Abstract—To aid the formal verification of fault-tolerant distributed protocols, we propose an approach that significantly reduces the costs of their model checking. These protocols often specify atomic, process-local events that consume a set of messages, change the state of a process, and send zero or more messages. We call such events quorum transitions and leverage them to optimize state exploration in two ways. First, we generate fewer states compared to models where quorum transitions are expressed by single-message transitions. Second, we refine transitions into a set of equivalent, finer-grained transitions that allow partial-order algorithms to achieve better reduction. We implement the MP-Basset model checker, which supports refined quorum transitions. We model check protocols representing core primitives of deployed reliable distributed systems, namely: Paxos consensus, regular storage, and Byzantine-tolerant multicast. We achieve up to 92 % memory and 85 % time reduction compared to model checking with standard unrefined single-message transitions. I.

In multithreaded programs both environment input data and the nondeterministic interleavings of concurrent events can affect the behavior of the program. One approach to systematically explore the nondeterminism caused by input data is dynamic symbolic execution. For testing multithreaded programs we present a new approach that combinesdynamicsymbolicexecutionwithunfoldings, amethod originally developed for Petri nets but also applied to many other models of concurrency. We provide an experimental comparison of our new approach with existing algorithms combining dynamic symbolic execution and partial-order reductions and show that the new algorithm can explore the reachable control states of each thread with a significantly smaller number of test runs. In some cases the reduction to the number of test runs can be even exponential allowing programs with long test executions or hard-to-solve constrains generated by symbolic execution to be tested more efficiently. Categories andSubject Descriptors