Maze
A maze is a spatial puzzle or problem space of connected and obstructed routes in which a path must be found between designated locations.
Classic Computer Science Problems in Swift: Essential techniques for practicing programmers
A navigational problem space consisting of connected locations and passages with a goal of finding a path between locations.
- How it is used
- Uses a grid navigation problem to exercise depth-first search, breadth-first search, and A*.
- How deep it goes
- Builds random generation, locations, legal moves, goal testing, and path display; does not guarantee a generated maze has a solution.
- Examples
- Runs searches on randomly generated 10-by-10 grids and prints routes marked with start, goal, and path characters.
- What you can do after
- Build it from scratch in Swift, then run a pathfinding algorithm and display a route when one exists.
Learn Go with Pocket-Sized Projects
A maze is a spatial puzzle consisting of connected and obstructed routes arranged so that a path must be found between designated locations.
- How it is used
- Uses mazes as a complete engineering exercise for concurrent exploration, image processing, command-line output, and testing.
- How deep it goes
- Explains grid encoding, constraints, neighbor discovery, entrance scanning, concurrent exploration, and focused tests.
- Examples
- Demonstrates edge and internal treasures, colored PNG grids, dead ends, branches, crosses, and small exploration test images.
- What you can do after
- Build a Go command-line solver that reads a PNG maze, finds its solution, highlights the route, and optionally creates an exploration GIF.
Read how Learn Go with Pocket-Sized Projects explains maze →
Related concepts
- PNGuses · PNG is a lossless raster-image file format supporting indexed, grayscale, and truecolor images, with optional transparency and metadata.
- griduses · A grid is a regular arrangement of positions or cells organized by rows and columns or by fixed neighboring relationships.
- A-star algorithmmeasured by · A* is an informed graph-search algorithm that prioritizes paths or states by combining the cost incurred so far with a heuristic estimate of the remaining cost to a goal.
- breadth-first searchmeasured by · Breadth-first search is a graph or tree traversal algorithm that explores nodes in nondecreasing order of their distance from a starting node.
- depth-first searchmeasured by · Depth-first search is a graph or tree traversal algorithm that explores one branch as far as possible before backtracking to explore alternatives.
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