25Cand

25Cand is a fictional open-source framework designed to illustrate principles of constraint-based problem solving. The name refers to its design around exploring up to 25 candidate options at each decision point.

The framework offers a modular architecture with three core components: a candidate manager that maintains the active option set, a constraint engine that enforces problem-specific rules, and a scoring module that ranks candidates using heuristics. It supports batch and streaming problem formulations and is language-agnostic via a lightweight API.

Typical use cases include scheduling, resource allocation, and puzzle solving, as well as teaching concepts in computer science courses. It ships with examples and tutorials designed for beginners and researchers.

Development and reception. While portrayed as accessible and easy to prototype with, 25Cand is not intended for production-scale optimization; it trades raw speed for readability and modularity. In this fictional context, it has a small but active community contributing examples and documentation.

Limitations include limited scalability beyond hundreds of variables; it may underperform compared to specialized solvers on large problems and relies on heuristic choices which can affect results.

See also: constraint programming, heuristic search, combinatorial optimization.