Small shortest-path solvers with negative-weight controls
Provide Dijkstra and Bellman–Ford implementations with hand-enumerated reference graphs, explicit negative-edge rejection, and a negative-cycle control.
Proposed original example. Source release and any execution are separate steps.
Do the implementations respect their input assumptions and return the expected distances on the supplied controls?
Compare with manually enumerated integer path costs; verify distinct treatment of negative edges and reachable negative cycles.
What you could produce
- A scoped observations JSON record and a comparison with the stated reference.
Before you use it
- Python 3.13 standard library
Limits to keep in view
- No research code was executed by the preparation tool.
- Author output cannot issue an independent scientific-verification result.
Source and permission context
Original local preparation by the Executable Science seed collection; upstream API references remain separately attributed.
Rights need review. Review the scope and upstream conditions before reuse.
Still unresolved
- Proposed local-draft licenses: original code MIT, explanations CC-BY-4.0, synthetic numeric data CC0-1.0; publication/disclosure approval remains separate.