Abstract: A method and a system for automated testing of applications includes crawling an application by an application crawler to identify application states. Rewards associated with the application states are calculated using a reinforcement learning engine, based on a reward matrix. Critical paths are identified by the reinforcement learning engine and are passed to a test scenario generator. Test scripts are generated by the test scenario generator based on the identified critical paths. The applications are tested by a test scenario execution engine based on the generated one or more test scripts, and test data generated by the test data generator. Test results are captured by a behavior analyzer. One or more insights are generated by the behavior analyzer, from the captured test results to update the reward matrix and to improve the efficiency of continuous autonomous testing system.

Abstract: A method and a system for automated testing of applications includes crawling an application by an application crawler to identify application states. Rewards associated with the application states are calculated using a reinforcement learning engine, based on a reward matrix. Critical paths are identified by the reinforcement learning engine and are passed to a test scenario generator. Test scripts are generated by the test scenario generator based on the identified critical paths. The applications are tested by a test scenario execution engine based on the generated one or more test scripts, and test data generated by the test data generator. Test results are captured by a behavior analyzer. One or more insights are generated by the behavior analyzer, from the captured test results to update the reward matrix and to improve the efficiency of continuous autonomous testing system.