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20232026
most citedCopiloting the Copilots: Fusing Large Language Models with Completion Engines for Automated Program Repair

104 citations · 242 across the 12 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.SE2024★ 17 cited

Agentless: Demystifying LLM-based Software Engineering Agents

Chunqiu Steven Xia, Yinlin Deng, Soren Dunn +1

Recent advancements in large language models (LLMs) have significantly advanced the automation of software development tasks, including code synthesis, program repair, and test gen…

cs.SE2024★ 5 cited

TESTEVAL: Benchmarking Large Language Models for Test Case Generation

Wenhan Wang, Chenyuan Yang, Zhijie Wang +6

Testing plays a crucial role in the software development cycle, enabling the detection of bugs, vulnerabilities, and other undesirable behaviors. To perform software testing, teste…

cs.SE2024★ 6 cited

UniDebugger: Hierarchical Multi-Agent Framework for Unified Software Debugging

Cheryl Lee, Chunqiu Steven Xia, Longji Yang +4

Software debugging is a time-consuming endeavor involving a series of steps, such as fault localization and patch generation, each requiring thorough analysis and a deep understand…

cs.SE2024★ 4 cited

Top Leaderboard Ranking = Top Coding Proficiency, Always? EvoEval: Evolving Coding Benchmarks via LLM

Chunqiu Steven Xia, Yinlin Deng, Lingming Zhang

LLMs have become the go-to choice for code generation tasks, with an exponential increase in the training, development, and usage of LLMs specifically for code generation. To evalu…

cs.CR2024★ 37 cited

KernelGPT: Enhanced Kernel Fuzzing via Large Language Models

Chenyuan Yang, Zijie Zhao, Lingming Zhang

Bugs in operating system kernels can affect billions of devices and users all over the world. As a result, a large body of research has been focused on kernel fuzzing, i.e., automa…