A Model-Based Framework for Cloud API Testing

Abstract

Following the Service-Oriented Architecture, a large number of diversified Cloud services are exposed as Web APIs (Application Program Interface), which serve as the contracts between the service providers and service consumers. Due to their massive and broad applications, any flaw in the cloud APIs may lead to serious consequences. API testing is thus necessary to ensure the availability, reliability, and stability of cloud services. The research proposes a model-based approach to automating API testing. The semi-structured API specifications, like XML/HTML specifications, are gathered from the Web sites using web crawlers, and translated into YAML-encoded standard representations. A scenario editor is designed to specify the dependencies among API operations. Test generators are built to derive test scripts from the specifications and scenarios, including test data, test cases for individual operations as well as operations sequences. Various algorithms can be used for test generation, such as combinatorial data generation, heuristic graph search, and optimization algorithms. The produced test scripts, together with a load model, can be deployed on Cloud and scheduled for execution. A prototype system, called ATCloud, was constructed to illustrate the process of API understanding, test scenario modeling using directed diagraph annotated with transfer probabilities between operations, cloud-based test resources management, distributed workload simulation, and performance monitoring.