Difference between revisions of "Publications/kheireddine.21.cp"
From LRDE
(Created page with "{{Publication | published = true | date = 2021-08-31 | authors = Anissa kheireddine, Etienne Renault, Souheib Baarrir | title = Towards better Heuristics for solving Bounded M...") |
|||
Line 2: | Line 2: | ||
| published = true |
| published = true |
||
| date = 2021-08-31 |
| date = 2021-08-31 |
||
− | | authors = Anissa |
+ | | authors = Anissa Kheireddine, Étienne Renault, Souheib Baarrir |
| title = Towards better Heuristics for solving Bounded Model Checking Problems |
| 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 |
+ | | booktitle = Proceedings of the 27th International Conference on Principles and Practice of Constraint Programmings (CP) |
− | | series = ?? |
||
− | | publisher = ?? |
||
− | | volume = ?? |
||
− | | pages = ?? |
||
| 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. |
| 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. |
||
| lrdeprojects = Spot |
| lrdeprojects = Spot |
||
Line 15: | Line 11: | ||
| type = inproceedings |
| type = inproceedings |
||
| id = kheireddine.21.cp |
| id = kheireddine.21.cp |
||
− | | identifier = doi:?? |
||
| bibtex = |
| bibtex = |
||
@InProceedings<nowiki>{</nowiki> kheireddine.21.cp, |
@InProceedings<nowiki>{</nowiki> kheireddine.21.cp, |
||
− | author = <nowiki>{</nowiki>Anissa |
+ | author = <nowiki>{</nowiki>Anissa Kheireddine and \'Etienne Renault and Souheib |
Baarrir<nowiki>}</nowiki>, |
Baarrir<nowiki>}</nowiki>, |
||
title = <nowiki>{</nowiki>Towards better Heuristics for solving Bounded Model |
title = <nowiki>{</nowiki>Towards better Heuristics for solving Bounded Model |
||
Checking Problems<nowiki>}</nowiki>, |
Checking Problems<nowiki>}</nowiki>, |
||
booktitle = <nowiki>{</nowiki>Proceedings of the 27th International Conference on |
booktitle = <nowiki>{</nowiki>Proceedings of the 27th International Conference on |
||
− | Principles and Practice of Constraint Programmings |
+ | Principles and Practice of Constraint Programmings (CP)<nowiki>}</nowiki>, |
− | (CP'21)<nowiki>}</nowiki>, |
||
− | series = <nowiki>{</nowiki>??<nowiki>}</nowiki>, |
||
− | publisher = <nowiki>{</nowiki>??<nowiki>}</nowiki>, |
||
− | volume = <nowiki>{</nowiki>??<nowiki>}</nowiki>, |
||
− | pages = <nowiki>{</nowiki>??<nowiki>}</nowiki>, |
||
year = <nowiki>{</nowiki>2021<nowiki>}</nowiki>, |
year = <nowiki>{</nowiki>2021<nowiki>}</nowiki>, |
||
month = oct, |
month = oct, |
||
− | abstract = <nowiki>{</nowiki> |
+ | abstract = <nowiki>{</nowiki>This paper presents a new way to improve the performance |
of the SAT-based bounded model checking problem by |
of the SAT-based bounded model checking problem by |
||
exploiting relevant information identified through the |
exploiting relevant information identified through the |
||
Line 40: | Line 30: | ||
problem. This paper compares the state-of-the-art approach |
problem. This paper compares the state-of-the-art approach |
||
with two new heuristics: Structure-based and Linear |
with two new heuristics: Structure-based and Linear |
||
− | Programming heuristics and show promising results.<nowiki>}</nowiki> |
+ | Programming heuristics and show promising results.<nowiki>}</nowiki> |
− | doi = <nowiki>{</nowiki>??<nowiki>}</nowiki> |
||
<nowiki>}</nowiki> |
<nowiki>}</nowiki> |
||
Revision as of 10:56, 8 September 2021
- Authors
- Anissa Kheireddine, Étienne Renault, Souheib Baarrir
- Where
- Proceedings of the 27th International Conference on Principles and Practice of Constraint Programmings (CP)
- Type
- inproceedings
- Projects
- Spot
- Date
- 2021-08-31
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.} }