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..
The Impact of Treewidth on ASP Grounding and Solving
Authors: Bernhard Bliem, Marius Moldovan, Michael Morak, Stefan Woltran
IJCAI 2017 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We first perform an experimental evaluation that shows that the solving performance is heavily influenced by the treewidth, given ground input programs that are otherwise uniform, both in size and construction. |
| Researcher Affiliation | Academia | TU Wien, Vienna, Austria |
| Pseudocode | No | The paper includes code listings (Listing 1 and 2) but no explicitly labeled |
| Open Source Code | No | The paper provides a link to benchmarks, but not to the source code for the methodology itself (e.g., the implementation of connection-guarded programs or the experimental setup scripts). |
| Open Datasets | Yes | Full archive: http://dbai.tuwien.ac.at/proj/decodyn/ijcai17-benchmarks.zip |
| Dataset Splits | No | The paper describes the construction of input instances and their properties but does not specify any training, validation, or test dataset splits. |
| Hardware Specification | No | The paper does not mention any specific hardware used for running the experiments (e.g., GPU/CPU models, memory, or cloud instances). |
| Software Dependencies | Yes | Grounding was done using the grounder gringo 4.5.4 [Gebser et al., 2011]. We then measured the running time of the ASP solvers clasp 3.1.4 [Gebser et al., 2011] and WASP 2.0 [Alviano et al., 2015]. |
| Experiment Setup | No | The paper describes how the input instances were generated and the software used, but it does not specify any hyperparameters or system-level training settings for the ASP solvers. |