Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/10313
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dc.contributor.authorSmith, G-
dc.contributor.authorDerrick, J-
dc.contributor.authorDongol, B-
dc.date.accessioned2015-03-02T16:00:27Z-
dc.date.available2015-
dc.date.available2015-03-02T16:00:27Z-
dc.date.issued2015-
dc.identifier.citationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8997: 364 - 383, (January 2015)en_US
dc.identifier.isbn978-3-319-15316-2-
dc.identifier.urihttp://link.springer.com/chapter/10.1007%2F978-3-319-15317-9_22-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/10313-
dc.description“The final publication is available at http://link.springer.com/chapter/10.1007%2F978-3-319-15317-9_22 ”.en_US
dc.description.abstractLinearizability has become the standard correctness criterion for fine-grained non-atomic concurrent algorithms, however, most approaches assume a sequentially consistent memory model, which is not always realised in practice. In this paper we study the correctness of concurrent algorithms on a weak memory model: the TSO (Total Store Order) memory model, which is commonly implemented by multicore architectures. Here, linearizability is often too strict, and hence, we prove a weaker criterion, quiescent consistency instead. Like linearizability, quiescent consistency is compositional making it an ideal correctness criterion in a component-based context. We demonstrate how to model a typical concurrent algorithm, seqlock, and prove it quiescent consistent using a simulation-based approach. Previous approaches to proving correctness on TSO architectures have been based on linearizabilty which makes it necessary to modify the algorithm’s high-level requirements. Our approach is the first, to our knowledge, for proving correctness without the need for such a modification.en_US
dc.format.extent364 - 383-
dc.format.extent364 - 383-
dc.language.isoenen_US
dc.publisherSpringer International Publishingen_US
dc.subjectLinearizabilityen_US
dc.subjectConcurrent algorithmsen_US
dc.subjectWeak memory modelen_US
dc.subjectTotal Store Order memory modelen_US
dc.titleAdmit your weakness: Verifying correctness on TSO architecturesen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.1007/978-3-319-15317-9_22-
dc.relation.isPartOfLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.relation.isPartOfLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
pubs.volume8997-
pubs.volume8997-
pubs.organisational-data/Brunel-
pubs.organisational-data/Brunel/Brunel Staff by College/Department/Division-
pubs.organisational-data/Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences-
pubs.organisational-data/Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences/Dept of Computer Science-
pubs.organisational-data/Brunel/Brunel Staff by College/Department/Division/College of Engineering, Design and Physical Sciences/Dept of Computer Science/Computer Science-
Appears in Collections:Dept of Computer Science Research Papers

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