Evaluating Partial Correctness of Programs in Automated Program Repair

Yusaku Ito; Hironori Washizaki; Kazunori Sakamoto; Yoshiaki Fukazawa

doi:10.1109/GCCE53005.2021.9621861

Evaluating Partial Correctness of Programs in Automated Program Repair

Yusaku Ito, Hironori Washizaki, Kazunori Sakamoto, Yoshiaki Fukazawa

School of Fundamental Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Genetic programming-based automated program repair is actively studied as a bug fixing method. The existing methods evaluates randomly generated solution candidates using the success rate of test suites. However, the candidates are sometimes evaluated inaccurately. This study proposes a method to more appropriately judge the correctness of program candidates. The proposed method verifies the correctness of the intermediate calculation process using statements to check the predicted conditions for internal variables. In an experiment involving the Defects4J dataset, the execution time was reduced in 15 of the 23 bugs.

Original language	English
Title of host publication	2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	742-743
Number of pages	2
ISBN (Electronic)	9781665436762
DOIs	https://doi.org/10.1109/GCCE53005.2021.9621861
Publication status	Published - 2021
Event	10th IEEE Global Conference on Consumer Electronics, GCCE 2021 - Kyoto, Japan Duration: 2021 Oct 12 → 2021 Oct 15

Publication series

Name	2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021

Conference

Conference	10th IEEE Global Conference on Consumer Electronics, GCCE 2021
Country/Territory	Japan
City	Kyoto
Period	21/10/12 → 21/10/15

Keywords

Genetic programming
Program repair
Software engineering
Testing

ASJC Scopus subject areas

Computer Science Applications
Signal Processing
Biomedical Engineering
Electrical and Electronic Engineering
Media Technology
Instrumentation

Access to Document

10.1109/GCCE53005.2021.9621861

Cite this

Ito, Y., Washizaki, H., Sakamoto, K., & Fukazawa, Y. (2021). Evaluating Partial Correctness of Programs in Automated Program Repair. In 2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021 (pp. 742-743). (2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GCCE53005.2021.9621861

Evaluating Partial Correctness of Programs in Automated Program Repair. / Ito, Yusaku; Washizaki, Hironori; Sakamoto, Kazunori et al.

2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 742-743 (2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ito, Y, Washizaki, H, Sakamoto, K & Fukazawa, Y 2021, Evaluating Partial Correctness of Programs in Automated Program Repair. in 2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021. 2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021, Institute of Electrical and Electronics Engineers Inc., pp. 742-743, 10th IEEE Global Conference on Consumer Electronics, GCCE 2021, Kyoto, Japan, 21/10/12. https://doi.org/10.1109/GCCE53005.2021.9621861

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abstract = "Genetic programming-based automated program repair is actively studied as a bug fixing method. The existing methods evaluates randomly generated solution candidates using the success rate of test suites. However, the candidates are sometimes evaluated inaccurately. This study proposes a method to more appropriately judge the correctness of program candidates. The proposed method verifies the correctness of the intermediate calculation process using statements to check the predicted conditions for internal variables. In an experiment involving the Defects4J dataset, the execution time was reduced in 15 of the 23 bugs.",

keywords = "Genetic programming, Program repair, Software engineering, Testing",

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series = "2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021",

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AB - Genetic programming-based automated program repair is actively studied as a bug fixing method. The existing methods evaluates randomly generated solution candidates using the success rate of test suites. However, the candidates are sometimes evaluated inaccurately. This study proposes a method to more appropriately judge the correctness of program candidates. The proposed method verifies the correctness of the intermediate calculation process using statements to check the predicted conditions for internal variables. In an experiment involving the Defects4J dataset, the execution time was reduced in 15 of the 23 bugs.

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Evaluating Partial Correctness of Programs in Automated Program Repair

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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