1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.SE2026
Coding in a Bubble? Evaluating LLMs in Resolving Context Adaptation Bugs During Code Adaptation
Tanghaoran Zhang, Xinjun Mao, Shangwen Wang +8
Code adaptation is a fundamental but challenging task in software development, requiring developers to modify existing code for new contexts. A key challenge is to resolve Context…
cs.SE2026
AdaptEval: A Benchmark for Evaluating Large Language Models on Code Snippet Adaptation
Tanghaoran Zhang, Xinjun Mao, Shangwen Wang +6
Recent advancements in large language models (LLMs) have automated various software engineering tasks, with benchmarks emerging to evaluate their capabilities. However, for adaptat…
cs.SE2024★ 1 cited
Instruct or Interact? Exploring and Eliciting LLMs' Capability in Code Snippet Adaptation Through Prompt Engineering
Tanghaoran Zhang, Yue Yu, Xinjun Mao +5
Code snippet adaptation is a fundamental activity in the software development process. Unlike code generation, code snippet adaptation is not a "free creation", which requires deve…