FA-86441 / Procedural level generation constraints / Open access
Enemy spawn point selection: Enemies spawn in water · case 01
Land enemies appear on water tiles.
ROOT CAUSE
Only walls are rejected, so any other tile type is spawnable.
VERIFIED REPAIR
Restore `grid[r][c] != '.'` at the spawn tile step.
Unsuccessful approach: Explicitly allowing water keeps the defect.
Case contract
Candidates [row, col] are tried in order until count spawns are chosen. A spawn must be in bounds on a '.' tile, at Chebyshev distance >= min_dist from the player and at Chebyshev distance >= 2 from every chosen spawn (no touching spawns, diagonals included). Returns chosen cells.
Why this case matters
Procedural generators silently emit unplayable or unfair levels when a single constraint check uses the wrong boundary, axis, neighborhood or update order; the defect is visible in exact generated geometry.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(grid, player, candidates, min_dist, count):
chosen = []
pr, pc = player
for r, c in candidates:
if len(chosen) >= count:
break
if not (0 <= r < len(grid) and 0 <= c < len(grid[0])) or grid[r][c] == '#':
continue
if max(abs(r - pr), abs(c - pc)) < min_dist:
continue
if any(max(abs(r - a), abs(c - b)) < 2 for a, b in chosen):
continue
chosen.append([r, c])
return chosen
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
cases = [[('regression spawn tile #1',
[['...#', '.#..', '#.#~', '~~.~', '~~#.', '~##.', '....', '...#'],
[1, 2],
[[0, 1], [6, 4], [5, 4], [4, 1], [4, 0], [6, 1], [0, 4], [7, 2], [5, 3], [-1, 1]],
3,
2],
[[6, 1], [5, 3]]),
('regression spawn tile #2',
[['~......', '......~', '~#.~##.', '.#..~~.', '#..#~#.', '......#'],
[3, 2],
[[1, 0], [6, 3], [5, 2], [4, 0], [2, 3], [1, 4], [6, 7], [2, 7]],
0,
5],
[[1, 0], [5, 2], [1, 4]]),
('regression spawn tile #3',
[['~#...~..', '~...~~#.', '~~.#.##~', '~.#.#~#.'],
[0, 5],
[[2, 8], [1, 0], [2, 1], [3, 7], [2, 1], [-1, 5], [3, 2], [0, 0]],
1,
3],
[[3, 7]]),
('regression spawn tile #4',
[['#.#', '~..', '~.#', '.#~', '.#.', '#..', '##.', '~#.'], [7, 0], [[5, 0], [2, 0], [5, 3]], 3, 3],
[]),
('diagonal neighbour spawn #1', [['....', '....', '....'], [0, 0], [[1, 2], [2, 3]], 1, 3], [[1, 2]]),
('exact safe radius #1', [['.....', '.....'], [0, 0], [[1, 1], [0, 2]], 2, 2], [[0, 2]]),
('negative index candidate #1', [['...', '...', '..#'], [0, 0], [[-1, -1], [2, 0]], 1, 2], [[2, 0]]),
('control #1',
[['#.#', '...', '#.#', '.#.', '...', '...', '...', '##.'], [6, 2], [[2, -1], [7, 2]], 0, 0],
[])],
[('regression spawn tile #1',
[['~#...~..', '~...~~#.', '~~.#.##~', '~.#.#~#.'],
[0, 5],
[[2, 8], [1, 0], [2, 1], [3, 7], [2, 1], [-1, 5], [3, 2], [0, 0]],
1,
3],
[[3, 7]]),
('regression spawn tile #2',
