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          <dc:title>Concurrent Data Structures Linked in Time</dc:title>
          <dc:creator>Delbianco, Germán Andrés</dc:creator>
          <dc:creator>Sergey, Ilya</dc:creator>
          <dc:creator>Nanevski, Aleksandar</dc:creator>
          <dc:creator>Banerjee, Anindya</dc:creator>
          <dc:subject>Separation logic</dc:subject>
          <dc:subject>Linearization Points</dc:subject>
          <dc:subject>Concurrent snapshots</dc:subject>
          <dc:subject>FCSL</dc:subject>
          <dc:description>Arguments about correctness of a concurrent data structure are&#13;
typically carried out by using the notion of linearizability and&#13;
specifying the linearization points of the data structure's&#13;
procedures. Such arguments are often cumbersome as the linearization&#13;
points' position in time can be dynamic (depend on the interference,&#13;
run-time values and events from the past, or even future), non-local&#13;
(appear in procedures other than the one considered), and whose&#13;
position in the execution trace may only be determined after the&#13;
considered procedure has already terminated.&#13;
&#13;
In this paper we propose a new method, based on a separation-style&#13;
logic, for reasoning about concurrent objects with such linearization&#13;
points. We embrace the dynamic nature of linearization points, and&#13;
encode it as part of the data structure's auxiliary state, so that it&#13;
can be dynamically modified in place by auxiliary code, as needed when&#13;
some appropriate run-time event occurs. We name the idea&#13;
linking-in-time, because it reduces temporal reasoning to spatial&#13;
reasoning. For example, modifying a temporal position of a&#13;
linearization point can be modeled similarly to a pointer update in&#13;
separation logic. Furthermore, the auxiliary state provides a&#13;
convenient way to concisely express the properties essential for&#13;
reasoning about clients of such concurrent objects. We illustrate the&#13;
method by verifying (mechanically in Coq) an intricate optimal&#13;
snapshot algorithm due to Jayanti, as well as some clients.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Germán Andrés Delbianco and Ilya Sergey and Aleksandar Nanevski and Anindya Banerjee</dc:contributor>
          <dc:date>2017</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 74, 31st European Conference on Object-Oriented Programming (ECOOP 2017)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
          <dc:type>doc-type:ResearchArticle</dc:type>
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          <dc:format>application/pdf</dc:format>
          <dc:identifier>doi:10.4230/LIPIcs.ECOOP.2017.8</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-72558</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2017.8</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/3.0/legalcode</dc:rights>
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