From Greedy Steps to Global Optimization: Learning Sequential Test Suite Generation
This paper formalizes test suite generation as a Markov Decision Process (MDP) and demonstrates that its objective exhibits monotone submodularity, which enables an effective relaxation of this NP-hard global optimization into a tractable step-wise greedy procedure.