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..
Object Reachability via Swaps along a Line
Authors: Sen Huang, Mingyu Xiao2037-2044
AAAI 2019 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We answer this open problem positively by giving a polynomial-time algorithm. Furthermore, we show that the problem on a path will become NP-hard when the preferences of the agents are weak (ties are allowed). |
| Researcher Affiliation | Academia | Sen Huang, Mingyu Xiao School of Computer Science and Engineering University of Electronic Science and Technology of China |
| Pseudocode | Yes | Algorithm 1: Main steps to solve STRICT OBJECT REACHABILITY in a path |
| Open Source Code | No | No statement about making the source code publicly available was found. |
| Open Datasets | No | The paper describes a theoretical algorithm and proves NP-hardness, and does not involve empirical evaluation on a dataset that would require public access. |
| Dataset Splits | No | The paper describes a theoretical algorithm and proofs, and does not involve experimental validation on data with specified splits. |
| Hardware Specification | No | The paper is theoretical and does not describe experiments run on specific hardware. |
| Software Dependencies | No | The paper mentions using 'solvers for the 2-SAT problem' and refers to 'the O(n+m)-time algorithm for 2-SAT (Aspvall, Plass, and Tarjan 1979)', but does not provide specific version numbers for any software dependencies. |
| Experiment Setup | No | The paper describes a theoretical algorithm and its complexity, and does not provide details on experimental setup such as hyperparameters or training configurations. |