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P2 Effectiveness and challenges in generating concurrent tests for thread-safe classes

面向线程安全类的并发测试生成:有效性与挑战
ASE Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering2018匹配度 2/10 · 该论文聚焦线程安全类的并发测试自动生成与工具实证评估,属于软件测试/并发领域;但未涉及静态分析、LLM/Agent、浮点程序分析或贝叶斯程序分析等用户核心方向,因此匹配度较低。引用 20 inbox
Valerio Terragni, Mauro Pezzè
crossref: 2026-09-12

AI 速览

一句话:对自动生成线程安全类并发测试的现有工具进行独立实证评估,发现仅17%的并发故障被检出。

开发正确高效的并发程序十分困难,线程安全类封装了大部分同步复杂性,因此测试其并发行为对程序可靠性至关重要。近年来,研究者提出多种自动生成并发测试的技术与工具。本文系统梳理了现有技术,并对公开可用工具进行独立实证评估:在包含47个有文档记录的并发故障的JaConTeBe基准上运行所有工具。结果显示,仅8个故障(17%)被至少一个工具检出。作者进一步分析工具局限与所生成测试的问题,总结出改进自动化并发测试生成有效性的研究启示。

问题
线程安全类的并发测试至关重要,但自动生成有效并发测试仍面临困难;本文关注现有技术与工具能否实际检出真实并发故障。
方法
系统综述现有自动并发测试生成技术,并在JaConTeBe基准上统一运行所有公开工具,分析工具与生成测试的不足。
评估
在含47个并发故障的JaConTeBe基准上评估,仅8个(17%)故障被至少一个工具检出,并据此提炼未来研究启示。
原文摘要(Abstract)

Developing correct and efficient concurrent programs is difficult and error-prone, due to the complexity of thread synchronization. Often, developers alleviate such problem by relying on thread-safe classes, which encapsulate most synchronization-related challenges. Thus, testing such classes is crucial to ensure the reliability of the concurrency aspects of programs. Some recent techniques and corresponding tools tackle the problem of testing thread-safe classes by automatically generating concurrent tests. In this paper, we present a comprehensive study of the state-of-the-art techniques and an independent empirical evaluation of the publicly available tools. We conducted the study by executing all tools on the JaConTeBe benchmark that contains 47 well-documented concurrency faults. Our results show that 8 out of 47 faults (17%) were detected by at least one tool. By studying the issues of the tools and the generated tests, we derive insights to guide future research on improving the effectiveness of automated concurrent test generation.

链接与引用

DOI 原文 ·

BibTeX
@inproceedings{paperbot4756,
  title = {Effectiveness and challenges in generating concurrent tests for thread-safe classes},
  author = {Valerio Terragni and Mauro Pezzè},
  booktitle = {ASE},
  year = {2018},
  doi = {10.1145/3238147.3238224}
}