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Data Independence for Software Transactional Memory

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NASA Formal Methods (NFM 2019)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 11460))

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Abstract

Software Transactional Memory (STM) algorithms provide programmers with a synchronisation mechanism for concurrent access to shared variables. Basically, programmers can specify transactions (reading from and writing to shared state) which then execute in a “seeming” atomicity. This property is captured in a correctness criterion called opacity. For model checking the opacity of an STM algorithm, we – in principle – need to check opacity for all possible combinations of transactions with all possible values to be written. This leads to several sources of infinity during model checking: infinitely many data values, infinitely many possible accesses in transactions, and unboundedly many transactions being executed.

In this paper, we propose a technique for avoiding the first source of infinity: infinitely many different data values. To this end, we employ a notion of data independence and provide two results. First, we prove that opacity as a correctness criterion is data independent. Second, we develop conditions for checking data independence of STM algorithms and show their soundness. Together, these results allow to reduce model checking (of data independent STMs) to transactions with a single choice for values written.

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Notes

  1. 1.

    This is the main difference to [2]: Abdulla et al. only have data values as they consider operations on concurrent data structures where the data structure is fixed and thus need not be a parameter to the method.

  2. 2.

    Note that non-data values are not counted here.

  3. 3.

    Note that a transaction writes at most once to a location.

  4. 4.

    Meta data cannot be accessed via TM operations.

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Correspondence to Jürgen König .

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König, J., Wehrheim, H. (2019). Data Independence for Software Transactional Memory. In: Badger, J., Rozier, K. (eds) NASA Formal Methods. NFM 2019. Lecture Notes in Computer Science(), vol 11460. Springer, Cham. https://doi.org/10.1007/978-3-030-20652-9_18

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  • DOI: https://doi.org/10.1007/978-3-030-20652-9_18

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  • Online ISBN: 978-3-030-20652-9

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