[['#.#', '~..', '~.#', '.#~', '.#.', '#..', '##.', '~#.'], [7, 0], [[5, 0], [2, 0], [5, 3]], 3, 3],
[]),
('regression spawn tile #3',
[['..~##.', '~..~..', '.~~#.~'], [0, 3], [[1, 4], [-1, 6], [1, 1], [2, 4], [2, 2], [1, 0]], 3, 5],
[]),
('regression spawn tile #4',
[['..##....', '~.#.#.~#', '##...#.~', '.....#~~', '#...#..~', '...#.~.~'],
[1, 0],
[[2, 2], [3, 8], [5, 7], [5, 5]],
0,
5],
[[2, 2]]),
('negative index candidate #1', [['...', '...', '..#'], [0, 0], [[-1, -1], [2, 0]], 1, 2], [[2, 0]]),
('diagonal neighbour spawn #1', [['....', '....', '....'], [0, 0], [[1, 2], [2, 3]], 1, 3], [[1, 2]]),
('control #1',
[['#.#', '...', '#.#', '.#.', '...', '...', '...', '##.'], [6, 2], [[2, -1], [7, 2]], 0, 0],
[]),
('control #2',
[['.#~', '...', '~.#', '#.~', '..#', '#~.'], [3, 1], [[5, 0], [1, 0], [6, -1], [6, -1]], 0, 5],
[[1, 0]])],
[('regression spawn tile #1',
[['..~##.', '~..~..', '.~~#.~'], [0, 3], [[1, 4], [-1, 6], [1, 1], [2, 4], [2, 2], [1, 0]], 3, 5],
[]),
('regression spawn tile #2',
[['..##....', '~.#.#.~#', '##...#.~', '.....#~~', '#...#..~', '...#.~.~'],
[1, 0],
[[2, 2], [3, 8], [5, 7], [5, 5]],
0,
5],
[[2, 2]]),
('regression spawn tile #3',
[['~#~~', '.~~.', '~.~.', '....', '.#.~'],
[1, 0],
[[-1, 2], [-1, 1], [1, 2], [5, 2], [-1, 4], [-1, 2], [2, 0]],
2,
3],
[]),
('regression spawn tile #4',
[['.~....##', '......#.', '~...#..#', '~......~'],
[2, 3],
[[-1, 3], [0, 1], [1, -1], [1, 2], [2, 5], [1, 3]],
2,
1],
[[2, 5]]),
('exact safe radius #1', [['.....', '.....'], [0, 0], [[1, 1], [0, 2]], 2, 2], [[0, 2]]),
('negative index candidate #1', [['...', '...', '..#'], [0, 0], [[-1, -1], [2, 0]], 1, 2], [[2, 0]]),
('control #1',
[['.#~', '...', '~.#', '#.~', '..#', '#~.'], [3, 1], [[5, 0], [1, 0], [6, -1], [6, -1]], 0, 5],
[[1, 0]]),
('control #2',
[['...#...', '......~', '~~.....', '..~....', '.~....~', '.....#.'], [5, 2], [[1, 5]], 0, 0],
[])],
[('regression spawn tile #1',
[['~#~~', '.~~.', '~.~.', '....', '.#.~'],
[1, 0],
[[-1, 2], [-1, 1], [1, 2], [5, 2], [-1, 4], [-1, 2], [2, 0]],
2,
3],
[]),
('regression spawn tile #2',
[['.~....##', '......#.', '~...#..#', '~......~'],
[2, 3],
[[-1, 3], [0, 1], [1, -1], [1, 2], [2, 5], [1, 3]],
2,
1],
[[2, 5]]),
('regression spawn tile #3',
[['.#..#~..', '~...#.#~', '..~.~...'], [0, 4], [[3, 7], [2, 5], [3, -1], [1, 0], [3, 1], [-1, -1]], 2, 3],
[[2, 5]]),
('regression spawn tile #4',
[['~...', '~~.~', '....', '#.~#', '..#~', '....', '#.~.'],
[6, 1],
[[1, 1], [-1, 0], [6, 1], [5, 3], [4, 1], [2, 1], [-1, 3], [1, -1], [6, 1]],
1,
1],
[[5, 3]]),
('diagonal neighbour spawn #1', [['....', '....', '....'], [0, 0], [[1, 2], [2, 3]], 1, 3], [[1, 2]]),
('exact safe radius #1', [['.....', '.....'], [0, 0], [[1, 1], [0, 2]], 2, 2], [[0, 2]]),
