Towards Better Heuristics for Solving Bounded Model Checking Problems
From LRDE
- Authors
- Anissa Kheireddine, Étienne Renault, Souheib Baarir
- Journal
- Constraints
- Type
- article
- Publisher
- Springer
- Projects
- Spot
- Date
- 2022-12-09
Abstract
This paper presents a new way to improve the performance of the SAT-based bounded model checking problem on sequential and parallel procedures 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 approaches with two new heuristics for sequential procedures: Structure-based and Linear Programming heuristics. We extend these study and applied the above methodology on parallel approaches, especially to refine the sharing measure which shows promising results.
Documents
Bibtex (lrde.bib)
@Article{ kheireddine.22.constraints, author = {Anissa Kheireddine and \'Etienne Renault and Souheib Baarir}, title = {Towards Better Heuristics for Solving Bounded Model Checking Problems}, journal = {Constraints}, editor = {Mark Wallace}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, year = {2023}, pages = {45--66}, volume = {28}, publisher = {Springer}, month = mar, abstract = {This paper presents a new way to improve the performance of the SAT-based bounded model checking problem on sequential and parallel procedures 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 approaches with two new heuristics for sequential procedures: Structure-based and Linear Programming heuristics. We extend these study and applied the above methodology on parallel approaches, especially to refine the sharing measure which shows promising results.}, doi = {10.1007/s10601-022-09339-8}, note = {First published online on 27 December 2022.} }