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This work introduces (1) a technique that allows large language models (LLMs) to leverage user-provided code when solving programming tasks and (2) a method to iteratively generate modular sub-functions that can aid future code generation…

Machine Learning · Computer Science 2023-12-05 Patrick Hajali , Ignas Budvytis

In this paper, we identify a fragment of second-order logic with restricted quantification that is expressive enough to capture numerous static analysis problems (e.g. safety proving, bug finding, termination and non-termination proving,…

Logic in Computer Science · Computer Science 2015-09-01 Cristina David , Daniel Kroening , Matt Lewis

This paper contributes to the mathematical foundations of logic programming by introducing and studying the sequential composition of answer set programs. On the semantic side, we show that the immediate consequence operator of a program…

Artificial Intelligence · Computer Science 2024-06-13 Christian Antić

We consider the problem of synthesizing provably non-overflowing integer arithmetic expressions or Boolean relations among integer arithmetic expressions. First we use a numerical abstract domain to infer numerical properties among program…

Programming Languages · Computer Science 2013-09-23 Francesco Logozzo , Matthieu Martel

We introduce the notion of porous invariants for multipath (or branching/nondeterministic) affine loops over the integers; these invariants are not necessarily convex, and can in fact contain infinitely many 'holes'. Nevertheless, we show…

Logic in Computer Science · Computer Science 2021-06-02 Engel Lefaucheux , Joël Ouaknine , David Purser , James Worrell

Increasing demands in software industry and scarcity of software engineers motivates researchers and practitioners to automate the process of software generation and configuration. Large scale automatic software generation and configuration…

Software Engineering · Computer Science 2023-05-31 Shantanu Mandal

Program synthesis is the generation of a program from a specification. Correct synthesis is difficult, and methods that provide formal guarantees suffer from scalability issues. On the other hand, neural networks are able to generate…

Logic in Computer Science · Computer Science 2020-01-28 Elizabeth Polgreen , Ralph Abboud , Daniel Kroening

The automatic generation of computer programs is one of the main applications with practical relevance in the field of evolutionary computation. With program synthesis techniques not only software developers could be supported in their…

Neural and Evolutionary Computing · Computer Science 2021-08-30 Dominik Sobania , Dirk Schweim , Franz Rothlauf

We survey and unify recent results on the existence of accurate algorithms for evaluating multivariate polynomials, and more generally for accurate numerical linear algebra with structured matrices. By "accurate" we mean that the computed…

Numerical Analysis · Mathematics 2008-05-21 James Demmel , Ioana Dumitriu , Olga Holtz , Plamen Koev

The rise of large language models (LLMs) has sparked interest in coding assistants. While general-purpose programming languages are well supported, generating code for domain-specific languages remains a challenging problem for LLMs. In…

Artificial Intelligence · Computer Science 2025-12-22 Timo Pierre Schrader , Lukas Lange , Tobias Kaminski , Simon Razniewski , Annemarie Friedrich

This paper describes a way to improve the scalability of program synthesis by exploiting modularity: larger programs are synthesized from smaller programs. The key issue is to make each "larger-created-from-smaller" synthesis sub-problem be…

Programming Languages · Computer Science 2023-08-15 Kanghee Park , Keith J. C. Johnson , Loris D'Antoni , Thomas Reps

We consider each of the three classes of representations of cyclic groups that arise in the study of rational sphere maps. We study the possible number of terms for invariant polynomials with non-negative coefficients that are constant on…

Complex Variables · Mathematics 2025-12-08 John P. D'Angelo , Dusty E. Grundmeier , Daniel A. Lichtblau

We present our public-domain software for the following tasks in sparse (or toric) elimination theory, given a well-constrained polynomial system. First, C code for computing the mixed volume of the system. Second, Maple code for defining…

Mathematical Software · Computer Science 2014-03-06 Ioannis Z. Emiris

This work introduces a controller synthesis method via system level synthesis for nonlinear systems characterized by polynomial dynamics. The resulting framework yields finite impulse response, time-invariant, closed-loop transfer functions…

Optimization and Control · Mathematics 2022-09-26 Lauren Conger , Jing Shuang Li , Eric Mazumdar , Steven L. Brunton

In recent years, deep learning techniques have been developed to improve the performance of program synthesis from input-output examples. Albeit its significant progress, the programs that can be synthesized by state-of-the-art approaches…

Machine Learning · Computer Science 2018-03-09 Xinyun Chen , Chang Liu , Dawn Song

We present a new domain-agnostic synthesis technique for generating programs from input-output examples. Our method, called metric program synthesis, relaxes the well-known observational equivalence idea (used widely in bottom-up…

Programming Languages · Computer Science 2022-10-12 John Feser , Isil Dillig , Armando Solar-Lezama

Automatic parallelization remains a challenging problem in software engineering, particularly in identifying code regions where loops can be safely executed in parallel on modern multi-core architectures. Traditional static analysis…

Software Engineering · Computer Science 2026-04-01 Izavan dos S. Correia , Henrique C. T. Santos , Tiago A. E. Ferreira

This article presents resource-guided synthesis, a technique for synthesizing recursive programs that satisfy both a functional specification and a symbolic resource bound. The technique is type-directed and rests upon a novel type system…

Programming Languages · Computer Science 2019-04-19 Tristan Knoth , Di Wang , Nadia Polikarpova , Jan Hoffmann

A program invariant is a property that holds for every execution of the program. Recent work suggest to infer likely-only invariants, via dynamic analysis. A likely invariant is a property that holds for some executions but is not…

Software Engineering · Computer Science 2007-05-23 Tristan Denmat , Arnaud Gotlieb , Mireille Ducasse

Template abstract domains allow to express more interesting properties than classical abstract domains. However, template generation is a challenging problem when one uses template abstract domains for program analysis. In this paper, we…

Logic in Computer Science · Computer Science 2014-10-21 Assalé Adjé , Victor Magron