DeepREST: Automated Test Case Generation for REST APIs Exploiting Deep Reinforcement Learning
Davide Corradini, Zeno Montolli, Michele Pasqua, Mariano Ceccato
Abstract
Automatically crafting test scenarios for REST APIs helps deliver more reliable and trustworthy web-oriented systems. However, current black-box testing approaches rely heavily on the information available in the API's formal documentation, i.e., the Open API Specification (OAS for short). While useful, the OAS mostly covers syntactic aspects of the API (e.g., producer-consumer relations between operations, input value properties, and additional constraints in natural language), and it lacks a deeper understanding of the API business logic. Missing semantics include implicit ordering (logic dependency) between operations and implicit input-value constraints. These limitations hinder the ability of black-box testing tools to generate truly effective test cases automatically.