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Mining temporal invariants from partially ordered logs
Managing Large-scale Systems via the Analysis of System Logs and the Application of Machine Learning Techniques on - SLAML '11
A common assumption made in log analysis research is that the underlying log is totally ordered. For concurrent systems, this assumption constrains the generated log to either exclude concurrency altogether, or to capture a particular interleaving of concurrent events. This paper argues that capturing concurrency as a partial order is useful and often indispensable for answering important questions about concurrent systems. To this end, we motivate a family of event ordering invariants overdoi:10.1145/2038633.2038636 fatcat:qvclvczcyvh57oluh4jhxjdjti