Sound Atomicity Inference for Data-Centric Synchronization
Data-Centric Concurrency Control (DCCC) shifts the reasoning about concurrency restrictions from control structures to data declaration. It is a high-level declarative approach that abstracts away from the actual concurrency control mechanism(s) in use. Despite its advantages, the practical use of D...
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Zusammenfassung: | Data-Centric Concurrency Control (DCCC) shifts the reasoning about
concurrency restrictions from control structures to data declaration. It is a
high-level declarative approach that abstracts away from the actual concurrency
control mechanism(s) in use. Despite its advantages, the practical use of DCCC
is hindered by the fact that it may require many annotations and/or multiple
implementations of the same method to cope with differently qualified
parameters. Moreover, the existing DCCC solutions do not address the use of
interfaces, precluding their use in most object-oriented programs. To overcome
these limitations, in this paper we present AtomiS, a new DCCC model based on a
rigorously defined type-sound programming language. Programming with AtomiS
requires only (atomic)-qualifying types of parameters and return values in
interface definitions, and of fields in class definitions. From this atomicity
specification, a static analysis infers the atomicity constraints that are
local to each method, considering valid only the method variants that are
consistent with the specification, and performs code generation for all valid
variants of each method. The generated code is then the target for automatic
injection of concurrency control primitives, by means of the desired automatic
technique and associated atomicity and deadlock-freedom guarantees, which can
be plugged-into the model's pipeline. We present the foundations for the AtomiS
analysis and synthesis, with formal guarantees that the generated program is
well-typed and that it corresponds behaviourally to the original one. The
proofs are mechanised in Coq. We also provide a Java implementation that
showcases the applicability of AtomiS in real-life programs. |
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DOI: | 10.48550/arxiv.2309.05483 |