Distributed systems are complex, being usually composed of several subsystems running in parallel. Concurrent execution and inter-process communication in these systems are prone to errors that are difficult to detect by traditional testing, which does not cover every possible program execution. Unlike testing, model checking can detect such faults in a concurrent system by exploring every possible state of the system. However, most model-checking techniques require that a system be described in a modeling language. Although this simplifies verification, faults may be introduced in the implementation. Recently, some model checkers verify program code at runtime but tend to be limited to stand-alone programs. This paper proposes cache-based model checking, which relaxes this limitation to some extent by verifying one process at a time and running other processes in another execution environment. This approach has been implemented as an extension of Java PathFinder, a Java model checker. It is a scalable and promising technique to handle distributed systems. To support a larger class of distributed systems, a checkpointing tool is also integrated into the verification system. Experimental results on various distributed systems show the capability and scalability of cache-based model checking.

Verification of distributed software systems by model checking is not a straightforward task due to inter-process communication. Many software model checkers only explore the state space of a single multi-threaded process. Recent work proposes a technique that applies a cache to capture communication between the main process and its peers, and allows the model checker to complete state-space exploration. Although previous work handles non-deterministic output in the main process, any peer program is required to produce deterministic output. This paper introduces a process checkpointing tool. The combination of caching and process checkpointing makes it possible to handle non-determinism on both sides of communication. Peer states are saved as checkpoints and restored when the model checker backtracks and produces a request not available in the cache. We also introduce the concept of strategies to control the creation of checkpoints and the overhead caused by the checkpointing tool.

Many applications are concurrent and communicate over a network. The non-determinism in the thread and communication schedules makes it desirable to model check such systems. However, a simple state space exploration scheme is not applicable, as backtracking results in repeated communication operations. A cache-based approach solves this problem by hiding redundant communication operations from the environment. In this work, we propose a change from a linear-time to a branching-time cache, allowing us to relax restrictions in previous work regarding communication traces that differ between schedules. We successfully applied the new algorithm to real-life programs where a previous solution is not applicable.