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..
On Neighborhood Singleton Consistencies
Authors: Anastasia Paparrizou, Kostas Stergiou
IJCAI 2017 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We make a detailed experimental study using a very simple algorithm for their implementation. Results demonstrate that they outperform the existing propagation techniques, often by orders of magnitude, on a wide range of problems. Finally, we make an experimental evaluation of all the considered methods. |
| Researcher Affiliation | Academia | Anastasia Paparrizou CRIL-CNRS and Universit e d Artois Lens, France EMAIL Kostas Stergiou University of Western Macedonia Kozani, Greece EMAIL |
| Pseudocode | Yes | Algorithm 1 The RNSQ algorithm |
| Open Source Code | No | The paper does not provide any statement about releasing source code for the methodology or a link to a code repository. |
| Open Datasets | Yes | We experimented with 16 classes of binary CSPs taken from C.Lecoutre s XCSP repository: rlfap, graph coloring, qcp, qwh, bqwh, driver, haystacks, hanoi, pigeons, black hole, ehi, queens, queens Attacking, queens Knights, geometric, composed. |
| Dataset Splits | No | The paper does not specify training, validation, or test dataset splits (e.g., percentages or sample counts), nor does it mention cross-validation. CSP problems are typically solved directly, not trained like machine learning models. |
| Hardware Specification | Yes | The experiments were performed on a FUJITSU Server (2.90GHz, 48 GB RAM, 16MB cache). |
| Software Dependencies | No | The paper mentions implementing baseline methods using "the corresponding state-of-the-art algorithms [Lecoutre and Hemery, 2007; Balafoutis et al., 2011; Stergiou, 2015]" and discusses AC-3, but it does not specify any software names with version numbers (e.g., specific solver versions, programming language versions, or library versions). |
| Experiment Setup | Yes | We mainly used dom/ddeg instead of the more ef๏ฌcient dom/wdeg to avoid severe interference between the heuristic and propagation. |