NDLI: Automatically classifying benign and harmful data races using replay analysis

Content Provider	ACM Digital Library
Author	Wang, Zhenghao Calder, Brad Narayanasamy, Satish Edwards, Andrew Tigani, Jordan
Abstract	Many concurrency bugs in multi-threaded programs are due to dataraces. There have been many efforts to develop static and dynamic mechanisms to automatically find the data races. Most of the prior work has focused on finding the data races and eliminating the false positives. In this paper, we instead focus on a dynamic analysis technique to automatically classify the data races into two categories - the dataraces that are potentially benign and the data races that are potentially harmful. A harmful data race is a real bug that needs to be fixed. This classification is needed to focus the triaging effort on those data races that are potentially harmful. Without prioritizing the data races we have found that there are too many data races to triage. Our second focus is to automatically provide to the developer a reproducible scenario of the data race, which allows the developer to understand the different effects of a harmful data race on a program's execution. To achieve the above, we record a multi-threaded program's execution in a replay log. The replay log is used to replay the multi-threaded program, and during replay we find the data races using a happens-before based algorithm. To automatically classify if a data race that we find is potentially benign or potentially harmful, were play the execution twice for a given data race - one for each possible order between the conflicting memory operations. If the two replays for the two orders produce the same result, then we classify the data race to be potentially benign. We discuss our experiences in using our replay based dynamic data race checker on several Microsoft applications.
Starting Page	22
Ending Page	31
Page Count	10
File Format	PDF
ISSN	03621340 15581160
DOI	10.1145/1273442.1250738
Journal	ACM SIGPLAN Notices (SIGP)
Volume Number	42
Issue Number	6
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1983-05-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Replay Concurrency bbugs Benign data races
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

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Automatically classifying benign and harmful data races using replay analysis

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