Reinforcement Learning-Driven Continuous and Crashless Load Test Architecture

Abstract

Realistic load testing of software systems and continuous testing of the systems is an industry requirement. Within the scope of this study, a software architecture was presented, and prototype implementation was implemented for load testing of live systems with realistic loads continuously and without crashing the system. Experiments of the crashless load test module of the prototype were implemented, and successful results were obtained from experiments.