Refactor axial pathfinding for efficiency and simplicity#118
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- Optimized A* implementation by using a constant array for neighbor offsets, avoiding repeated list allocations. - Improved priority queue efficiency by allowing duplicate entries and skipping stale nodes (replacing O(N) removals with O(log N) behavior). - Reduced object overhead by consolidating state tracking into maps instead of a custom Node class. - Added PathfindingTest.kt to ensure correctness and prevent regressions. Co-authored-by: candour <4670475+candour@users.noreply.github.com>
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📝 WalkthroughWalkthroughThe A* pathfinding algorithm was rewritten from a Node-based approach to a PriorityQueue-backed implementation using gScores, parents maps, and closedSet for neighbor discovery via NEIGHBOR_OFFSETS. Comprehensive unit tests validate the new behavior across path discovery, blocked positions, and edge cases. ChangesA* Pathfinding Refactor & Tests
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This change refactors the pathfinding utility to be more efficient and simpler. It optimizes the A* algorithm implementation for a hexagonal grid using axial coordinates, significantly reducing memory allocations and improving algorithmic performance by avoiding costly queue removals. A new unit test suite verifies the functionality against various scenarios.
PR created automatically by Jules for task 7602219207758408355 started by @candour
Summary by CodeRabbit
Refactor
Tests