ Luxembourg, Luxembourg, Luxembourg.;Furiosa Ai, Seoul, South Korea. (creator_code:org_t)
2019-08-12
2019
Engelska.
Ingår i: ESEC/FSE'2019. - New York, NY, USA : ASSOC COMPUTING MACHINERY. ; , s. 314-325
  • Konferensbidrag (refereegranskat)
Abstract Ämnesord
Stäng  
  • Issue tracking systems are commonly used in modern software development for collecting feedback from users and developers. An ultimate automation target of software maintenance is then the systematization of patch generation for user-reported bugs. Although this ambition is aligned with the momentum of automated program repair, the literature has, so far, mostly focused on generate-and-validate setups where fault localization and patch generation are driven by a well-defined test suite. On the one hand, however, the common (yet strong) assumption on the existence of relevant test cases does not hold in practice for most development settings: many bugs are reported without the available test suite being able to reveal them. On the other hand, for many projects, the number of bug reports generally outstrips the resources available to triage them. Towards increasing the adoption of patch generation tools by practitioners, we investigate a new repair pipeline, iFixR, driven by bug reports: (1) bug reports are fed to an IR-based fault localizer; (2) patches are generated from fix patterns and validated via regression testing; (3) a prioritized list of generated patches is proposed to developers. We evaluate iFixR on the Defects4J dataset, which we enriched (i.e., faults are linked to bug reports) and carefully-reorganized (i.e., the timeline of test-cases is naturally split). iFixR generates genuine/plausible patches for 21/44 Defects4J faults with its IR-based fault localizer. iFixR accurately places a genuine/plausible patch among its top-5 recommendation for 8/13 of these faults (without using future test cases in generation-and-validation).

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)

Nyckelord

Information retrieval
fault localization
automatic patch generation

Publikations- och innehållstyp

ref (ämneskategori)
kon (ämneskategori)

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