Towards better Heuristics for solving Bounded Model Checking Problems

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Abstract

This paper presents a new way to improve the performance of the SAT-based bounded model checking problem by exploiting relevant information identified through the characteristics of the original problem. This led us to design a new way of building interesting heuristics based on the structure of the underlying problem. The proposed methodology is generic and can be applied for any SAT problem. This paper compares the state-of-the-art approach with two new heuristics: Structure-based and Linear Programming heuristics and show promising results.

Documents

Bibtex (lrde.bib)

@InProceedings{	  kheireddine.21.cp,
  author	= {Anissa Kheireddine and \'Etienne Renault and Souheib
		  Baarrir},
  title		= {Towards better Heuristics for solving Bounded Model
		  Checking Problems},
  booktitle	= {Proceedings of the 27th International Conference on
		  Principles and Practice of Constraint Programmings (CP)},
  year		= {2021},
  month		= oct,
  abstract	= {This paper presents a new way to improve the performance
		  of the SAT-based bounded model checking problem by
		  exploiting relevant information identified through the
		  characteristics of the original problem. This led us to
		  design a new way of building interesting heuristics based
		  on the structure of the underlying problem. The proposed
		  methodology is generic and can be applied for any SAT
		  problem. This paper compares the state-of-the-art approach
		  with two new heuristics: Structure-based and Linear
		  Programming heuristics and show promising results.}
}