('control #1',
[['....', '.#.~', '..~~', '...#'], [2, 0], [[4, -1], [3, 3], [3, 1], [1, 0], [1, 3]], 0, 2],
[[3, 1], [1, 0]]),
('control #2',
[['.#.', '...', '#..', '...', '#..', '#.~'], [5, 2], [[2, -1], [5, 2], [1, 3], [2, 0], [6, 0]], 3, 0],
[])],
[('regression spawn tile #1',
[['.#..#~..', '~...#.#~', '..~.~...'], [0, 4], [[3, 7], [2, 5], [3, -1], [1, 0], [3, 1], [-1, -1]], 2, 3],
[[2, 5]]),
('regression spawn tile #2',
[['~...', '~~.~', '....', '#.~#', '..#~', '....', '#.~.'],
[6, 1],
[[1, 1], [-1, 0], [6, 1], [5, 3], [4, 1], [2, 1], [-1, 3], [1, -1], [6, 1]],
1,
1],
[[5, 3]]),
('regression spawn tile #3',
[['..~.#', '..#~.', '.....', '.....', '~~~~.', '.#..#', '...#.', '#.~##'], [7, 1], [[4, 2]], 3, 2],
[]),
('regression spawn tile #4',
[['..~..', '..#..', '.#..~'],
[1, 0],
[[0, 2], [-1, -1], [0, 1], [3, 5], [-1, 3], [3, 4], [-1, 0], [2, 2], [2, 5], [2, 1]],
0,
1],
[[0, 1]]),
('negative index candidate #1', [['...', '...', '..#'], [0, 0], [[-1, -1], [2, 0]], 1, 2], [[2, 0]]),
('diagonal neighbour spawn #1', [['....', '....', '....'], [0, 0], [[1, 2], [2, 3]], 1, 3], [[1, 2]]),
('control #1',
[['.#.#~.', '~.....', '.~#...', '......', '..#.#.'], [0, 0], [[1, 1], [5, 0], [3, 3], [-1, 0]], 0, 5],
[[1, 1], [3, 3]]),
('control #2',
[['...', '~..', '...', '..#', '...', '..~'],
[0, 0],
[[6, 1], [3, 2], [0, 3], [2, -1], [1, 1], [5, 1]],
3,
0],
[])]]
for label, args, expected in cases[N-1]:
check(label, solve(*args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression spawn tile #1 | [[4, 1], [6, 1]] | [[6, 1], [5, 3]] | Failed |
| regression spawn tile #2 | [[1, 0], [5, 2], [2, 3]] | [[1, 0], [5, 2], [1, 4]] | Failed |
| regression spawn tile #3 | [[1, 0], [3, 7]] | [[3, 7]] | Failed |
| regression spawn tile #4 | [[2, 0]] | [] | Failed |
| diagonal neighbour spawn #1 | [[1, 2]] | [[1, 2]] | Passed |
| exact safe radius #1 | [[0, 2]] | [[0, 2]] | Passed |
| negative index candidate #1 | [[2, 0]] | [[2, 0]] | Passed |
| control #1 | [] | [] | Passed |
SHA-256 / 5af784b2dc8214905bdd599443438c5d81c3629a9b4815042bbed7ec06853c10
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(grid, player, candidates, min_dist, count):
chosen = []
pr, pc = player
for r, c in candidates:
if len(chosen) >= count:
break
if not (0 <= r < len(grid) and 0 <= c < len(grid[0])) or grid[r][c] not in '.~':
continue
if max(abs(r - pr), abs(c - pc)) < min_dist:
continue
if any(max(abs(r - a), abs(c - b)) < 2 for a, b in chosen):
continue
chosen.append([r, c])
return chosen
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
cases = [[('regression spawn tile #1',
[['...#', '.#..', '#.#~', '~~.~', '~~#.', '~##.', '....', '...#'],
[1, 2],
