Doherty, S. and Derrick, J. (2016) Linearizability and Causality. In: Software Engineering and Formal Methods. 14th International Conference, SEFM 2016, 04-08 Jul 2016, Vienna, Austria. Lecture Notes in Computer Science, 9763 . Springer , pp. 45-60. ISBN 978-3-319-41590-1
Abstract
Most work on the verification of concurrent objects for shared memory assumes sequential consistency, but most multicore processors support only weak memory models that do not provide sequential consistency. Furthermore, most verification efforts focus on the linearizability of concurrent objects, but there are existing implementations optimized to run on weak memory models that are not linearizable.
In this paper, we address these problems by introducing causal linearizability, a correctness condition for concurrent objects running on weak memory models. Like linearizability itself, causal linearizability enables concurrent objects to be composed, under weak constraints on the client’s behaviour. We specify these constraints by introducing a notion of operation-race freedom, where programs that satisfy this property are guaranteed to behave as if their shared objects were in fact linearizable.
We apply these ideas to objects from the Linux kernel, optimized to run on TSO, the memory model of the x86 processor family.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 Springer International Publishing. This is an author produced version of a paper subsequently published in Theoretical Computer Science and General Issues. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 14 Mar 2017 10:34 |
Last Modified: | 19 Jun 2019 15:27 |
Status: | Published |
Publisher: | Springer |
Series Name: | Lecture Notes in Computer Science |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-319-41591-8_4 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:113094 |