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..
Conflict-driven ASP Solving with External Sources and Program Splits
Authors: Christoph Redl
IJCAI 2017 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In Section 6 we present our implementation and experimental results, which show a significant in some cases even exponential speedup. |
| Researcher Affiliation | Academia | Institut f ur Informationssysteme, Technische Universit at Wien Favoritenstraße 9-11, A-1040 Vienna, Austria EMAIL |
| Pseudocode | Yes | Algorithm 1: HEX-CDNL; Algorithm 2: Inconsistency Analysis |
| Open Source Code | No | The paper mentions integrating techniques into DLVHEX (http:/www.kr.tuwien.ac.at/research/systems/dlvhex) and provides a link to benchmark encodings (https:/github.com/hexhex/core/tree/master/benchmarks), but does not provide a direct link or explicit statement for the source code of the specific methodology described in the paper. |
| Open Datasets | No | For the experiment we consider for each size n ten randomly generated instances with n domain elements, n 5 + 1 properties, a random function m, and a random number of constraints, such that their count has an expected value of n. |
| Dataset Splits | No | The paper does not provide specific training/validation/test dataset splits or describe a cross-validation setup. |
| Hardware Specification | Yes | All benchmarks were run on a Linux machine with two 12-core AMD Opteron 6176 SE CPUs and 128 GB RAM; timeout was 300 secs and memout 8 GB per instance. |
| Software Dependencies | Yes | For the experiments, we integrated our techniques into the reasoner DLVHEX4 with GRINGO 4.5.4 and CLASP 3.1.4 as backends. |
| Experiment Setup | Yes | All benchmarks were run on a Linux machine with two 12-core AMD Opteron 6176 SE CPUs and 128 GB RAM; timeout was 300 secs and memout 8 GB per instance. We used the HTCondor load distribution system (http:/research.cs. wisc.edu/htcondor) to ensure robust runtimes (i.e., deviations of runs on the same instance are negligible). |