TY - GEN
T1 - Seeding and Mocking in White-Box Fuzzing Enterprise RPC APIs
T2 - 39th ACM/IEEE International Conference on Automated Software Engineering, ASE 2024
AU - Zhang, Man
AU - Arcuri, Andrea
AU - Teng, Piyun
AU - Xue, Kaiming
AU - Wang, Wenhao
N1 - Publisher Copyright:
© 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.
PY - 2024/10/27
Y1 - 2024/10/27
N2 - 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.
AB - 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.
KW - SBST
KW - automated test case generation
KW - fuzzing
KW - microservices
UR - https://www.scopus.com/pages/publications/85212441432
U2 - 10.1145/3691620.3695265
DO - 10.1145/3691620.3695265
M3 - 会议稿件
AN - SCOPUS:85212441432
T3 - Proceedings - 2024 39th ACM/IEEE International Conference on Automated Software Engineering, ASE 2024
SP - 2024
EP - 2034
BT - Proceedings - 2024 39th ACM/IEEE International Conference on Automated Software Engineering, ASE 2024
PB - Association for Computing Machinery, Inc
Y2 - 28 October 2024 through 1 November 2024
ER -