Reference : On the Efficiency of Test Suite based Program Repair: A Systematic Assessment of 16 A...
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
Security, Reliability and Trust
http://hdl.handle.net/10993/42854
On the Efficiency of Test Suite based Program Repair: A Systematic Assessment of 16 Automated Repair Systems for Java Programs
English
Liu, Kui mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Wang, Shangwen []
Koyuncu, Anil mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Kim, Kisub mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Bissyande, Tegawendé François D Assise mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Kim, Dongsun []
Wu, Peng []
Klein, Jacques mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Computer Science and Communications Research Unit (CSC) >]
Mao, Xiaoguang []
Le Traon, Yves mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Computer Science and Communications Research Unit (CSC) >]
May-2020
42nd ACM/IEEE International Conference on Software Engineering (ICSE)
Yes
International
42nd ACM/IEEE International Conference on Software Engineering
from 5-23-2020 to 5-29-2020
[en] Patch generation ; Program repair ; Efficiency ; Empirical assessment
[en] Test-based automated program repair has been a prolific field of research in software engineering in the last decade. Many approaches have indeed been proposed, which leverage test suites as a weak, but affordable, approximation to program specifications. Although the literature regularly sets new records on the number of benchmark bugs that can be fixed, several studies increasingly raise concerns about the limitations and biases of state-of-the-art approaches. For example, the correctness of generated patches has been questioned in a number of studies, while other researchers pointed out that evaluation schemes may be misleading with respect to the processing of fault localization results. Nevertheless, there is little work addressing the efficiency of patch generation, with regard to the practicality of program repair. In this paper, we fill this gap in the literature, by providing an extensive review on the efficiency of test suite based program repair. Our objective is to assess the number of generated patch candidates, since this information is correlated to (1) the strategy to traverse the search space efficiently in order to select sensical repair attempts, (2) the strategy to minimize the test effort for identifying a plausible patch, (3) as well as the strategy to prioritize the generation of a correct patch. To that end, we perform a large-scale empirical study on the efficiency, in terms of quantity of generated patch candidates of the 16 open-source repair tools for Java programs. The experiments are carefully conducted under the same fault localization configurations to limit biases. Eventually, among other findings, we note that: (1) many irrelevant patch candidates are generated by changing wrong code locations; (2) however, if the search space is carefully triaged, fault localization noise has little impact on patch generation efficiency; (3) yet, current template-based repair systems, which are known to be most effective in fixing a large number of bugs, are actually least efficient as they tend to generate majoritarily irrelevant patch candidates.
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/10993/42854
10.1145/3377811.3380338
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

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