[[0, 1], [6, 4], [5, 4], [4, 1], [4, 0], [6, 1], [0, 4], [7, 2], [5, 3], [-1, 1]],
3,
2],
[[6, 1], [5, 3]]),
('regression spawn tile #2',
[['~......', '......~', '~#.~##.', '.#..~~.', '#..#~#.', '......#'],
[3, 2],
[[1, 0], [6, 3], [5, 2], [4, 0], [2, 3], [1, 4], [6, 7], [2, 7]],
0,
5],
[[1, 0], [5, 2], [1, 4]]),
('regression spawn tile #3',
[['~#...~..', '~...~~#.', '~~.#.##~', '~.#.#~#.'],
[0, 5],
[[2, 8], [1, 0], [2, 1], [3, 7], [2, 1], [-1, 5], [3, 2], [0, 0]],
1,
3],
[[3, 7]]),
('regression spawn tile #4',
[['#.#', '~..', '~.#', '.#~', '.#.', '#..', '##.', '~#.'], [7, 0], [[5, 0], [2, 0], [5, 3]], 3, 3],
[]),
('diagonal neighbour spawn #1', [['....', '....', '....'], [0, 0], [[1, 2], [2, 3]], 1, 3], [[1, 2]]),
('exact safe radius #1', [['.....', '.....'], [0, 0], [[1, 1], [0, 2]], 2, 2], [[0, 2]]),
('negative index candidate #1', [['...', '...', '..#'], [0, 0], [[-1, -1], [2, 0]], 1, 2], [[2, 0]]),
('control #1',
[['#.#', '...', '#.#', '.#.', '...', '...', '...', '##.'], [6, 2], [[2, -1], [7, 2]], 0, 0],
[])],
[('regression spawn tile #1',
[['~#...~..', '~...~~#.', '~~.#.##~', '~.#.#~#.'],
[0, 5],
[[2, 8], [1, 0], [2, 1], [3, 7], [2, 1], [-1, 5], [3, 2], [0, 0]],
1,
3],
[[3, 7]]),
('regression spawn tile #2',
[['#.#', '~..', '~.#', '.#~', '.#.', '#..', '##.', '~#.'], [7, 0], [[5, 0], [2, 0], [5, 3]], 3, 3],
[]),
('regression spawn tile #3',
[['..~##.', '~..~..', '.~~#.~'], [0, 3], [[1, 4], [-1, 6], [1, 1], [2, 4], [2, 2], [1, 0]], 3, 5],
[]),
('regression spawn tile #4',
[['..##....', '~.#.#.~#', '##...#.~', '.....#~~', '#...#..~', '...#.~.~'],
[1, 0],
[[2, 2], [3, 8], [5, 7], [5, 5]],
0,
5],
[[2, 2]]),
('negative index candidate #1', [['...', '...', '..#'], [0, 0], [[-1, -1], [2, 0]], 1, 2], [[2, 0]]),
('diagonal neighbour spawn #1', [['....', '....', '....'], [0, 0], [[1, 2], [2, 3]], 1, 3], [[1, 2]]),
('control #1',
[['#.#', '...', '#.#', '.#.', '...', '...', '...', '##.'], [6, 2], [[2, -1], [7, 2]], 0, 0],
[]),
('control #2',
[['.#~', '...', '~.#', '#.~', '..#', '#~.'], [3, 1], [[5, 0], [1, 0], [6, -1], [6, -1]], 0, 5],
[[1, 0]])],
[('regression spawn tile #1',
[['..~##.', '~..~..', '.~~#.~'], [0, 3], [[1, 4], [-1, 6], [1, 1], [2, 4], [2, 2], [1, 0]], 3, 5],
[]),
('regression spawn tile #2',
[['..##....', '~.#.#.~#', '##...#.~', '.....#~~', '#...#..~', '...#.~.~'],
[1, 0],
[[2, 2], [3, 8], [5, 7], [5, 5]],
0,
5],
[[2, 2]]),
('regression spawn tile #3',
[['~#~~', '.~~.', '~.~.', '....', '.#.~'],
[1, 0],
[[-1, 2], [-1, 1], [1, 2], [5, 2], [-1, 4], [-1, 2], [2, 0]],
2,
3],
[]),
('regression spawn tile #4',
[['.~....##', '......#.', '~...#..#', '~......~'],
[2, 3],
[[-1, 3], [0, 1], [1, -1], [1, 2], [2, 5], [1, 3]],
2,
1],
[[2, 5]]),
