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Detecting access anomalies in programs with critical sections

Authors:

Anne Dinning,

Edith SchonbergAuthors Info & Claims

ACM SIGPLAN Notices, Volume 26, Issue 12

Pages 85 - 96

https://doi.org/10.1145/127695.122767

Published: 01 December 1991 Publication History

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References

[1]

Allen, T. R. and D. Padua. Debugging Fortran on a Shared Memory Machine. Proc. International Conference on Parallel Processing, August 1987, pages 721-727.

Google Scholar

[2]

Appelbe, B. and Charles E. McDowell. Developing Multitasking Applications Programs. In Proceedings of the 21st Annual Hawaii International Conference on Systems Science, pages 94-102, 1988.

Digital Library

Google Scholar

[3]

Bernstein, A. J. Program Analysis for Parallel Processing. Transactions on Electronic Computers, EC-15(5):757-762, October 1966.

Google Scholar

[4]

Callahan, D. and K. Kennedy. Analysis of Interprocedural Side Effects in a Parallel Programming Environment. In Proceedings of the First inlernational Conference on Supercomputing, pages 139-171, june 1987.

Digital Library

Google Scholar

[5]

Callahan, D., K. Kennedy, and J. Subhlok. Analysis of Event Synchronization in a Parallel Programming Tool. In Proceedings of Second A CM SIGPLAN Symposium on Principles and Praclice of Parallel Programming, March 1990.

Digital Library

Google Scholar

[6]

Choi, Jong-Deok. Parallel Program Debugging with Flowback Analysis. PhD thesis, University of Wisconsin- Madison, 1989.

Digital Library

Google Scholar

[7]

Choi, Jong-Deok and S. L. Min. Race Frontier: Reproducing Data Races in Parallel-Program Debugging. Proc. of the 3rd Symposium on Principles and Practice of Parallel Programming, April 1991.

Digital Library

Google Scholar

[8]

Dinning, Anne. Detecting Nondeterminism in Parallel Programs. PhD thesis, New York University, October 1990.

Digital Library

Google Scholar

[9]

Dinning, A. and Edith Sehonberg. An Empirical Comparison of Monitoring Algorithms for Access Anomaly Detection. In Proceedings of the Second A CM SIGPLAN Symposium on Principles and Practice of Parallel Programming, pages 1 - 10, March 1990.

Crossref

Google Scholar

[10]

Emrath, A. and D. A. Padua. Automatic Detection of Nondeterminancy in Parallel Programs. In Proceedings of the SIGPLAN Workshop on Parallel and Distributed Debugging, pages 89-99, May 1988.

Digital Library

Google Scholar

[11]

Ferrante, J., K. Ottenstein, and J.D. Warren. The Program Dependence Graph and its Uses in Optimization. A CM Transaction on Programming Languages and Systems, 9(3):319- 349, July 1987.

Digital Library

Google Scholar

[12]

Helmbold, D.P., C.E.McDowell and J.Z. Wang. Detecting Data Races from Sequential Traces. Proc. Hawaii International Conference on System Sciences, 1991, pp. 408-417.

Crossref

Google Scholar

[13]

Hood, R., K. Kennedy, and J. Mellor- Crummey. Parallel Program Debugging with On-the-fly Anomaly Detection. Supercomputing '90, November 1990.

Digital Library

Google Scholar

[14]

Lamport, Leslie. Time, Clocks, and the Ordering of Events in a Distributed System. Communications of the A CM, 21(7), July 1978.

Digital Library

Google Scholar

[15]

LeBlanc, T.J., and J.M. Mellor-Crummey. Debugging Parallel Programs with Instant Replay. IEEE Transactions on Computers, C- 36(4):471-482, April 1987.

Digital Library

Google Scholar

[16]

Miller, B. P. and Jong-Deok Choi. A Mechanism for Efficient Debugging of Parallel Programs. In Proceedings of the SIGPLAN Conference on Programming Language Design and implementation, June 1988.

Digital Library

Google Scholar

[17]

Netzer, R.I-I.B. and B.P. Miller. Detecting Data Races in Parallel Program Executions. Languages and Compilers for Parallel Comput. ing, ed. D. Gelernter, 2'. Gross, A. Nicolau, and D. Padua, MIT Press (1991). Also Proc. of the 3rd Workshop on Programming Languages and Compilers for Parallel Computing, August 1990.

