Predicting all data race pairs for a specific schedule

Author:

Sulzmann Martin1,Stadtmüller Kai1

Affiliation:

1. Karlsruhe University of Applied Sciences, Germany

Publisher

ACM Press

Reference17 articles.

1. Utpal Banerjee, Brian Bliss, Zhiqiang Ma, and Paul Petersen. 2006. A theory of data race detection. In Proceedings of the 2006 workshop on Parallel and distributed systems: testing and debugging. ACM, 69–78.

2. Stephen M. Blackburn, Robin Garner, Chris Hoffmann, Asjad M. Khang, Kathryn S. McKinley, Rotem Bentzur, Amer Diwan, Daniel Feinberg, Daniel Frampton, Samuel Z. Guyer, Martin Hirzel, Antony Hosking, Maria Jump, Han Lee, J. Eliot B. Moss, Aashish Phansalkar, Darko Stefanović, Thomas VanDrunen, Daniel von Dincklage, and Ben Wiedermann. 2006. The DaCapo Benchmarks: Java Benchmarking Development and Analysis. In Proc. of OOPSLA ’06. ACM, New York, NY, USA, 169–190.

3. Anne Dinning and Edith Schonberg. 1991. Detecting Access Anomalies in Programs with Critical Sections. SIGPLAN Not. 26, 12 (Dec. 1991), 85–96.

4. Colin J. Fidge. 1988. Timestamps in message-passing systems that preserve the partial ordering. Proceedings of the 11th Australian Computer Science Conference 10, 1 (1988), 56–66. http://sky.scitech.qut.edu.au/~fidgec/ Publications/fidge88a.pdf

5. Cormac Flanagan and Stephen N Freund. 2010a. FastTrack: efficient and precise dynamic race detection. Commun. ACM 53, 11 (2010), 93–101.

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1. Efficient, near complete, and often sound hybrid dynamic data race prediction;Proceedings of the 17th International Conference on Managed Programming Languages and Runtimes;2020-11-04

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