Problem solution · Python

ARC031 B — 埋め立て

ARC031 B — 埋め立て: a Python solution using breadth-first search. Learn the idea, check the complexity, and read the full code, with credit to KATO-Hiro AtCoder Solutions.

Technique
Breadth-first search
Source
KATO-Hiro AtCoder Solutions
Length
58 lines
Start with the idea.

Try the problem first. If you get stuck, read the approach below, then write your own solution. The full code is at the bottom.

Approach

Breadth-first search

For ARC031 B — 埋め立て, the implementation explores reachable states in layers, which is the standard shape for unweighted shortest paths and minimum-step transitions.

  1. Model each valid configuration as a state and each legal move as an edge.
  2. Seed the queue with the starting state and mark it immediately.
  3. Expand each state once, recording distance or reachability for unseen neighbours.

Code notes

  • 58 lines of Python from the credited upstream file arc031_2.py.
  • The implementation visibly relies on sequence storage, work queue.
  • No explicit loop blocks detected.

Complexity

Verify that each state and transition is processed only a bounded number of times; that determines the traversal cost.

Check the problem constraints before deciding whether this complexity will pass.

Source

Code and credit

This code comes from KATO-Hiro AtCoder Solutions by KATO-Hiro and is used under the CC0-1.0 licence.

Full codeARC031 B — 埋め立て · PythonPython
Use this to learn the idea, then write your own version.
# -*- coding: utf-8 -*-  def main():    from collections import deque     n = 10    s = [list(input()) for _ in range(n)]     land_count = 0    dxy = [(0, 1), (0, -1), (-1, 0), (1, 0)]     for i in range(n):        for j in range(n):            if s[i][j] == "o":                land_count += 1     for i in range(n):        for j in range(n):            d = deque()            d.append((j, i))            visited = [[False for _ in range(n)] for _ in range(n)]            visited[i][j] = True            count = 0             while d:                dix, diy = d.popleft()                 for dx, dy in dxy:                    nx = dix + dx                    ny = diy + dy                     if nx < 0 or nx > 9:                        continue                     if ny < 0 or ny > 9:                        continue                     if s[ny][nx] == "x":                        continue                     if visited[ny][nx]:                        continue                     visited[ny][nx] = True                    d.append((nx, ny))                    count += 1             if count == land_count:                print("YES")                exit()     print("NO")  if __name__ == "__main__":    main() 

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