Google Scholar

[18]

Netzer, R.H.B. and B.P. Miller. Improving the Accuracy of Data Race Detection. Proc. of the 3rd Symposium on Principles and Practice of Parallel Programming, April 1991.

Digital Library

Google Scholar

[19]

Netzer, R.H.B. Private Communication, 1991.

Google Scholar

[20]

Nudler, Itzhak and Larry Rudolph. Tools for the Efficient Development of Efficient Parallel Programs. Israeli .Conference on Computer System Engineering, 1988.

Google Scholar

[21]

Ottenstein, K. and L. Ottenstein. The Program Dependence Graph in a Software Development Environment. Proceedings of the A CM SIGSOFT/SIBPLAN Symposium on Practical Software Development Environments, April 1984.

Digital Library

Google Scholar

[22]

Schonberg, Edith. On-The-Fly Detection of Access Anomalies. In Proceedings of the SIG- PLAN Conference on Programming Language Design and Implementation, June 1989.

Digital Library

Google Scholar

[23]

Snir, Marc. Private Communication, 1988.

Google Scholar

[24]

Weiser, Mark. Program Slicing. IEEE Transactions on Software Engineering, SE- 10(4):352-357, july 1984.

Google Scholar

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Zhu SGuo YZhang LCai YGrundy JPollock LPenta M(2023)Tolerate Control-Flow Changes for Sound Data Race PredictionProceedings of the 45th International Conference on Software Engineering10.1109/ICSE48619.2023.00118(1342-1354)Online publication date: 14-May-2023
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Guo YLiang ZZhu SWang JYang ZShen WZhang JCai Y(2023)Sound Predictive Fuzzing for Multi-threaded Programs2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC)10.1109/COMPSAC57700.2023.00110(810-819)Online publication date: Jun-2023
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Detecting access anomalies in programs with critical sections

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Information

Published In

ACM SIGPLAN Notices Volume 26, Issue 12

Dec. 1991

192 pages

ISSN:0362-1340

EISSN:1558-1160

DOI:10.1145/127695

Editor:
Richard L. Wexelblat
ACM SIGPLAN Notices, Alexandria, VA

Issue’s Table of Contents

PADD '91: Proceedings of the 1991 ACM/ONR workshop on Parallel and distributed debugging
December 1991
206 pages
ISBN:0897914570
DOI:10.1145/122759
Chairmen:
Barton Miller
Univ. of Wisconsin, Madison
,
Charles McDowell
Univ. of California, Santa Cruz

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 01 December 1991

Published in SIGPLAN Volume 26, Issue 12

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https://dl.acm.org/doi/10.1109/ICSE48619.2023.00118
Guo YLiang ZZhu SWang JYang ZShen WZhang JCai Y(2023)Sound Predictive Fuzzing for Multi-threaded Programs2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC)10.1109/COMPSAC57700.2023.00110(810-819)Online publication date: Jun-2023
https://doi.org/10.1109/COMPSAC57700.2023.00110
Jahić JDoganci VGehring H(2022)CASA: An Approach for Exposing and Documenting Concurrency-Related Software PropertiesEmbedded Computer Systems: Architectures, Modeling, and Simulation10.1007/978-3-031-15074-6_9(139-154)Online publication date: 3-Jul-2022
https://dl.acm.org/doi/10.1007/978-3-031-15074-6_9
Cai YYun HWang JQiao LPalsberg JSpinellis DGousios GChechik MDi Penta M(2021)Sound and efficient concurrency bug predictionProceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3468264.3468549(255-267)Online publication date: 20-Aug-2021
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Shirole MKumar R(2021)Concurrency coverage criteria for activity diagramsIET Software10.1049/sfw2.1200915:1(43-54)Online publication date: 19-Jan-2021
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Shirole MKumar R(2021)Constrained permutation-based test scenario generation from concurrent activity diagramsInnovations in Systems and Software Engineering10.1007/s11334-021-00389-417:4(343-353)Online publication date: 1-Dec-2021
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Sulzmann MStadtmüller KMarr S(2020)Efficient, near complete, and often sound hybrid dynamic data race predictionProceedings of the 17th International Conference on Managed Programming Languages and Runtimes10.1145/3426182.3426185(30-51)Online publication date: 4-Nov-2020
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On The Limits of Detecting Process Anomalies in Critical Infrastructure

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