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With several microservice architectures comprising of thousands of webservices in total, used to serve 630 million customers, companies like Meituanface several challenges in the verification and validation of their software.The use of automated techniques, especially advanced AI-based ones, could bringsignificant benefits here. EvoMaster is an open-source test case generationtool for web services, that exploits the latest advances in the field ofSearch-Based Software Testing research. This paper reports on our experience ofintegrating the EvoMaster tool in the testing processes at Meituan. Experimentswere carried out to evaluate its performance in detail on two industrial webservices which are parts of a large e-commerce microservices. A questionnaireand interviews were carried out with the engineers and managers at Meituan, tobetter understand the applicability and usability of fuzzing tools likeEvoMaster in real industrial settings. On the one hand, the results of theseanalyses clearly show that existing tools like EvoMaster are already ofbenefits for practitioners in industry, e.g., EvoMaster detected 21 real faultsand achieved an average of 71.3% coverage for code defining endpoints and 51.7%coverage for code implementing business logic, on two industrial APIs. On theother hand, there are still many critical challenges that the researchcommunity has to investigate.

Fuzzing Microservices In Industry: Experience of Applying EvoMaster at Meituan