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Proceedings of the ACM on Programming Languages
Article . 2024 . Peer-reviewed
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Positive Almost-Sure Termination: Complexity and Proof Rules

Authors: Rupak Majumdar; V. R. Sathiyanarayana;

Positive Almost-Sure Termination: Complexity and Proof Rules

Abstract

We study the recursion-theoretic complexity of Positive Almost-Sure Termination (PAST) in an imperative programming language with rational variables, bounded nondeterministic choice, and discrete probabilistic choice. A program terminates positive almost-surely if, for every scheduler, the program terminates almost-surely and the expected runtime to termination is finite. We show that PAST for our language is complete for the (lightface) co-analytic sets ( Π 1 1 -complete). This is in contrast to the related notions of Almost-Sure Termination (AST) and Bounded Termination (BAST), both of which are arithmetical ( Π 2 0 - and Σ 2 0 -complete respectively). Our upper bound implies an effective procedure to reduce reasoning about probabilistic termination to non-probabilistic fair termination in a model with bounded nondeterminism, and to simple program termination in models with unbounded nondeterminism. Our lower bound shows the opposite: for every program with unbounded nondeterministic choice, there is an effectively computable probabilistic program with bounded choice such that the original program is terminating if, and only if, the transformed program is PAST. We show that every program has an effectively computable normal form, in which each probabilistic choice either continues or terminates execution immediately, each with probability 1 / 2 . For normal form programs, we provide a sound and complete proof rule for PAST. Our proof rule uses transfinite ordinals. We show that reasoning about PAST requires transfinite ordinals up to ω 1 CK ; thus, existing techniques for probabilistic termination based on ranking supermartingales that map program states to reals do not suffice to reason about PAST.

Keywords

FOS: Computer and information sciences, Computer Science - Computational Complexity, Computer Science - Programming Languages, Computational Complexity (cs.CC), Programming Languages (cs.PL)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Average
Top 10%
Green
Published in a Diamond OA journal