Logic Programming for Orthogonal Graph Drawing on Restricted Grids

This paper investigates the use of logic programming—specifically, Answer Set Programming (ASP)—as a declarative approach to orthogonal graph drawing on restricted grids. The drawing problem is encoded as a constraint satisfaction problem that enforces planarity, orthogonality, and spatial constraints within bounded integer grids. Experimental results on benchmark graphs indicate that the approach generates valid and aesthetically pleasing layouts, particularly for small and medium-sized instances. These findings demonstrate the promise of declarative programming in supporting constraint-driven graph layout methodologies.

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Publication Details

Journal
Procedia Computer Science
Published
2025-01-01
DOI
https://doi.org/10.1016/j.procs.2025.09.353
Primary Topic
Logic, Reasoning, and Knowledge
Type
article
Field-Weighted Citation Impact
0.00
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article

Logic Programming for Orthogonal Graph Drawing on Restricted Grids

Wojciech Wieczorek, Arkadiusz Nowakowski, Łukasz Strąk
Procedia Computer Science
Logic, Reasoning, and Knowledge
article

Logic Programming for Orthogonal Graph Drawing on Restricted Grids

Wojciech Wieczorek, Arkadiusz Nowakowski, Łukasz Strąk
article en

Abstract

This paper investigates the use of logic programming—specifically, Answer Set Programming (ASP)—as a declarative approach to orthogonal graph drawing on restricted grids. The drawing problem is encoded as a constraint satisfaction problem that enforces planarity, orthogonality, and spatial constraints within bounded integer grids. Experimental results on benchmark graphs indicate that the approach generates valid and aesthetically pleasing layouts, particularly for small and medium-sized instances. These findings demonstrate the promise of declarative programming in supporting constraint-driven graph layout methodologies.

Procedia Computer ScienceVol. 270
University of Bielsko-Biała (PL), University of Silesia in Katowice (PL)
Openalex Percentile: Top 83%
Logic, Reasoning, and Knowledge
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