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 [1].

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๏ฌcient dom/wdeg to avoid severe interference between the heuristic and propagation.