Violations of a number of common safety properties of multithreaded programs - such as atomicity and absence of dataraces - cannot be observed by looking at the linear execution trace. We characterize a class of such properties, called robust properties, and define a simple but expressive epistemic logic to specify them. We then develop an efficient algorithm to automatically monitor and predict violations of robust safety properties. Our algorithm is based on capturing the causal structure of a computation through a mechanism similar to vector clock updates. The algorithm automatically synthesizes decentralized monitors to evaluate the information at each thread and to detect and predict safety violations. Based on this approach, a tool named DAME has been developed and evaluated on some simple examples.

We present a new model checking algorithm for verifying computation tree logic (CTL) properties. To our knowledge, this is the first CTL model checking algorithm for infinite state systems that can also handle fairness constraints. Our technique is based on using language inference to learn the fixpoints necessary for checking a CTL formula instead of computing them iteratively as is done in traditional model checking. This allows us to analyze infinite or large state-space systems where the traditional iterations may not converge or may take too long to converge. Our procedure is guaranteed to terminate with the correct answer if fixpoints needed for all subformulas of the CTL property are regular. We have extended our LEVER tool to use the technique presented in this paper and demonstrate its effectiveness by verifying a number of parametric and integer systems.

We describe an efficient decentralized monitoring algorithm that monitors a distributed program's execution to check for violations of safety properties. The monitoring is based on formulae written in PT-DTL, a variant of past time linear temporal logic that we define. PT-DTL is suitable for expressing temporal properties of distributed systems. Specifically, the formulae of PT-DTL are relative to a particular process and are interpreted over a projection of the trace of global states that represents what that process is aware of. A formula relative to one process may refer to other processes' local states through remote expressions and remote formulae. In order to correctly evaluate remote expressions, we introduce the notion of Knowledge Vector and provide an algorithm which keeps a process aware of other processes' local states that can affect the validity of a monitored PT-DTL formula. Both the logic and the monitoring algorithm are illustrated through a number of examples. Finally, we describe our implementation of the algorithm in a tool called DIANA.