  Verification planning is a sequential decision-making problem that specifies
a set of verification activities (VA) and correction activities (CA) at
different phases of system development. While VAs are used to identify errors
and defects, CAs also play important roles in system verification as they
correct the identified errors and defects. However, current planning methods
only consider VAs as decision choices. Because VAs and CAs have different
activity spaces, planning a joint verification-correction strategy (JVCS) is
still challenging, especially for large-size systems. Here we introduce a
UCB-based tree search approach to search for near-optimal JVCSs. First,
verification planning is simplified as repeatable bandit problems and an upper
confidence bound rule for repeatable bandits (UCBRB) is presented with the
optimal regret bound. Next, a tree search algorithm is proposed to search for
feasible JVCSs. A tree-based ensemble learning model is also used to extend the
tree search algorithm to handle local optimality issues. The proposed approach
is evaluated on the notional case of a communication system.
