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Detecting and isolating bugs that arise in parallel programs is a tedious and a challenging task. An especially subtle class of bugs is those that are scale-dependent: while small-scale test cases may not exhibit the bug, the bug arises in large-scale production runs, and can change the result or performance of an application. A popular approach to finding bugs is statistical bug detection, where abnormal behavior is detected through comparison with bug-free behavior. Unfortunately, for scale-dependent bugs, there may not be bug-free runs at large scales and therefore traditional statistical techniques are not viable. In this paper, the authors propose Vrisha, a statistical approach to detecting and localizing scale-dependent bugs.
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