('exact safe radius #1', [['.....', '.....'], [0, 0], [[1, 1], [0, 2]], 2, 2], [[0, 2]]),
('negative index candidate #1', [['...', '...', '..#'], [0, 0], [[-1, -1], [2, 0]], 1, 2], [[2, 0]]),
('control #1',
[['.#~', '...', '~.#', '#.~', '..#', '#~.'], [3, 1], [[5, 0], [1, 0], [6, -1], [6, -1]], 0, 5],
[[1, 0]]),
('control #2',
[['...#...', '......~', '~~.....', '..~....', '.~....~', '.....#.'], [5, 2], [[1, 5]], 0, 0],
[])],
[('regression spawn tile #1',
[['~#~~', '.~~.', '~.~.', '....', '.#.~'],
[1, 0],
[[-1, 2], [-1, 1], [1, 2], [5, 2], [-1, 4], [-1, 2], [2, 0]],
2,
3],
[]),
('regression spawn tile #2',
[['.~....##', '......#.', '~...#..#', '~......~'],
[2, 3],
[[-1, 3], [0, 1], [1, -1], [1, 2], [2, 5], [1, 3]],
2,
1],
[[2, 5]]),
('regression spawn tile #3',
[['.#..#~..', '~...#.#~', '..~.~...'], [0, 4], [[3, 7], [2, 5], [3, -1], [1, 0], [3, 1], [-1, -1]], 2, 3],
[[2, 5]]),
('regression spawn tile #4',
[['~...', '~~.~', '....', '#.~#', '..#~', '....', '#.~.'],
[6, 1],
[[1, 1], [-1, 0], [6, 1], [5, 3], [4, 1], [2, 1], [-1, 3], [1, -1], [6, 1]],
1,
1],
[[5, 3]]),
('diagonal neighbour spawn #1', [['....', '....', '....'], [0, 0], [[1, 2], [2, 3]], 1, 3], [[1, 2]]),
('exact safe radius #1', [['.....', '.....'], [0, 0], [[1, 1], [0, 2]], 2, 2], [[0, 2]]),
('control #1',
[['....', '.#.~', '..~~', '...#'], [2, 0], [[4, -1], [3, 3], [3, 1], [1, 0], [1, 3]], 0, 2],
[[3, 1], [1, 0]]),
('control #2',
[['.#.', '...', '#..', '...', '#..', '#.~'], [5, 2], [[2, -1], [5, 2], [1, 3], [2, 0], [6, 0]], 3, 0],
[])],
[('regression spawn tile #1',
[['.#..#~..', '~...#.#~', '..~.~...'], [0, 4], [[3, 7], [2, 5], [3, -1], [1, 0], [3, 1], [-1, -1]], 2, 3],
[[2, 5]]),
('regression spawn tile #2',
[['~...', '~~.~', '....', '#.~#', '..#~', '....', '#.~.'],
[6, 1],
[[1, 1], [-1, 0], [6, 1], [5, 3], [4, 1], [2, 1], [-1, 3], [1, -1], [6, 1]],
1,
1],
[[5, 3]]),
('regression spawn tile #3',
[['..~.#', '..#~.', '.....', '.....', '~~~~.', '.#..#', '...#.', '#.~##'], [7, 1], [[4, 2]], 3, 2],
[]),
('regression spawn tile #4',
[['..~..', '..#..', '.#..~'],
[1, 0],
[[0, 2], [-1, -1], [0, 1], [3, 5], [-1, 3], [3, 4], [-1, 0], [2, 2], [2, 5], [2, 1]],
0,
1],
[[0, 1]]),
('negative index candidate #1', [['...', '...', '..#'], [0, 0], [[-1, -1], [2, 0]], 1, 2], [[2, 0]]),
('diagonal neighbour spawn #1', [['....', '....', '....'], [0, 0], [[1, 2], [2, 3]], 1, 3], [[1, 2]]),
('control #1',
[['.#.#~.', '~.....', '.~#...', '......', '..#.#.'], [0, 0], [[1, 1], [5, 0], [3, 3], [-1, 0]], 0, 5],
[[1, 1], [3, 3]]),
('control #2',
[['...', '~..', '...', '..#', '...', '..~'],
[0, 0],
[[6, 1], [3, 2], [0, 3], [2, -1], [1, 1], [5, 1]],
3,
0],
[])]]
for label, args, expected in cases[N-1]:
