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..
A Modularity-Based Random SAT Instances Generator
Authors: Jesús Giráldez-Cru, Jordi Levy
IJCAI 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We evaluate the adequacy of this model to real industrial problems in terms of SAT solvers performance, and show that modern solvers do actually exploit this community structure. |
| Researcher Affiliation | Academia | Jes us Gir aldez-Cru and Jordi Levy IIIA CSIC Campus UAB, Bellaterra, Spain |
| Pseudocode | Yes | Algorithm 1: Community Attachment |
| Open Source Code | Yes | This modularity-based SAT generator is available in http://www.iiia.csic.es/ jgiraldez/software |
| Open Datasets | No | The paper generates its own random SAT instances for evaluation using the described model. It does not use a pre-existing publicly available dataset for training or evaluation. |
| Dataset Splits | No | The paper generates random instances based on specified parameters (n, m/n, Q, c) and then evaluates them. It does not describe standard training, validation, or test splits of a fixed dataset. |
| Hardware Specification | No | The paper mentions the use of SAT solvers (MiniSat, Glucose, March) but does not provide any specific details about the hardware (CPU, GPU, RAM) used for running the experiments. |
| Software Dependencies | No | The paper mentions specific SAT solvers used (Mini Sat, Glucose, March) and an algorithm from a prior work, but it does not specify version numbers for these software components, which is required for reproducibility. |
| Experiment Setup | Yes | We have generated some sets of random formulas for different values of Q {0.9, 0.8, 0.7, 0.5, 0.3} (hence P = Q + 1/c). ... The input number of communities c is fixed to 40. ... The timeout is set to 3 hours. |