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..
Plan Reordering and Parallel Execution Ñ A Parameterized Complexity View
Authors: Meysam Aghighi, Christer Bckstrm
AAAI 2017 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We revisit these problems, but applying parameterized complexity analysis rather than standard complexity analysis. We consider various parameters... Our findings include that MCD and MCR are W[2]-hard and in W[P]... Problem PPL is fpt... We primarily study the problems defined by B ackstr om (1998), but using parameterized complexity instead. |
| Researcher Affiliation | Academia | Meysam Aghighi, Christer B ackstr om Department of Computer and Information Science Link oping University Link oping, Sweden {meysam.aghighi, christer.backstrom} at liu.se |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any concrete access to source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not use datasets, therefore no public dataset information is provided. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical evaluation on datasets, so no dataset split information is provided. |
| Hardware Specification | No | The paper is theoretical and does not describe experiments that would require specific hardware, thus no hardware specifications are provided. |
| Software Dependencies | No | The paper is theoretical and does not describe experiments that would require specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe empirical experiments, so no specific experimental setup details (like hyperparameters or training configurations) are provided. |