Automated Software Testing Frameworks for Cloud-Native Applications

Abstract

Cloud-native applications—commonly composed of microservices and deployed in containerized, dynamic environments—demand robust, automated testing frameworks to ensure reliability, scalability, and rapid deployment. This paper surveys key automated testing tools and methodologies established before 2019 for cloud native systems. We analyze techniques including white-box RESTful API test-case generation (EVOMASTER), automated unit test generation (EvoSuite), BDD frameworks (Cucumber), API contract testing (Pact), and integration testing tools such as Postman, Karate, and Wiremock. Through literature synthesis and selected case studies, we assess how these frameworks address the unique complexities of microservices—such as frequent deployment, service contracts, and test environment instability. The methodology blends systematic literature review with practical evaluation via implementation scenarios. Notable findings include the effectiveness of consumer-driven contract testing and mocking strategies to decouple services during testing, and the use of automated test generation tools to discover edge-case faults in REST APIs and Java code. We propose a structured testing workflow for cloud-native applications: service decomposition analysis, unit and mutation test generation, contract definition and testing, API and integration testing with simulation of dependencies, and CI-linked test automation. Advantages include improved test coverage, faster feedback loops, and reduced reliance on fragile end-to-end tests; disadvantages involve higher complexity in setup, potential maintenance overhead, and the challenge of generating meaningful tests in distributed environments. Results show that combining these tools within CI/CD pipelines enhances reliability and scalability. We conclude that automated testing frameworks are essential to cloud-native development; future work should explore AI-assisted test generation, better orchestration of ephemeral test environments, and integrated observability-driven testing.