Fuzzing Microservices: A Series of User Studies in Industry on Industrial Systems with EvoMaster
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arXiv
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| Auteurs principaux: | , , , , , , , |
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| Format: | Preprint |
| Publié: |
2022
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| _version_ | 1866929468311863296 |
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| author | Zhang, Man Arcuri, Andrea Li, Yonggang Liu, Yang Xue, Kaiming Wang, Zhao Huo, Jian Huang, Weiwei |
| author_facet | Zhang, Man Arcuri, Andrea Li, Yonggang Liu, Yang Xue, Kaiming Wang, Zhao Huo, Jian Huang, Weiwei |
| contents | With several microservice architectures comprising of thousands of web services, used to serve 630 million customers, companies like Meituan face several challenges in the verification and validation of their software. This paper reports on our experience of integrating EvoMaster (a search-based white-box fuzzer) in the testing processes at Meituan over almost 2 years. Two user studies were carried out in 2021 and in 2023 to evaluate two versions of EvoMaster, respectively, in tackling the test generation for industrial web services which are parts of a large e-commerce microservice system. The two user studies involve in total 321,131 lines of code from five APIs and 27 industrial participants at Meituan. Questionnaires and interviews were carried out in both user studies with employees at Meituan. The two user studies demonstrate clear advantages of EvoMaster (i.e., code coverage and fault detection) and the urgent need to have such a fuzzer in industrial microservices testing. To study how these results could generalize, a follow up user study was done in 2024 with five engineers in the five different companies. Our results show that, besides their clear usefulness, there are still many critical challenges that the research community needs to investigate to improve performance further. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2208_03988 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Fuzzing Microservices: A Series of User Studies in Industry on Industrial Systems with EvoMaster Zhang, Man Arcuri, Andrea Li, Yonggang Liu, Yang Xue, Kaiming Wang, Zhao Huo, Jian Huang, Weiwei Software Engineering With several microservice architectures comprising of thousands of web services, used to serve 630 million customers, companies like Meituan face several challenges in the verification and validation of their software. This paper reports on our experience of integrating EvoMaster (a search-based white-box fuzzer) in the testing processes at Meituan over almost 2 years. Two user studies were carried out in 2021 and in 2023 to evaluate two versions of EvoMaster, respectively, in tackling the test generation for industrial web services which are parts of a large e-commerce microservice system. The two user studies involve in total 321,131 lines of code from five APIs and 27 industrial participants at Meituan. Questionnaires and interviews were carried out in both user studies with employees at Meituan. The two user studies demonstrate clear advantages of EvoMaster (i.e., code coverage and fault detection) and the urgent need to have such a fuzzer in industrial microservices testing. To study how these results could generalize, a follow up user study was done in 2024 with five engineers in the five different companies. Our results show that, besides their clear usefulness, there are still many critical challenges that the research community needs to investigate to improve performance further. |
| title | Fuzzing Microservices: A Series of User Studies in Industry on Industrial Systems with EvoMaster |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2208.03988 |