ArkEval: Benchmarking and Evaluating Automated Code Repair for ArkTS

IEEE/ACM International Conference on Automated Software Engineering (ASE) 2026 Open access

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Authors: Bang Xie, Senjian Zhang, Zhiyuan Peng, Wei J. Chen, Chenhao Ying, Chenhao Ying, Yuan Luo
DOI: 10.1145/3832783.3837514
Cited by: 0

Abstract

Automated program repair benchmarks largely cover mature languages such as Python and Java, leaving limited support for ArkTS and OpenHarmony. We present ArkEval, an executable repository-level benchmark for evaluating repair on real ArkTS/OpenHarmony issue-resolution tasks. To the best of our knowledge, it is the first benchmark with this scope.

Fields of Study & Subjects

Software Engineering Research Software Testing and Debugging Techniques Software System Performance and Reliability

Publication details

Journal / source
IEEE/ACM International Conference on Automated Software Engineering (ASE)
Pages
2767–2779
Publication date
7 October 2026
Language
EN