跳到主要导航 跳到搜索 跳到主要内容

Seeding and Mocking in White-Box Fuzzing Enterprise RPC APIs: An Industrial Case Study

  • Man Zhang*
  • , Andrea Arcuri
  • , Piyun Teng
  • , Kaiming Xue
  • , Wenhao Wang
  • *此作品的通讯作者
  • Kristiania University College
  • Meituan

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

Microservices is now becoming a promising architecture to build large-scale web services in industry. Due to the high complexity of enterprise microservices, industry has an urgent need to have a solution to enable automated testing of such systems. EvoMaster is an open-source fuzzer, equipped with the state-of-the-art techniques for supporting automated system-level testing of Web APIs. It has been assessed as the most performant tool in two recent empirical studies in terms of line coverage and fault detection. In this paper, we carried out an empirical experiment to investigate how to better apply the state-of-the-art academic prototype (i.e., EvoMaster) in industrial context. We extended the tool to handle seeding of existing industrial tests, and mocking of external services with their data handled as part of the input fuzzing. We studied two configurations of EvoMaster, using two time budgets, on 40 enterprise RPC-based APIs (involving 5.6 million lines of code for their core business logic) at Meituan. Results show that, compared to existing practice of manual system-level testing and tests produced by record and replay of online traffic, EvoMaster demonstrates clear additional benefits. EvoMaster with the best configuration is capable of covering up to 32.4% line coverage, covering more than 10% line coverage on 36 out of 40 (90%) case studies, and identifying on average 3520 potential faults in these 40 APIs. In addition, we also identified and discussed important challenges in fuzzing enterprise microservices that must be addressed in the future.

源语言英语
主期刊名Proceedings - 2024 39th ACM/IEEE International Conference on Automated Software Engineering, ASE 2024
出版商Association for Computing Machinery, Inc
页2024-2034
页数11
ISBN(电子版)9798400712487
DOI
出版状态已出版 - 27 10月 2024
活动39th ACM/IEEE International Conference on Automated Software Engineering, ASE 2024 - Sacramento, 美国
期限: 28 10月 2024 → 1 11月 2024

丛书

姓名Proceedings - 2024 39th ACM/IEEE International Conference on Automated Software Engineering, ASE 2024

会议

会议39th ACM/IEEE International Conference on Automated Software Engineering, ASE 2024
国家/地区美国
市Sacramento
时期28/10/24 → 1/11/24

学术指纹

探究 'Seeding and Mocking in White-Box Fuzzing Enterprise RPC APIs: An Industrial Case Study' 的科研主题。它们共同构成独一无二的学术指纹。

引用此