Abstract
We present PyTER, an automated program repair (APR) technique for Python type errors. Python developers struggle with type error exceptions that are prevalent and difficult to fix. Despite the importance, however, automatically repairing type errors in dynamically typed languages such as Python has received little attention in the APR community and no existing techniques are readily available for practical use. PyTER is the first technique that is carefully designed to fix diverse type errors in real-world Python applications. To this end, we present a novel APR approach that uses dynamic and static analyses to infer correct and incorrect types of program variables, and leverage their difference to effectively identify faulty locations and patch candidates. We evaluated PyTER on 93 type errors collected from open-source projects. The result shows that PyTER is able to fix 48.4% of them with a precision of 77.6%.
| Original language | English |
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| Title of host publication | ESEC/FSE 2022 - Proceedings of the 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering |
| Editors | Abhik Roychoudhury, Cristian Cadar, Miryung Kim |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 922-934 |
| Number of pages | 13 |
| ISBN (Electronic) | 9781450394130 |
| DOIs | |
| Publication status | Published - 2022 Nov 7 |
| Event | 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2022 - Singapore, Singapore Duration: 2022 Nov 14 → 2022 Nov 18 |
Publication series
| Name | ESEC/FSE 2022 - Proceedings of the 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering |
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Conference
| Conference | 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2022 |
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| Country/Territory | Singapore |
| City | Singapore |
| Period | 22/11/14 → 22/11/18 |
Bibliographical note
Funding Information:This work was partly supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government(MSIT) (No.2020-0-01337,(SW STAR LAB) Research on Highly-Practical Automated Software Repair and No.2021-0-00758, Development of Automated Program Repair Technology by Combining Code Analysis and Mining) and the MSIT(Ministry of Science and ICT), Korea, under the ICT Creative Consilience program (IITP-2022-2020-0-01819) supervised by the IITP(Institute for Information & communications Technology Planning & Evaluation), and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No.2021R1A5A1021944).
Publisher Copyright:
© 2022 ACM.
Keywords
- Debugging
- Program Analysis
- Program Repair
ASJC Scopus subject areas
- Artificial Intelligence
- Software