Denotational Semantics for Probabilistic and Concurrent Programs
By: Noam Zilberstein, Daniele Gorla, Alexandra Silva
Potential Business Impact:
Helps computers understand tricky programs with choices and speed.
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.
Similar Papers
Integrating Belief Domains into Probabilistic Logic Programs
Logic in Computer Science
Lets computers understand when they are unsure.
A Probabilistic Choreography Language for PRISM
Logic in Computer Science
Checks computer programs for mistakes automatically.
An Adequate While-Language for Stochastic Hybrid Computation
Logic in Computer Science
Helps computers understand how things move and change.