  A key problem in constrained random verification (CRV) concerns generation of
input stimuli that result in good coverage of the system's runs in targeted
corners of its behavior space. Existing CRV solutions however provide no formal
guarantees on the distribution of the system's runs. In this paper, we take a
first step towards solving this problem. We present an algorithm based on
Algebraic Decision Diagrams for sampling bounded traces (i.e. sequences of
states) of a sequential circuit with provable uniformity (or bias) guarantees,
while satisfying given constraints. We have implemented our algorithm in a tool
called TraceSampler. Extensive experiments show that TraceSampler outperforms
alternative approaches that provide similar uniformity guarantees.
