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The goal of this lecture is to show how modern theorem provers---in this case, the Coq proof assistant---can be used to mechanize the specification of programming languages and their semantics, and to reason over individual programs and…

Programming Languages · Computer Science 2010-10-28 Xavier Leroy

What is called "numerical reproducibility" is the problem of getting the same result when the scientific computation is run several times, either on the same machine or on different machines, with different types and numbers of processing…

Numerical Analysis · Computer Science 2014-05-20 Nathalie Revol , Philippe Théveny

Most state-of-the-art branch-and-bound solvers for mixed-integer linear programming rely on limited-precision floating-point arithmetic and use numerical tolerances when reasoning about feasibility and optimality during their search. While…

Optimization and Control · Mathematics 2025-04-04 Alexander Hoen , Ambros Gleixner

This paper presents a proof system for reasoning about execution time bounds for a core imperative programming language. Proof systems are defined for three different scenarios: approximations of the worst-case execution time, exact time…

Programming Languages · Computer Science 2022-10-28 Ana Carolina Silva , Manuel Barbosa , Mario Florido

We describe a general and safe computational framework that provides integer programming results with the degree of certainty that is required for machine-assisted proofs of mathematical theorems. At its core, the framework relies on a…

Combinatorics · Mathematics 2020-09-22 Leon Eifler , Ambros Gleixner , Jonad Pulaj

Reliably determining system trajectories is essential in many analysis and control design approaches. To this end, an initial value problem has to be usually solved via numerical algorithms which rely on a certain software realization.…

Systems and Control · Electrical Eng. & Systems 2021-04-07 Grigory Devadze , Lars Flessing , Stefan Streif

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…

We propose a methodology for studying the performance of common splitting methods through semidefinite programming. We prove tightness of the methodology and demonstrate its value by presenting two applications of it. First, we use the…

Optimization and Control · Mathematics 2020-05-01 Ernest K. Ryu , Adrien B. Taylor , Carolina Bergeling , Pontus Giselsson

We present a new procedure to infer size bounds for integer programs automatically. Size bounds are important for the deduction of bounds on the runtime complexity or in general, for the resource analysis of programs. We show that our…

Logic in Computer Science · Computer Science 2024-11-19 Nils Lommen , Jürgen Giesl

What provides the highest level of assurance for correctness of execution within a programming language? One answer, and our solution in particular, to this problem is to provide a formalization for, if it exists, the denotational semantics…

Category Theory · Mathematics 2023-03-17 Zachary Flores , Angelo Taranto , Eric Bond , Yakir Forman

The Why3 IDE and verification system facilitates the use of a wide range of Satisfiability Modulo Theories (SMT) solvers through a driver-based architecture. We present Where4: a portfolio-based approach to discharge Why3 proof obligations.…

Software Engineering · Computer Science 2017-01-31 Andrew Healy , Rosemary Monahan , James F. Power

Deductive verification of concurrent programs under weak memory has thus far been limited to simple programs over a monolithic state space. For scalability, we also require modular techniques with verifiable library abstractions. This paper…

Logic in Computer Science · Computer Science 2021-08-21 Sadegh Dalvandi , Brijesh Dongol

Interactive proof assistants are computer programs carefully constructed to check a human-designed proof of a mathematical claim with high confidence in the implementation. However, this only validates truth of a formal claim, which may…

Programming Languages · Computer Science 2023-10-09 Colin S. Gordon , Sergey Matskevich

The estimation of covariance operators of spatio-temporal data is in many applications only computationally feasible under simplifying assumptions, such as separability of the covariance into strictly temporal and spatial factors.Powerful…

Statistics Theory · Mathematics 2020-03-30 Holger Dette , Gauthier Dierickx , Tim Kutta

Symbolic regression via genetic programming is a flexible approach to machine learning that does not require up-front specification of model structure. However, traditional approaches to symbolic regression require the use of protected…

Neural and Evolutionary Computing · Computer Science 2017-04-18 Grant Dick

Recently, researchers have been working toward the development of practical general-purpose protocols for verifiable computation. These protocols enable a computationally weak verifier to offload computations to a powerful but untrusted…

Cryptography and Security · Computer Science 2017-02-09 Justin Thaler

Interval linear programming provides a tool for solving real-world optimization problems under interval-valued uncertainty. Instead of approximating or estimating crisp input data, the coefficients of an interval program may perturb…

Optimization and Control · Mathematics 2025-10-08 Elif Garajová , Milan Hladík , Miroslav Rada

Modern separation logics allow one to prove rich properties of intricate code, e.g. functional correctness and linearizability of non-blocking concurrent code. However, this expressiveness leads to a complexity that makes these logics…

Programming Languages · Computer Science 2021-08-16 Felix A. Wolf , Malte Schwerhoff , Peter Müller

Verification of numerical accuracy properties in modern software remains an important and challenging task. This paper describes an original framework combining different solutions for numerical accuracy. First, we extend an existing…

Software Engineering · Computer Science 2019-11-26 Maxime Jacquemin , Fonenantsoa Maurica , Nikolai Kosmatov , Julien Signoles , Franck Védrine

Quantization replaces floating point arithmetic with integer arithmetic in deep neural network models, providing more efficient on-device inference with less power and memory. In this work, we propose a framework for formally verifying…

Machine Learning · Computer Science 2023-12-29 Pei Huang , Haoze Wu , Yuting Yang , Ieva Daukantas , Min Wu , Yedi Zhang , Clark Barrett
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