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..
Exploiting Justifications for Lazy Grounding of Answer Set Programs
Authors: Bart Bogaerts, Antonius Weinzierl
IJCAI 2018 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We implemented the justification analysis in ALPHA4 and present the results of our experiments. The benchmarks were run on a cluster of Linux machines with Intel Xeon E5-2680 v3 CPUs. |
| Researcher Affiliation | Academia | KU Leuven, Department of Computer Science, Celestijnenlaan 200A, Leuven, Belgium Aalto University, Department of Computer Science, FI-00076 AALTO, Finland |
| Pseudocode | Yes | Algorithm 1: ANALYZE: High level overview of the justification-conflict analysis. Algorithm 2: EXPLAINUNJUST: Find a set of litsets that covers all bodies of rules with head p. Algorithm 3: UNJUSTCOVER |
| Open Source Code | Yes | ALPHA is freely available at: https://github.com/alpha-asp/Alpha |
| Open Datasets | Yes | The instances used for benchmarking are available at https://dtai.cs.kuleuven.be/krr/experiments/alpha_justifications.zip. |
| Dataset Splits | No | The paper does not specify distinct training, validation, or test splits for its benchmarks, which are problem instances used for evaluation. |
| Hardware Specification | Yes | The benchmarks were run on a cluster of Linux machines with Intel Xeon E5-2680 v3 CPUs. |
| Software Dependencies | No | The paper mentions 'ALPHA4' and 'CLINGO' but does not provide specific version numbers for these or other software dependencies. |
| Experiment Setup | Yes | Each benchmark was given 300 seconds and 8GB of memory on a single core of the cluster. Every run requested 10 answer sets and if a problem admits random instances, the reported run times are an average over 10 different random inputs while for other problems it is the average over 5 runs on the same instance. |