This document describes the artifact for the paper DeepREST: Automated Test Case Generation for REST APIs Exploiting Deep Reinforcement Learning, accepted for publication in the proceedings of the 39th International Conference on Automated Software Engineering - Research Papers (ASE 2024). The paper proposes a novel approach for automated black-box testing of REST APIs based on Deep Reinforcement Learning (DRL). To empirically validate the proposed approach, the paper provides DeepREST, an HTTP interaction generator targeting REST APIs that relies on DRL. The empirical evaluation has been carried out in the form of a comparative analysis of testing effectiveness and efficiency against state-of-the-art REST API black-box testing tools on a set of benchmark REST APIs.

The goal of the artifact is to facilitate the replication of the results presented in such empirical evaluation, as well as to explain how to use the tool DeepREST. The artifact includes the usage documentation of the tool, its source code, build scripts for DeepREST and the other tools in the comparison, the set of APIs used in the evaluation, and a detailed description of how to replicate the experiment.