Evaluating Pre-trained Language Models for Repairing API Misuses

• URL: http://arxiv.org/abs/2310.16390v1
• Date: Wed, 25 Oct 2023 06:10:22 GMT
• Title: Evaluating Pre-trained Language Models for Repairing API Misuses
• Authors: Ting Zhang and Ivana Clairine Irsan and Ferdian Thung and David Lo and Asankhaya Sharma and Lingxiao Jiang
• Abstract summary: API misuses often lead to software bugs, crashes, and vulnerabilities. In a recent study, test-suite-based automatic program repair (APR) tools were found to be ineffective in repairing API misuses. We conduct a comprehensive empirical study on 11 learning-aided APR tools, which include 9 of the state-of-the-art general-purpose PLMs and two APR tools. Our results show that PLMs perform better than the studied APR tools in repairing API misuses.
• Score: 15.17607624946389
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: API misuses often lead to software bugs, crashes, and vulnerabilities. While several API misuse detectors have been proposed, there are no automatic repair tools specifically designed for this purpose. In a recent study, test-suite-based automatic program repair (APR) tools were found to be ineffective in repairing API misuses. Still, since the study focused on non-learning-aided APR tools, it remains unknown whether learning-aided APR tools are capable of fixing API misuses. In recent years, pre-trained language models (PLMs) have succeeded greatly in many natural language processing tasks. There is a rising interest in applying PLMs to APR. However, there has not been any study that investigates the effectiveness of PLMs in repairing API misuse. To fill this gap, we conduct a comprehensive empirical study on 11 learning-aided APR tools, which include 9 of the state-of-the-art general-purpose PLMs and two APR tools. We evaluate these models with an API-misuse repair dataset, consisting of two variants. Our results show that PLMs perform better than the studied APR tools in repairing API misuses. Among the 9 pre-trained models tested, CodeT5 is the best performer in the exact match. We also offer insights and potential exploration directions for future research.

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