BUGSPHP: A dataset for Automated Program Repair in PHP

被引:0
|
作者
Pramod, K. D. [1 ]
De Silva, W. T. N. [1 ]
Thabrew, W. U. K. [1 ]
Shariffdeen, Ridwan [2 ]
Wickramanayake, Sandareka [1 ]
机构
[1] Univ Moratuwa, Moratuwa, Sri Lanka
[2] Natl Univ Singapore, Singapore, Singapore
来源
2024 IEEE/ACM 21ST INTERNATIONAL CONFERENCE ON MINING SOFTWARE REPOSITORIES, MSR | 2024年
关键词
Automated Program Repair; PHP Application Errors;
D O I
10.1145/3643991.3644878
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Automated Program Repair (APR) improves developer productivity by saving debugging and bug-fixing time. While APR has been extensively explored for C/C++ and Java programs, there is little research on bugs in PHP programs due to the lack of a benchmark PHP bug dataset. This is surprising given that PHP has been one of the most widely used server-side languages for over two decades, being used in a variety of contexts such as e-commerce, social networking, and content management. This paper presents a benchmark dataset of PHP bugs on real-world applications called BugsPHP, which can enable research on analysis, testing, and repair for PHP programs. The dataset consists of training and test datasets, separately curated from GitHub and processed locally. The training dataset includes more than 600,000 bug-fixing commits. The test dataset contains 513 manually validated bug-fixing commits equipped with developer-provided test cases to assess patch correctness.
引用
收藏
页码:128 / 132
页数:5
相关论文
共 50 条
  • [31] Should Fixing These Failures be Delegated to Automated Program Repair?
    Le, Xuan-Bach D.
    Le, Tien-Duy B.
    Lo, David
    2015 IEEE 26TH INTERNATIONAL SYMPOSIUM ON SOFTWARE RELIABILITY ENGINEERING (ISSRE), 2015, : 427 - 437
  • [32] Overfitting in Semantics-based Automated Program Repair
    Le, Xuan-Bach D.
    Thung, Ferdian
    Lo, David
    Le Goues, Claire
    PROCEEDINGS 2018 IEEE/ACM 40TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING (ICSE), 2018, : 163 - 163
  • [33] Reinforcement learning for mutation operator selection in automated program repair
    Hanna, Carol
    Blot, Aymeric
    Petke, Justyna
    AUTOMATED SOFTWARE ENGINEERING, 2025, 32 (02)
  • [34] TBar: Revisiting Template-Based Automated Program Repair
    Liu, Kui
    Koyuncu, Anil
    Kim, Dongsun
    Bissyande, Tegawende F.
    PROCEEDINGS OF THE 28TH ACM SIGSOFT INTERNATIONAL SYMPOSIUM ON SOFTWARE TESTING AND ANALYSIS (ISSTA '19), 2019, : 31 - 42
  • [35] An Empirical Study on the Usage of Fault Localization in Automated Program Repair
    Yang, Deheng
    Qi, Yuhua
    Mao, Xiaoguang
    2017 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE MAINTENANCE AND EVOLUTION (ICSME), 2017, : 504 - 508
  • [36] Evolving Paradigms in Automated Program Repair: Taxonomy, Challenges, and Opportunities
    Huang, Kai
    Xu, Zhengzi
    Yang, Su
    Sun, Honyu
    Li, Xuejun
    Yan, Zheng
    Zhang, Yuqing
    ACM COMPUTING SURVEYS, 2025, 57 (02)
  • [37] Extending the range of bugs that automated program repair can handle
    Al-Bataineh, Omar I.
    Moonen, Leon
    Vidziunas, Linas
    JOURNAL OF SYSTEMS AND SOFTWARE, 2024, 209
  • [38] Is the Cure Worse Than the Disease? Overfitting in Automated Program Repair
    Smith, Edward K.
    Barr, Earl T.
    Le Goues, Claire
    Brun, Yuriy
    2015 10TH JOINT MEETING OF THE EUROPEAN SOFTWARE ENGINEERING CONFERENCE AND THE ACM SIGSOFT SYMPOSIUM ON THE FOUNDATIONS OF SOFTWARE ENGINEERING (ESEC/FSE 2015) PROCEEDINGS, 2015, : 532 - 543
  • [39] Boosting Automated Program Repair with Bug-Inducing Commits
    Wen, Ming
    Liu, Yepang
    Cheung, Shing-Chi
    2020 IEEE/ACM 42ND INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING: NEW IDEAS AND EMERGING RESULTS (ICSE-NIER 2020), 2020, : 77 - 80
  • [40] Quality of Automated Program Repair on Real-World Defects
    Motwani, Manish
    Soto, Mauricio
    Brun, Yuriy
    Just, Rene
    Le Goues, Claire
    IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 2022, 48 (02) : 637 - 661