2024
Authors
Santos, S; Saraiva, J; Ribeiro, F;
Publication
2024 ACM/IEEE INTERNATIONAL WORKSHOP ON AUTOMATED PROGRAM REPAIR, APR 2024
Abstract
This paper introduces a new method of Automated Program Repair that relies on a combination of the GPT-4 Large Language Model and automatic type checking of Haskell programs. This method identifies the source of a type error and asks GPT-4 to fix that specific portion of the program. Then, QuickCheck is used to automatically generate a large set of test cases to validate whether the generated repair behaves as the correct solution. Our publicly available experiments revealed a success rate of 88.5% in normal conditions. However, more detailed testing should be performed to more accurately evaluate this form of APR.
2024
Authors
Cunha, S; Silva, L; Saraiva, J; Fernandes, JP;
Publication
Proceedings of the 17th ACM SIGPLAN International Conference on Software Language Engineering
Abstract
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