check(label, solve(*args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression spawn tile #1 | [[4, 1], [6, 1]] | [[6, 1], [5, 3]] | Failed |
| regression spawn tile #2 | [[1, 0], [5, 2], [2, 3]] | [[1, 0], [5, 2], [1, 4]] | Failed |
| regression spawn tile #3 | [[1, 0], [3, 7]] | [[3, 7]] | Failed |
| regression spawn tile #4 | [[2, 0]] | [] | Failed |
| diagonal neighbour spawn #1 | [[1, 2]] | [[1, 2]] | Passed |
| exact safe radius #1 | [[0, 2]] | [[0, 2]] | Passed |
| negative index candidate #1 | [[2, 0]] | [[2, 0]] | Passed |
| control #1 | [] | [] | Passed |
SHA-256 / 1b0caddb47cfb8d8f88db31492f0424ec630126708054c65aabd260b246f4a54
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(grid, player, candidates, min_dist, count):
chosen = []
pr, pc = player
for r, c in candidates:
if len(chosen) >= count:
break
if not (0 <= r < len(grid) and 0 <= c < len(grid[0])) or grid[r][c] != '.':
continue
if max(abs(r - pr), abs(c - pc)) < min_dist:
continue
if any(max(abs(r - a), abs(c - b)) < 2 for a, b in chosen):
continue
chosen.append([r, c])
return chosen
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
cases = [[('regression spawn tile #1',
[['...#', '.#..', '#.#~', '~~.~', '~~#.', '~##.', '....', '...#'],
[1, 2],
[[0, 1], [6, 4], [5, 4], [4, 1], [4, 0], [6, 1], [0, 4], [7, 2], [5, 3], [-1, 1]],
3,
2],
[[6, 1], [5, 3]]),
('regression spawn tile #2',
[['~......', '......~', '~#.~##.', '.#..~~.', '#..#~#.', '......#'],
[3, 2],
[[1, 0], [6, 3], [5, 2], [4, 0], [2, 3], [1, 4], [6, 7], [2, 7]],
0,
5],
[[1, 0], [5, 2], [1, 4]]),
('regression spawn tile #3',
[['~#...~..', '~...~~#.', '~~.#.##~', '~.#.#~#.'],
[0, 5],
[[2, 8], [1, 0], [2, 1], [3, 7], [2, 1], [-1, 5], [3, 2], [0, 0]],
1,
3],
[[3, 7]]),
('regression spawn tile #4',
[['#.#', '~..', '~.#', '.#~', '.#.', '#..', '##.', '~#.'], [7, 0], [[5, 0], [2, 0], [5, 3]], 3, 3],
[]),
('diagonal neighbour spawn #1', [['....', '....', '....'], [0, 0], [[1, 2], [2, 3]], 1, 3], [[1, 2]]),
('exact safe radius #1', [['.....', '.....'], [0, 0], [[1, 1], [0, 2]], 2, 2], [[0, 2]]),
('negative index candidate #1', [['...', '...', '..#'], [0, 0], [[-1, -1], [2, 0]], 1, 2], [[2, 0]]),
('control #1',
[['#.#', '...', '#.#', '.#.', '...', '...', '...', '##.'], [6, 2], [[2, -1], [7, 2]], 0, 0],
[])],
[('regression spawn tile #1',
[['~#...~..', '~...~~#.', '~~.#.##~', '~.#.#~#.'],
[0, 5],
[[2, 8], [1, 0], [2, 1], [3, 7], [2, 1], [-1, 5], [3, 2], [0, 0]],
1,
3],
[[3, 7]]),
('regression spawn tile #2',
[['#.#', '~..', '~.#', '.#~', '.#.', '#..', '##.', '~#.'], [7, 0], [[5, 0], [2, 0], [5, 3]], 3, 3],
[]),
('regression spawn tile #3',
[['..~##.', '~..~..', '.~~#.~'], [0, 3], [[1, 4], [-1, 6], [1, 1], [2, 4], [2, 2], [1, 0]], 3, 5],
[]),
('regression spawn tile #4',
