Drift: Deep reinforcement learning for functional software testing
L Harries, RS Clarke, T Chapman… - arXiv preprint arXiv …, 2020 - arxiv.org
Efficient software testing is essential for productive software development and reliable user
experiences. As human testing is inefficient and expensive, automated software testing is
needed. In this work, we propose a Reinforcement Learning (RL) framework for functional
software testing named DRIFT. DRIFT operates on the symbolic representation of the user
interface. It uses Q-learning through Batch-RL and models the state-action value function
with a Graph Neural Network. We apply DRIFT to testing the Windows 10 operating system …
experiences. As human testing is inefficient and expensive, automated software testing is
needed. In this work, we propose a Reinforcement Learning (RL) framework for functional
software testing named DRIFT. DRIFT operates on the symbolic representation of the user
interface. It uses Q-learning through Batch-RL and models the state-action value function
with a Graph Neural Network. We apply DRIFT to testing the Windows 10 operating system …
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