ABOUT US
Welcome to Redux, a platform for NP-Complete problems. Input your challenges and gain access to reductions, solutions, verifiers, and visualizations. Join our community of problem solvers and unravel computational complexities using the application library. The project was greatly inspired by Richard Karp's paper "Reducibility Among Combinatorial Problems" (Karp, 1972).
When citing Redux, please use the following citation:
Kaden Marchetti, Andrija Sevaljevic, Alex Diviney, Caleb Eardley, Russell Phillips, Rajiv Khadka, Daniel Igbokwe, and Paul Bodily. 2024. Redux: An Interactive, Dynamic Knowledge Base for Teaching NP-completeness. In Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 1 (ITiCSE 2024). Association for Computing Machinery, New York, NY, USA, 255–261. [DOI][PDF]
CONTRIBUTORS
This project was started by Dr. Paul Bodily, who is also the ISU Faculty Sponsor of the project.
Project contributors
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PUBLICATIONS
Below are research publications associated with the Redux project and its contributors.
P. M. Bodily, “LLMs, Computational Theory, and Redux: New Directions for CC in Computational Complexity,” in Proceedings of the Workshop on Theoretical CS and Computational Creativity, 2026. [URL][PDF]
R. Phillips and P. M. Bodily. 2025. SPADE: A library for programmatic parsing and verification of discrete data structures. In 2025 Intermountain Engineering, Technology and Computing Conference (IETC), Orem, UT, USA, pp. 1–5. [DOI][PDF]
A. Sevaljevic and P. M. Bodily. 2024. Comparative empirical analysis of dancing links implementations to solve the exact cover problem. In 2024 Intermountain Engineering, Technology and Computing Conference (IETC), Orem, UT, USA, pp. 255–258. [DOI][PDF]
Kaden Marchetti, Andrija Sevaljevic, Alex Diviney, Caleb Eardley, Russell Phillips, Rajiv Khadka, Daniel Igbokwe, and Paul Bodily. 2024. Redux: An Interactive, Dynamic Knowledge Base for Teaching NP-completeness. In Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 1 (ITiCSE 2024). Association for Computing Machinery, New York, NY, USA, 255–261. [DOI][PDF]
K. Marchetti and P. Bodily. 2022. KAMI: Leveraging the power of crowd-sourcing to solve complex, real-world problems. In 2022 Intermountain Engineering, Technology and Computing Conference (IETC), Orem, UT, USA, pp. 1–4. Best Student Paper Award. [DOI][PDF]
AWARDS
Below are awards associated with the Redux project and its contributors.
THESES AND DISSERTATIONS
Below are theses and dissertations associated with the Redux project.
SUPPORT
Redux has been supported by the following grants:
Bodily, P.M. (Co-Lead), Bradley, J. (Co-Lead), Romney, A. (Co-PI), Petersen, J. (Co-I), “BengalBot MCP: Building AI-Literate Students at Idaho State University,” U.S. Department of Education (DOE) Fund for Improvement of Post-Secondary Education (FIPSE). $300,000. 2026.
Trosper, M.J., “Applied Computational Models and Algorithmic Solutions to Common Optimization Problems In Energy-Water Systems,” Summer Authentic Research Experience (SARE), Idaho Community-engaged Resilience for Energy-Water Systems (I-CREWS), National Science Foundation (NSF). $6,000. 2026.
“Crowd-Sourcing and Visualization of Advanced Computational Theory to Facilitate Application of Algorithmic Knowledgebase to Real-World Combinatorial Problems,” Center for Advanced Energy Studies (CAES). 2024.
“Application of advanced computational theory to facilitate efficient solutions to real-world combinatorial problems”, Center for Advanced Energy Studies (CAES). 2022.
“Interactive visualization tools for teaching computer science theory”, Idaho State University Office of Research. 2022.
Any opinions, findings, conclusions, or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the funding agencies who have supported this work.
LICENSE
This work is licensed under the BSD 3-Clause License.
