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Type and effect systems are a tool to analyse statically the behaviour of programs with effects. We present a proof based on the so called reducibility candidates that a suitable stratification of the type and effect system entails the…

Logic in Computer Science · Computer Science 2010-07-01 Roberto Amadio

The generation of comprehensible explanations is an essential feature of modern artificial intelligence systems. In this work, we consider probabilistic logic programming, an extension of logic programming which can be useful to model…

Artificial Intelligence · Computer Science 2023-08-17 Germán Vidal

In this paper, we consider an approach introduced in term rewriting for the automatic detection of non-looping non-termination from patterns of rules. We adapt it to logic programming by defining a new unfolding technique that produces…

Logic in Computer Science · Computer Science 2026-01-14 Etienne Payet

While a mature body of work supports the study of rewriting systems, abstract tools for Probabilistic Rewriting are still limited. In this paper we study the question of uniqueness of the result (unique limit distribution), and develop a…

Logic in Computer Science · Computer Science 2023-06-22 Claudia Faggian

The avoidability, or unavoidability of patterns in words over finite alphabets has been studied extensively. A word (pattern) over a finite set is said to be unavoidable if, for all but finitely many words, there exists a morphism mapping…

Formal Languages and Automata Theory · Computer Science 2019-07-16 Paul Sauer

We study the question of whether the "termination with probability 1" property of a randomized algorithm is preserved when one replaces the atomic registers that the algorithm uses with linearizable (implementations of) registers. We show…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-30 Vassos Hadzilacos , Xing Hu , Sam Toueg

The paper explores known results related to the problem of identifying if a given program terminates on all inputs -- this is a simple generalization of the halting problem. We will see how this problem is related and the notion of proof…

Computational Complexity · Computer Science 2012-03-02 Rina Panigrahy

Many probabilistic programming languages allow programs to be run under constraints in order to carry out Bayesian inference. Running programs under constraints could enable other uses such as rare event simulation and probabilistic…

Programming Languages · Computer Science 2015-01-19 Neil Toronto , Jay McCarthy , David Van Horn

Existing decision-theoretic reasoning frameworks such as decision networks use simple data structures and processes. However, decisions are often made based on complex data structures, such as social networks and protein sequences, and rich…

Artificial Intelligence · Computer Science 2014-07-14 Brian E. Ruttenberg , Avi Pfeffer

This paper shows that a variety of software model-checking algorithms can be seen as proof-search strategies for a non-standard proof system, known as a cyclic proof system. Our use of the cyclic proof system as a logical foundation of…

Programming Languages · Computer Science 2021-11-11 Takeshi Tsukada , Hiroshi Unno

In this paper we consider a fragment of the first-order theory of the real numbers that includes systems of equations of continuous functions in bounded domains, and for which all functions are computable in the sense that it is possible to…

Computational Complexity · Computer Science 2016-08-15 Peter Franek , Stefan Ratschan , Piotr Zgliczynski

This paper focuses on the inference of modes for which a logic program is guaranteed to terminate. This generalises traditional termination analysis where an analyser tries to verify termination for a specified mode. Our contribution is a…

Programming Languages · Computer Science 2007-05-23 Samir Genaim , Michael Codish

A hypothesis testing algorithm is replicable if, when run on two different samples from the same distribution, it produces the same output with high probability. This notion, defined by by Impagliazzo, Lei, Pitassi, and Sorell [STOC'22],…

Data Structures and Algorithms · Computer Science 2025-09-05 Anders Aamand , Maryam Aliakbarpour , Justin Y. Chen , Shyam Narayanan , Sandeep Silwal

We propose trace abstraction modulo probability, a proof technique for verifying high-probability accuracy guarantees of probabilistic programs. Our proofs overapproximate the set of program traces using failure automata, finite-state…

Programming Languages · Computer Science 2018-10-31 Calvin Smith , Justin Hsu , Aws Albarghouthi

It is becoming increasingly apparent that probabilistic approaches can overcome conservatism and computational complexity of the classical worst-case deterministic framework and may lead to designs that are actually safer. In this paper we…

Applications · Statistics 2008-11-01 Xinjia Chen , Kemin Zhou , Jorge L. Aravena

Programs for multiprocessor machines commonly perform busy-waiting for synchronisation. In this paper, we make a first step towards proving termination of such programs. We approximate (i) arbitrary waitable events by abrupt program…

Logic in Computer Science · Computer Science 2020-10-19 Tobias Reinhard , Amin Timany , Bart Jacobs

We establish fundamental and general techniques for formal verification of quantum protocols. Quantum protocols are novel communication schemes involving the use of quantum-mechanical phenomena for representation, storage and transmission…

Quantum Physics · Physics 2007-05-23 Simon Gay , Rajagopal Nagarajan , Nikolaos Papanikolaou

Programs for multiprocessor machines commonly perform busy-waiting for synchronisation. In this paper, we make a first step towards proving termination of such programs. We approximate (i) arbitrary waitable events by abrupt program…

Logic in Computer Science · Computer Science 2020-07-22 Tobias Reinhard , Amin Timany , Bart Jacobs

Computer programs may go wrong due to exceptional behaviors, out-of-bound array accesses, or simply coding errors. Thus, they cannot be blindly trusted. Scientific computing programs make no exception in that respect, and even bring…

Probabilistic programming combines general computer programming, statistical inference, and formal semantics to help systems make decisions when facing uncertainty. Probabilistic programs are ubiquitous, including having a significant…

Logic in Computer Science · Computer Science 2024-09-30 Kangfeng Ye , Jim Woodcock , Simon Foster