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Denotational Semantics for Probabilistic and Concurrent Programs

Published: March 4, 2025 | arXiv ID: 2503.02768v2

By: Noam Zilberstein, Daniele Gorla, Alexandra Silva

Potential Business Impact:

Helps computers understand tricky programs with choices and speed.

Business Areas:
Natural Language Processing Artificial Intelligence, Data and Analytics, Software

We develop a denotational model for probabilistic and concurrent imperative programs, a class of programs with standard control flow via conditionals and while-loops, as well as probabilistic actions and parallel composition. Whereas semantics for concurrent or randomized programs in isolation is well studied, their combination has not been thoroughly explored and presents unique challenges. The crux of the problem is that interactions between control flow, probabilistic actions, and concurrent execution cannot be captured by straightforward generalizations of prior work on pomsets and convex languages, prominent models for those effects, individually. Our model has good domain theoretic properties, important for semantics of unbounded loops. We also prove two adequacy theorems, showing that the model subsumes typical powerdomain semantics for concurrency and convex powerdomain semantics for probabilistic nondeterminism.

Page Count
65 pages

Category
Computer Science:
Programming Languages