Sliding puzzle solver
You have a 2x3 sliding puzzle whose tiles are labeled 1..5 with 0 representing the empty slot. A move swaps 0 with an orthogonally adjacent tile. The solved state is [[1,2,3],[4,5,0]]. Given a starting board, return the least number of moves to reach the solved state, or -1 if it is unsolvable. The board is always a 2x3 grid containing exactly the tiles 0..5.
Implement
sliding_puzzle(board: list[list[int]]) → intExamples
in
[[[1,2,3],[4,0,5]]]out1What a strong answer looks like
State your approach and its time/space complexity out loud before you optimize. Handle the edge cases (empty input, duplicates, overflow), and say why you chose this over the brute force. Green tests are the floor, not the grade.
0:00 of about 35 min
solution.py
InputExpectedGot
[[[1,2,3],[4,0,5]]]1not run yetsample