1 citations · 1 across the 3 of their papers we have counts for
4 papers · 1 filter
OdinEval: A Reproducible Benchmark for LLM-Based Program Repair in the Odin Programming Language
Bang Xie, Hao Liu, Zhiyuan Peng +8
Repository-level repair benchmarks still center on a few mainstream languages, leaving systems languages such as Odin largely untested. We present OdinEval, a reproducible benchmar…
AppEval: A Unified Benchmark for LLM-Based Mobile Application Repair in ArkTS, Swift, and Kotlin
Bang Xie, Hao Liu, Zhenyu Shi +11
Repository-level LLM agents are typically evaluated on projects whose tests run on the build host. It remains unclear whether their repairs survive the mobile build-install-launch-…
ArkEval: Benchmarking and Evaluating Automated CodeRepair for ArkTS
Bang Xie, Senjian Zhang, Zhiyuan Peng +3
Large language models have transformed code generation, enabling unprecedented automation in software development. As mobile ecosystems evolve, HarmonyOS has emerged as a critical…
SolAgent: A Specialized Multi-Agent Framework for Solidity Code Generation
Wei Chen, Zhiyuan Peng, Xin Yin +4
Smart contracts are the backbone of the decentralized web, yet ensuring their functional correctness and security remains a critical challenge. While Large Language Models (LLMs) h…