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We give a process for verifying numerical programs against their functional specifications. Our implementation is capable of automatically verifying programs against tight error bounds featuring common elementary functions. We demonstrate…

Logic in Computer Science · Computer Science 2022-07-05 Junaid Rasheed , Michal Konečný

In this note we study automata recognizing birecurrent sets. A set of words is birecurrent if the minimal partial DFA recognizing this set and the minimal partial DFA recognizing the reversal of this set are both strongly connected. This…

Formal Languages and Automata Theory · Computer Science 2017-11-10 Andrew Ryzhikov

This work considers weak deterministic B\"uchi automata reading encodings of non-negative reals in a fixed base. A Real Number Automaton is an automaton which recognizes all encoding of elements of a set of reals. It is explained how to…

Formal Languages and Automata Theory · Computer Science 2016-11-14 Arthur Milchior

Model checking invariant properties of designs, represented as transition systems, with non-linear real arithmetic (NRA), is an important though very hard problem. On the one hand NRA is a hard-to-solve theory; on the other hand most of the…

Logic in Computer Science · Computer Science 2018-01-29 Alessandro Cimatti , Alberto Griggio , Ahmed Irfan , Marco Roveri , Roberto Sebastiani

This paper presents a method for detecting mispronunciations with the aim of improving Computer Assisted Language Learning (CALL) tools used by foreign language learners. The algorithm is based on Principle Component Analysis (PCA). It is…

Sound · Computer Science 2016-02-29 Zhenhao Ge , Sudhendu R. Sharma , Mark J. T. Smith

We study the following problem: with the power of postselection (classically or quantumly), what is your ability to answer adaptive queries to certain languages? More specifically, for what kind of computational classes $\mathcal{C}$, we…

Computational Complexity · Computer Science 2016-10-17 Lijie Chen

We consider temporal logic verification of (possibly nonlinear) dynamical systems evolving over continuous state spaces. Our approach combines automata-based verification and the use of so-called barrier certificates. Automata-based…

Formal Languages and Automata Theory · Computer Science 2014-03-17 Tichakorn Wongpiromsarn , Ufuk Topcu , Andrew Lamperski

This paper presents a new static analysis for deriving upper bounds on the expected resource consumption of probabilistic programs. The analysis is fully automatic and derives symbolic bounds that are multivariate polynomials of the inputs.…

Programming Languages · Computer Science 2017-11-27 Van Chan Ngo , Quentin Carbonneaux , Jan Hoffmann

Bisimulation is crucial for verifying process equivalence in probabilistic systems. This paper presents a novel logical framework for analyzing bisimulation in probabilistic parameterized systems, namely, infinite families of finite-state…

Software Engineering · Computer Science 2025-05-16 Chih-Duo Hong , Anthony W. Lin , Philipp Rümmer , Rupak Majumdar

We introduce a notion of real-valued reward testing for probabilistic processes by extending the traditional nonnegative-reward testing with negative rewards. In this richer testing framework, the may and must preorders turn out to be…

Logic in Computer Science · Computer Science 2011-07-07 Yuxin Deng , Rob van Glabbeek , Matthew Hennessy , Carroll Morgan

This article introduces probabilistic disjunctive normal forms (PDNFs) as a framework for representing and reasoning about uncertainty in logical systems. Unlike classical DNFs, PDNFs assign real-valued weights to variables, encoding…

Logic in Computer Science · Computer Science 2026-03-13 Alexander Kuznetsov

Floating-point accumulation networks (FPANs) are key building blocks used in many floating-point algorithms, including compensated summation and double-double arithmetic. FPANs are notoriously difficult to analyze, and algorithms using…

Numerical Analysis · Mathematics 2025-05-27 David K. Zhang , Alex Aiken

In probabilistic grammatical inference, a usual goal is to infer a good approximation of an unknown distribution P called a stochastic language. The estimate of P stands in some class of probabilistic models such as probabilistic automata…

Machine Learning · Computer Science 2008-12-19 Amaury Habrard , Francois Denis , Yann Esposito

Pomset automata are an operational model of weak bi-Kleene algebra, which describes programs that can fork an execution into parallel threads, upon completion of which execution can join to resume as a single thread. We characterize a…

Formal Languages and Automata Theory · Computer Science 2023-06-22 Tobias Kappé , Paul Brunet , Bas Luttik , Alexandra Silva , Fabio Zanasi

We study the recursion-theoretic complexity of Positive Almost-Sure Termination ($\mathsf{PAST}$) in an imperative programming language with rational variables, bounded nondeterministic choice, and discrete probabilistic choice. A program…

Programming Languages · Computer Science 2023-10-30 Rupak Majumdar , V. R. Sathiyanarayana

We study alternating parity good-for-games (GFG) automata, i.e., alternating parity automata where both conjunctive and disjunctive choices can be resolved in an online manner, without knowledge of the suffix of the input word still to be…

Formal Languages and Automata Theory · Computer Science 2020-10-01 Udi Boker , Denis Kuperberg , Karoliina Lehtinen , Michał Skrzypczak

We realize the probabilistic cloning and identifying linear independent quantum states of multi-particles system, given prior probability, with universal quantum logic gates using the method of unitary representation. Our result is…

Quantum Physics · Physics 2007-05-23 Chuan-Wei Zhang , Chuan-Feng Li , Guang-Can Guo

In this paper the notion of quantum finite one-counter automata (QF1CA) is introduced. Introduction of the notion is similar to that of the 2-way quantum finite state automata by A.Kondacs and J.Watrous. The well-formedness conditions for…

Quantum Physics · Physics 2007-05-23 Maksim Kravtsev

Post-hoc explanations of machine learning models are crucial for people to understand and act on algorithmic predictions. An intriguing class of explanations is through counterfactuals, hypothetical examples that show people how to obtain a…

Machine Learning · Computer Science 2019-12-09 Ramaravind Kommiya Mothilal , Amit Sharma , Chenhao Tan

In this work, we introduce DeepDFA, a novel approach to identifying Deterministic Finite Automata (DFAs) from traces, harnessing a differentiable yet discrete model. Inspired by both the probabilistic relaxation of DFAs and Recurrent Neural…

Machine Learning · Computer Science 2024-08-19 Elena Umili , Roberto Capobianco