Crex: Predicting patch correctness in automated repair of C programs through transfer learning of execution semantics

Yan, Dapeng; Liu, Kui; Niu, Yuqing; Li, Li; Liu, Zhe; Liu, Zhiming; KLEIN, Jacques; BISSYANDE, Tegawendé François D Assise

doi:10.1016/j.infsof.2022.107043

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Crex: Predicting patch correctness in automated repair of C programs through transfer learning of execution semantics

Yan, Dapeng; Liu, Kui; Niu, Yuqing et al.

2022 • In Information and Software Technology, 152, p. 1-12

Peer Reviewed verified by ORBi

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https://hdl.handle.net/10993/54302

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10.1016/j.infsof.2022.107043

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Disciplines :

Computer science

Author, co-author :

Yan, Dapeng; Nanjing University of Aeronautics and Astronautics

Liu, Kui; Huawei Software Engineering Application Technology Lab

Niu, Yuqing; Nanjing University of Aeronautics and Astronautics

Li, Li; Monash University

Liu, Zhe; Nanjing University of Aeronautics and Astronautics

Liu, Zhiming; Northwestern Polytechnical University

KLEIN, Jacques ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > TruX

BISSYANDE, Tegawendé François D Assise ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > TruX

External co-authors :

yes

Language :

English

Title :

Crex: Predicting patch correctness in automated repair of C programs through transfer learning of execution semantics

Publication date :

December 2022

Journal title :

Information and Software Technology

ISSN :

0950-5849

eISSN :

1873-6025

Publisher :

Elsevier, Amsterdam, Netherlands

Volume :

152

Pages :

1-12

Peer reviewed :

Peer Reviewed verified by ORBi

Focus Area :

Security, Reliability and Trust

Available on ORBilu :

since 31 January 2023

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Bibliography

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