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 Shift Toward Open and Reproducible AI Research," Under Review, 2026. doi: 10.48550/arXiv.2606.16974..
A Bitwise GAC Algorithm for Alldifferent Constraints
Authors: Zhe Li, Yaohua Wang, Zhanshan Li
IJCAI 2023 | Venue PDF | LLM Run Details | Input Tokens: 17,577 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 3,909 Total number of tokens produced by the LLM (including reasoning/thinking tokens) for this paper's analysis.
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our experiments show that Alldiffbit outperforms the state-of-the-art GAC algorithms over 60%. Our experiments on large numbers of constraint problems (CPs) show that Alldiffbit is both efficient and stable. |
| Researcher Affiliation | Academia | 1National University of Defense Technology, Changsha, China 2Jilin University, Changchun, China |
| Pseudocode | Yes | Algorithm 1: FIND SCCS |
| Open Source Code | Yes | The source code and dataset are available at https://github.com/leezear2022/alldiff-choco. |
| Open Datasets | Yes | To conduct a comprehensive evaluation, we used various alldifferent CP instances from the XCSP3 website [Boussemart et al., 2016]4. http://xcsp.org/ |
| Dataset Splits | No | The paper does not provide specific details about training, validation, or test dataset splits (e.g., percentages, sample counts, or specific splitting methodology). |
| Hardware Specification | Yes | Our experiments were conducted on a PC with an AMD Ryzen 9 7950X CPU @ 4.5GHz, 32 GB RAM, and 64-bit Windows 11. |
| Software Dependencies | Yes | All the algorithms were implemented in the Java-based CP solver, Choco [Prud homme et al., 2017]5 using Open JDK 19. |
| Experiment Setup | Yes | To ensure fairness, We used binary branching search with DOM [Dechter and Meiri, 1994] as the variable ordering heuristic, and min value as the value ordering heuristic. |