Solving QBF by Clause Selection

Authors: Mikolas Janota, Joao Marques-Silva

IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental Experimental results, obtained on representative problem instances, show that the novel algorithm is competitive with, and often outperforms, the state of the art in QBF solving.
Researcher Affiliation Academia Mikol aˇs Janota1 and Joao Marques-Silva1,2 1 INESC-ID, IST, Lisbon, Portugal 2 University College Dublin, Ireland
Pseudocode Yes Algorithm 1: Two-level Selection QCNF Solving
Open Source Code No The paper states 'More detailed presentation of the results can be found on the authors website3. 3http://sat.inesc-id.pt/%7Emikolas/sw/qesto/', which points to results, but does not explicitly state that source code for the methodology is available at this link or elsewhere.
Open Datasets Yes For the evaluation we used the QBFLIB benchmark suite used in the 2014 QBF Gallery2 and the benchmarks from the 2QBF track of the 2010 QBF Evaluation. 2http://www.kr.tuwien.ac.at/events/qbfgallery2013/benchmarks/eval2012r2.tar.7z
Dataset Splits No The paper mentions using benchmark suites but does not specify any training, validation, or test dataset splits or how the data was partitioned for experiments.
Hardware Specification Yes The experimental results were carried out on Linux machines with Intel Xeon 5160 3GHz processors and 4GB of memory.
Software Dependencies Yes The prototype used for the evaluation was implemented in C++ and the SAT solver minisat 2.2 [E en and S orensson, 2003a] was used.
Experiment Setup No The paper states 'The time limit was set to 800 s and the memory limit to 2GB.' but does not provide specific hyperparameters, training configurations, or detailed system-level settings for the algorithm itself.