一句话：提出 FuzzBench 开放平台与服务，为 fuzzer 评估提供统一、可复现的基准测试基础设施。
模糊测试（fuzzing）是降低生产软件缺陷的关键工具，在 Google 已发现数万个 bug，也是学术研究热点，2020 年相关论文超过 120 篇。然而，如何正确评估模糊测试技术仍缺乏共识，社区在评估方法论和标准工具上难以统一。为此，作者提出 FuzzBench，一个开放的 fuzzer 基准测试平台与服务，旨在为 fuzzer 与模糊测试技术的开发、改进和评估提供标准化、可复现的基准测试基础设施。摘要侧重于问题动机与平台定位，未给出具体实验数据或评估结果。
Fuzzing is a key tool used to reduce bugs in production software. At Google, fuzzing has uncovered tens of thousands of bugs. Fuzzing is also a popular subject of academic research. In 2020 alone, over 120 papers were published on the topic of improving, developing, and evaluating fuzzers and fuzzing techniques. Yet, proper evaluation of fuzzing techniques remains elusive. The community has struggled to converge on methodology and standard tools for fuzzer evaluation.
@inproceedings{paperbot6359,
title = {FuzzBench: an open fuzzer benchmarking platform and service},
author = {Jonathan Metzman and László Szekeres and Laurent Simon and Read Sprabery and Abhishek Arya},
booktitle = {FSE},
year = {2021},
doi = {10.1145/3468264.3473932}
}