RepairLLaMA:程序修复的有效表示和微调适配器

IF 5.6 1区 计算机科学 Q1 COMPUTER SCIENCE, SOFTWARE ENGINEERING
André Silva;Sen Fang;Martin Monperrus
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引用次数: 0

摘要

随着大型语言模型(llm)的出现,自动程序修复(APR)得到了显著的发展。用于程序修复的微调llm是最近的一项研究,有许多维度尚未被探索。现有的工作主要是微调llm与幼稚的代码表示,并没有扩展到前沿模型。为了解决这个问题,我们提出了RepairLLaMA,这是一种新颖的程序修复方法,1)通过微调模型识别APR的最佳代码表示,2)为程序修复开拓了最先进的参数高效微调技术(PEFT)。这导致RepairLLaMA产生了一个非常有效的“程序修复适配器”,用于修复AI的错误。我们的实验证明了这两个概念的有效性。首先,带有程序修复特定代码表示的微调适配器使模型能够使用有意义的修复信号并产生更好的补丁。其次,参数高效的微调有助于微调收敛,显然有助于RepairLLaMA修复微调数据分布之外的bug。总的来说,RepairLLaMA正确修复了144个缺陷4j v2、109个HumanEval-Java和20个gibug - java,优于所有基线。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RepairLLaMA: Efficient Representations and Fine-Tuned Adapters for Program Repair
Automated Program Repair (APR) has evolved significantly with the advent of Large Language Models (LLMs). Fine-tuning LLMs for program repair is a recent avenue of research, with many dimensions which have not been explored. Existing work mostly fine-tune LLMs with naive code representations and does not scale to frontier models. To address this problem, we propose RepairLLaMA, a novel program repair approach that 1) identifies optimal code representations for APR with fine-tuned models, and 2) pioneers state-of-the-art parameter-efficient fine-tuning technique (PEFT) for program repair. This results in RepairLLaMA producing a highly effective ‘program repair adapter’ for fixing bugs with AI. Our experiments demonstrate the validity of both concepts. First, fine-tuning adapters with program repair specific code representations enables the model to use meaningful repair signals and produce better patches. Second, parameter-efficient fine-tuning helps fine-tuning to converge and clearly contributes to the effectiveness of RepairLLaMA in fixing bugs outside the fine-tuning data distribution. Overall, RepairLLaMA correctly fixes 144 Defects4J v2, 109 HumanEval-Java, and 20 GitBug-Java bugs, outperforming all baselines.
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来源期刊
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering 工程技术-工程:电子与电气
CiteScore
9.70
自引率
10.80%
发文量
724
审稿时长
6 months
期刊介绍: IEEE Transactions on Software Engineering seeks contributions comprising well-defined theoretical results and empirical studies with potential impacts on software construction, analysis, or management. The scope of this Transactions extends from fundamental mechanisms to the development of principles and their application in specific environments. Specific topic areas include: a) Development and maintenance methods and models: Techniques and principles for specifying, designing, and implementing software systems, encompassing notations and process models. b) Assessment methods: Software tests, validation, reliability models, test and diagnosis procedures, software redundancy, design for error control, and measurements and evaluation of process and product aspects. c) Software project management: Productivity factors, cost models, schedule and organizational issues, and standards. d) Tools and environments: Specific tools, integrated tool environments, associated architectures, databases, and parallel and distributed processing issues. e) System issues: Hardware-software trade-offs. f) State-of-the-art surveys: Syntheses and comprehensive reviews of the historical development within specific areas of interest.
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