Titre :

Automatic Repair of Real Bugs in Java: A Large-Scale Experiment on the Defects4J Dataset

Auteur(s) :

Martinez, Matias [Auteur]
Université de Valenciennes et du Hainaut-Cambrésis [UVHC]
Durieux, Thomas [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Sommerard, Romain [Auteur]
Université de Lille, Sciences et Technologies
Xuan, Jifeng [Auteur]
Wuhan University [China]
Monperrus, Martin [Auteur]
Université de Lille, Sciences et Technologies
Self-adaptation for distributed services and large software systems [SPIRALS]

Titre de la manifestation scientifique :

ESEC/FSE 2017 - 11th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering

Ville :

Paderborn

Pays :

Allemagne

Date de début de la manifestation scientifique :

2017-09-04

Date de publication :

2017

Mot(s)-clé(s) en anglais :

Software repair
Bugs
Defects
Patches
Fixes

Discipline(s) HAL :

Informatique [cs]/Génie logiciel [cs.SE]

Résumé en anglais : [en]

Defects4J is a large, peer-reviewed, structured dataset of real-world Java bugs. Each bug in Defects4J comes with a test suite and at least one failing test case that triggers the bug. In this paper, we report on an ...
Lire la suite >Defects4J is a large, peer-reviewed, structured dataset of real-world Java bugs. Each bug in Defects4J comes with a test suite and at least one failing test case that triggers the bug. In this paper, we report on an experiment to explore the effectiveness of automatic test-suite based repair on Defects4J. The result of our experiment shows that the considered state-of-the-art repair methods can generate patches for 47 out of 224 bugs. However, those patches are only test-suite adequate, which means that they pass the test suite and may potentially be incorrect beyond the test-suite satisfaction correctness criterion. We have manually analyzed 84 different patches to assess their real correctness. In total, 9 real Java bugs can be correctly repaired with test-suite based repair. This analysis shows that test-suite based repair suffers from under-specified bugs, for which trivial or incorrect patches still pass the test suite. With respect to practical applicability, it takes on average 14.8 minutes to find a patch. The experiment was done on a scientific grid, totaling 17.6 days of computation time. All the repair systems and experimental results are publicly available on Github in order to facilitate future research on automatic repair.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Commentaire :

update for oadoi on Nov 02 2018

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL