Using causality to diagnose configuration bugs

Mona Attariyan and Jason Flinn

Abstract

We present a novel method for diagnosing configuration management errors. Our proposed approach deduces the state of a buggy computer by running predicates that test system correctness and comparing the resulting execution to that generated by running the same predicates on a reference computer. Our approach generates signatures that represent the execution path of a predicate by recording the causal dependencies of its execution. Our results show that comparisons based on dependency sets significantly outperform comparisons based on predicate success or failure, uniquely identifying the correct bug 86-100% of the time. In the remaining cases, the dependency set method identifies the correct bug as one of two equally likely bugs.