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Dynamic race detection is the problem of determining if an observed programexecution reveals the presence of a data race in a program. The classicalapproach to solving this problem is to detect if there is a pair of conflictingmemory accesses that are unordered by Lamport's happens-before (HB) relation.HB based race detection is known to not report false positives, i.e., it issound. However, the soundness guarantee of HB only promises that the first pairof unordered, conflicting events is a schedulable data race. That is, there canbe pairs of HB-unordered conflicting data accesses that are not schedulableraces because there is no reordering of the events of the execution, where theevents in race can be executed immediately after each other. We introduce a newpartial order, called schedulable happens-before (SHB) that exactlycharacterizes the pairs of schedulable data races --- every pair of conflictingdata accesses that are identified by SHB can be scheduled, and every HB-racethat can be scheduled is identified by SHB. Thus, the SHB partial order istruly sound. We present a linear time, vector clock algorithm to detectschedulable races using SHB. Our experiments demonstrate the value of ouralgorithm for dynamic race detection --- SHB incurs only little performanceoverhead and can scale to executions from real-world software applicationswithout compromising soundness.

What Happens - After the First Race? Enhancing the Predictive Power of Happens - Before Based Dynamic Race Detection