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Large language models (LLMs) have shown remarkable ability to generate code, yet their outputs often violate syntactic or semantic constraints when guided only through natural language prompts. We introduce TreeCoder, the most general and…

Machine Learning · Computer Science 2026-04-27 Henrijs Princis , Arindam Sharma , Cristina David

Code translation is a crucial activity in the software development and maintenance process, and researchers have recently begun to focus on using pre-trained large language models (LLMs) for code translation. However, existing LLMs only…

Software Engineering · Computer Science 2025-09-30 Minghua He , Yue Chen , Fangkai Yang , Pu Zhao , Wenjie Yin , Yu Kang , Qingwei Lin , Saravan Rajmohan , Dongmei Zhang

Many of the famous single-player games, commonly called puzzles, can be shown to be NP-Complete. Indeed, this class of complexity contains hundreds of puzzles, since people particularly appreciate completing an intractable puzzle, such as…

Artificial Intelligence · Computer Science 2019-07-02 Cédric Piette , Éric Piette , Matthew Stephenson , Dennis J. N. J. Soemers , Cameron Browne

Researchers in answer set programming and constraint programming have spent significant efforts in the development of hybrid languages and solving algorithms combining the strengths of these traditionally separate fields. These efforts…

Artificial Intelligence · Computer Science 2017-12-04 Marcello Balduccini , Yuliya Lierler

This paper presents an overview of the functionalities and applications of Exasim, an open-source code for generating high-order discontinuous Galerkin codes to numerically solve parametrized partial differential equations (PDEs). The…

Mathematical Software · Computer Science 2022-05-17 Jordi Vila-Pérez , R. Loek Van Heyningen , Ngoc-Cuong Nguyen , Jaume Peraire

Graph-structured data is central to many scientific and industrial domains, where the goal is often to optimize objectives defined over graph structures. Given the combinatorial complexity of graph spaces, such optimization problems are…

Optimization and Control · Mathematics 2025-09-25 Shiqiang Zhang , Ruth Misener

Self-Supervised Learning (SSL) for Combinatorial Optimization (CO) is an emerging paradigm for solving combinatorial problems using neural networks. In this paper, we address a central challenge of SSL for CO: solving problems with discrete…

Machine Learning · Computer Science 2026-01-16 Nikolaos Karalias , Akbar Rafiey , Yifei Xu , Zhishang Luo , Behrooz Tahmasebi , Connie Jiang , Stefanie Jegelka

Constraint Satisfaction Problems (CSPs) typically have many solutions that satisfy all constraints. Often though, some solutions are preferred over others, that is, some solutions dominate other solutions. We present solution dominance as a…

Artificial Intelligence · Computer Science 2018-12-24 Tias Guns , Peter J. Stuckey , Guido Tack

Due to their importance in practice, dominating set problems in graphs have been greatly studied in past and different formulations of these problems are presented in literature. This paper's focus is on two problems: weakly convex…

Optimization and Control · Mathematics 2019-04-05 Jozef Kratica , Vladimir Filipovic , Dragan Matic , Aleksandar Kartelj

Structural decomposition methods, such as generalized hypertree decompositions, have been successfully used for solving constraint satisfaction problems (CSPs). As decompositions can be reused to solve CSPs with the same constraint scopes,…

Artificial Intelligence · Computer Science 2022-09-22 Georg Gottlob , Matthias Lanzinger , Davide Mario Longo , Cem Okulmus

Many constraint satisfaction and optimisation problems can be solved effectively by encoding them as instances of the Boolean Satisfiability problem (SAT). However, even the simplest types of constraints have many encodings in the…

Artificial Intelligence · Computer Science 2023-11-09 Felix Ulrich-Oltean , Peter Nightingale , James Alfred Walker

We study the design of stochastic local search methods to prove unsatisfiability of a constraint satisfaction problem (CSP). For a binary CSP, such methods have been designed using the microstructure of the CSP. Here, we develop a method to…

Artificial Intelligence · Computer Science 2020-02-11 Daya Gaur , Muhammad Khan

Constraint satisfaction problems (CSPs) consist of a set of variables taking values from some finite domain and a set of local constraints on these variables. The objective is to find an assignment to the variables that maximizes the…

Computational Complexity · Computer Science 2026-05-12 Amey Bhangale , Yezhou Zhang

Developing software to effectively take advantage of growth in parallel and distributed processing capacity poses significant challenges. Traditional programming techniques allow a user to assume that execution, message passing, and memory…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-05-24 Matthew Andres Moreno , Santiago Rodriguez Papa , Charles Ofria

Sparsity constrained minimization captures a wide spectrum of applications in both machine learning and signal processing. This class of problems is difficult to solve since it is NP-hard and existing solutions are primarily based on…

Optimization and Control · Mathematics 2018-12-31 Ganzhao Yuan , Bernard Ghanem

We study the secure decentralized Pliable Index CODing (PICOD) problem with circular side information sets at the users. The security constraint forbids every user to decode more than one message while a decentralized setting means there is…

Information Theory · Computer Science 2020-10-21 Tang Liu , Daniela Tuninetti

The paper presents an algebraic framework for optimization problems expressible as Valued Constraint Satisfaction Problems. Our results generalize the algebraic framework for the decision version (CSPs) provided by Bulatov et al. [SICOMP…

Computational Complexity · Computer Science 2016-05-03 Marcin Kozik , Joanna Ochremiak

In this paper we present a simple source code configuration tool. ExLibris operates on libraries and can be used to extract from local libraries all code relevant to a particular project. Our approach is not designed to address problems…

Software Engineering · Computer Science 2007-05-23 Nicos Angelopoulos

In eXplainable Constraint Solving (XCS), it is common to extract a Minimal Unsatisfiable Subset (MUS) from a set of unsatisfiable constraints. This helps explain to a user why a constraint specification does not admit a solution. Finding…

Artificial Intelligence · Computer Science 2024-12-19 Ignace Bleukx , Hélène Verhaeghe , Bart Bogaerts , Tias Guns

The eXtensible Markup Language (XML) provides a powerful and flexible means of encoding and exchanging data. As it turns out, its main advantage as an encoding format (namely, its requirement that all open and close markup tags are present…

Databases · Computer Science 2015-05-13 Gregory Leighton , Denilson Barbosa