Generating Concurrent Programs From Sequential Data Structure Knowledge Using Answer Set Programming

Sarat Chandra Varanasi
(The University of Texas at Dallas)
Neeraj Mittal
(The University of Texas at Dallas)
Gopal Gupta
(The University of Texas at Dallas)

We tackle the problem of automatically designing concurrent data structure operations given a sequential data structure specification and knowledge about concurrent behavior. Designing concurrent code is a non-trivial task even in simplest of cases. Humans often design concurrent data structure operations by transforming sequential versions into their respective concurrent versions. This requires an understanding of the data structure, its sequential behavior, thread interactions during concurrent execution and shared memory synchronization primitives. We mechanize this design process using automated commonsense reasoning. We assume that the data structure description is provided as axioms alongside the sequential code of its algebraic operations. This information is used to automatically derive concurrent code for that data structure, such as dictionary operations for linked lists and binary search trees. Knowledge in our case is expressed using Answer Set Programming (ASP), and we employ deduction and abduction—just as humans do—in the reasoning involved. ASP allows for succinct modeling of first order theories of pointer data structures, run-time thread interactions and shared memory synchronization. Our reasoner can systematically make the same judgments as a human reasoner, while constructing provably safe concurrent code. We present several reasoning challenges involved in transforming the sequential data structure into its equivalent concurrent version. All the reasoning tasks are encoded in ASP and our reasoner can make sound judgments to transform sequential code into concurrent code. To the best of our knowledge, our work is the first one to use commonsense reasoning to automatically transform sequential programs into concurrent code. We also have developed a tool that we describe that relies on state-of-the-art ASP solvers and performs the reasoning tasks involved to generate concurrent code.

In Andrea Formisano, Yanhong Annie Liu, Bart Bogaerts, Alex Brik, Veronica Dahl, Carmine Dodaro, Paul Fodor, Gian Luca Pozzato, Joost Vennekens and Neng-Fa Zhou: Proceedings 37th International Conference on Logic Programming (Technical Communications) (ICLP 2021), Porto (virtual event), 20-27th September 2021, Electronic Proceedings in Theoretical Computer Science 345, pp. 219–233.
Published: 17th September 2021.

ArXived at: bibtex PDF

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