Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Boosting MCSes Enumeration
Authors: Éric Grégoire, Yacine Izza, Jean-Marie Lagniez
IJCAI 2018 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Then, we present our extensive experimental study. |
| Researcher Affiliation | Academia | Eric Gr egoire, Yacine Izza, Jean-Marie Lagniez CRIL Universit e d Artois & CNRS, Lens, France EMAIL |
| Pseudocode | Yes | Algorithm 1: Enum-ELS (Enumerate All MCSes Computed with the Extract Partial MCS procedure); Algorithm 2: TC-MCS ( Σ1 ΣS 2 , U ); Algorithm 3: Enum-ELS-RMR; |
| Open Source Code | Yes | All data, results and software used in the experimentations are available from http://www.cril.fr/enumcs. |
| Open Datasets | Yes | We have selected the 866 benchmarks used in [Previti et al., 2017; Marques-Silva et al., 2013]: 269 instances are plain Max-SAT ones and the remaining 597 are Partial Max-SAT ones. We have enriched this experimental setting by also considering a second series of plain Max-SAT benchmarks made of the instances from the MUS competition http://www.satcompetition.org/2011. |
| Dataset Splits | No | The paper refers to established benchmarks but does not provide explicit train/validation/test splits within these benchmarks in the text. |
| Hardware Specification | Yes | All experimentations have been conducted on Intel Xeon E5-2643 (3.30GHz) processors with 64Gb memory on Linux CentOS. |
| Software Dependencies | No | We have implemented all our algorithms in C++ and used Minisat http://minisat.se/ as backend SAT solver. No version number for Minisat is provided. |
| Experiment Setup | Yes | Time-out was set to 1800 seconds for each run of an algorithm on an instance; memory-out was set to 8 Gb for each such run. |