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Data races, a condition where two memory accesses to the same memory location occur concurrently, have been shown to be a major source of concurrency bugs in distributed systems. Unfortunately, data races are often triggered by non-deterministic event orderings that are hard to detect when testing complex distributed systems. In this paper, we propose Spider, an automated tool for identifying data races in distributed system traces. Spider encodes the causal relations between the events in the trace as a symbolic constraint model, which is then fed into an SMT solver to check for the presence of conflicting concurrent accesses. To reduce the constraint solving time, Spider employs a pruning technique aimed at removing redundant portions of the trace. Our experiments with multiple benchmarks show that Spider is effective in detecting data races in distributed executions in a practical amount of time, providing evidence of its usefulness as a testing tool.

Go is an increasingly-popular systems programming language targeting, especially, concurrent and distributed systems. Go differentiates itself from other imperative languages by offering structural subtyping and lightweight concurrency through goroutines with messagepassing communication. This combination of features poses interesting challenges for static verification, most prominently the combination of a mutable heap and advanced concurrency primitives. We present Gobra, a modular, deductive program verifier for Go that proves memory safety, crash safety, data-race freedom, and user-provided specifications. Gobra is based on separation logic and supports a large subset of Go. Its implementation translates an annotated Go program into the Viper intermediate verification language and uses an existing SMT-based verification backend to compute and discharge proof obligations.