puzzle-solver-patterns

Constraint satisfaction solver failures can be debugged using structured tests and validating with real puzzle scenarios like L-shaped layouts. The patterns guide references solver.ts and puzzle.ts to help trace unsatisfiable puzzles and verify constraint logic.

MRV-based backtracking is a search strategy that selects the variable with the Minimum Remaining Values to reduce branching. It works with common constraint types like sum, equal, different, greater, less, and any to efficiently prune invalid puzzle states.

Partial pruning checks are implemented by evaluating constraint satisfaction before a puzzle state is fully assigned. This guide details performing full and partial constraint checks alongside type definitions and algorithmic checks within solver.ts components.

Yes, you can use these constraint patterns to debug unsatisfiable puzzle layouts by applying structured testing workflows. The guide demonstrates validating solver failures using real puzzle scenarios like L-shaped layouts across puzzle.ts and related components.

When tuning MRV backtracking, limitations arise from unsatisfiable puzzle states and incomplete partial pruning. This guide addresses these constraints by providing best practices for type definitions, algorithmic checks, and structured testing workflows to ensure robust solving.