One Sentence Can Kill the Bug: Auto-Replay Mobile App Crashes From One-Sentence Overviews

IF 5.6 1区计算机科学 Q1 COMPUTER SCIENCE, SOFTWARE ENGINEERING

IEEE Transactions on Software Engineering Pub Date : 2025-02-03 DOI:10.1109/TSE.2025.3535938

Yuchao Huang;Junjie Wang;Zhe Liu;Mingyang Li;Song Wang;Chunyang Chen;Yuanzhe Hu;Qing Wang

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引用次数: 0

Abstract

Crash reports play a crucial role in software maintenance as they inform developers about the issues encountered in mobile applications. Developers must reproduce the reported crash before fixing it, which is extremely time-consuming and tedious. Existing studies have focused on automatic crash reproduction with step-by-step instructions. However, a non-neglectable portion of crash reports only provides a one-sentence overview, which merely describes the final crash-triggering action. These reports require developers to invest more effort in understanding and fixing the issues while existing techniques cannot handle them due to the lack of step-by-step guidance, thus calling for a greater need for automatic support. Leveraging the capability of Large Language Models (LLMs) in combining acting and reasoning, we propose ReActDroid, an automated approach to reproduce mobile application crashes directly from the crash overview. ReActDroid utilizes ReAct prompting to augment the app-specific knowledge and exploration history, enabling the LLM to derive the necessary steps for triggering the crash from a comprehensive and historical perspective. We evaluate ReActDroid on 102 crash reports from 69 popular Android apps and successfully reproduce 57.8% of the crashes, surpassing the performance of state-of-the-art baselines by 69% to 321%. Besides, the average reproducing time is 51.8 seconds, outperforming the baselines by 73% to 949%. We also evaluate the usefulness of ReActDroid with promising results.

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一句话就能解决问题：手机应用的自动重播程序会因为一句话概述而崩溃

崩溃报告在软件维护中起着至关重要的作用，因为它告诉开发人员在移动应用程序中遇到的问题。开发人员必须在修复之前重现报告的崩溃，这是非常耗时和繁琐的。现有的研究主要集中在逐步指导下的自动崩溃再现。然而，崩溃报告中不可忽视的一部分只提供了一句话的概述，它仅仅描述了最终触发崩溃的操作。这些报告要求开发人员投入更多的精力来理解和修复问题，而现有的技术由于缺乏分步指导而无法处理这些问题，因此需要更多的自动支持。利用大型语言模型（llm）结合行为和推理的能力，我们提出了ReActDroid，这是一种直接从崩溃概述中重现移动应用程序崩溃的自动化方法。ReActDroid利用ReAct提示来增强应用程序特定的知识和探索历史，使LLM能够从全面和历史的角度得出触发崩溃的必要步骤。我们根据来自69个流行Android应用的102份崩溃报告对ReActDroid进行了评估，成功重现了57.8%的崩溃，比最先进的基准性能高出69%至321%。此外，平均复制时间为51.8秒，比基线高73%到949%。我们还评估了ReActDroid的有用性，并得出了有希望的结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

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.