一句话：通过实证评估揭示评估设置不一致对智能合约漏洞检测测试工具结论的影响，并探讨最佳选择。
本文关注智能合约安全漏洞检测中的测试工具评估问题。近年来，大量研究致力于开发面向智能合约漏洞检测的测试工具，但已发表工具通常只在各自设计的实验场景中验证有效性。数据集、性能指标等评估设置的不一致，可能导致对工具有效性的结论产生偏差，也使得不同工具之间难以进行公平、可靠的横向比较。为此，论文围绕智能合约测试开展实证评估，旨在系统考察相关测试工具在漏洞检测任务中的表现，分析不同评估选择如何影响结论，并回答在智能合约测试中“最佳选择”是什么这一问题。该工作强调一致、可复现的评估基准对智能合约测试研究的重要性，为后续工具开发、比较与选用提供参考依据。
Security of smart contracts has attracted increasing attention in recent years. Many researchers have devoted themselves to devising testing tools for vulnerability detection. Each published tool has demonstrated its effectiveness through a series of evaluations on their own experimental scenarios. However, the inconsistency of evaluation settings such as different data sets or performance metrics, may result in biased conclusion.
DOI 原文 ·
@inproceedings{paperbot6681,
title = {Empirical evaluation of smart contract testing: what is the best choice?},
author = {Meng Ren and Zijing Yin and Fuchen Ma and Zhenyang Xu and Yu Jiang and Chengnian Sun and Huizhong Li and Yan Cai},
booktitle = {ISSTA},
year = {2021},
doi = {10.1145/3460319.3464837}
}