[['..##....', '~.#.#.~#', '##...#.~', '.....#~~', '#...#..~', '...#.~.~'],
[1, 0],
[[2, 2], [3, 8], [5, 7], [5, 5]],
0,
5],
[[2, 2]]),
('negative index candidate #1', [['...', '...', '..#'], [0, 0], [[-1, -1], [2, 0]], 1, 2], [[2, 0]]),
('diagonal neighbour spawn #1', [['....', '....', '....'], [0, 0], [[1, 2], [2, 3]], 1, 3], [[1, 2]]),
('control #1',
[['#.#', '...', '#.#', '.#.', '...', '...', '...', '##.'], [6, 2], [[2, -1], [7, 2]], 0, 0],
[]),
('control #2',
[['.#~', '...', '~.#', '#.~', '..#', '#~.'], [3, 1], [[5, 0], [1, 0], [6, -1], [6, -1]], 0, 5],
[[1, 0]])],
[('regression spawn tile #1',
[['..~##.', '~..~..', '.~~#.~'], [0, 3], [[1, 4], [-1, 6], [1, 1], [2, 4], [2, 2], [1, 0]], 3, 5],
[]),
('regression spawn tile #2',
[['..##....', '~.#.#.~#', '##...#.~', '.....#~~', '#...#..~', '...#.~.~'],
[1, 0],
[[2, 2], [3, 8], [5, 7], [5, 5]],
0,
5],
[[2, 2]]),
('regression spawn tile #3',
[['~#~~', '.~~.', '~.~.', '....', '.#.~'],
[1, 0],
[[-1, 2], [-1, 1], [1, 2], [5, 2], [-1, 4], [-1, 2], [2, 0]],
2,
3],
[]),
('regression spawn tile #4',
[['.~....##', '......#.', '~...#..#', '~......~'],
[2, 3],
[[-1, 3], [0, 1], [1, -1], [1, 2], [2, 5], [1, 3]],
2,
1],
[[2, 5]]),
('exact safe radius #1', [['.....', '.....'], [0, 0], [[1, 1], [0, 2]], 2, 2], [[0, 2]]),
('negative index candidate #1', [['...', '...', '..#'], [0, 0], [[-1, -1], [2, 0]], 1, 2], [[2, 0]]),
('control #1',
[['.#~', '...', '~.#', '#.~', '..#', '#~.'], [3, 1], [[5, 0], [1, 0], [6, -1], [6, -1]], 0, 5],
[[1, 0]]),
('control #2',
[['...#...', '......~', '~~.....', '..~....', '.~....~', '.....#.'], [5, 2], [[1, 5]], 0, 0],
[])],
[('regression spawn tile #1',
[['~#~~', '.~~.', '~.~.', '....', '.#.~'],
[1, 0],
[[-1, 2], [-1, 1], [1, 2], [5, 2], [-1, 4], [-1, 2], [2, 0]],
2,
3],
[]),
('regression spawn tile #2',
[['.~....##', '......#.', '~...#..#', '~......~'],
[2, 3],
[[-1, 3], [0, 1], [1, -1], [1, 2], [2, 5], [1, 3]],
2,
1],
[[2, 5]]),
('regression spawn tile #3',
[['.#..#~..', '~...#.#~', '..~.~...'], [0, 4], [[3, 7], [2, 5], [3, -1], [1, 0], [3, 1], [-1, -1]], 2, 3],
[[2, 5]]),
('regression spawn tile #4',
[['~...', '~~.~', '....', '#.~#', '..#~', '....', '#.~.'],
[6, 1],
[[1, 1], [-1, 0], [6, 1], [5, 3], [4, 1], [2, 1], [-1, 3], [1, -1], [6, 1]],
1,
1],
[[5, 3]]),
('diagonal neighbour spawn #1', [['....', '....', '....'], [0, 0], [[1, 2], [2, 3]], 1, 3], [[1, 2]]),
('exact safe radius #1', [['.....', '.....'], [0, 0], [[1, 1], [0, 2]], 2, 2], [[0, 2]]),
('control #1',
[['....', '.#.~', '..~~', '...#'], [2, 0], [[4, -1], [3, 3], [3, 1], [1, 0], [1, 3]], 0, 2],
[[3, 1], [1, 0]]),
('control #2',
[['.#.', '...', '#..', '...', '#..', '#.~'], [5, 2], [[2, -1], [5, 2], [1, 3], [2, 0], [6, 0]], 3, 0],
[])],
[('regression spawn tile #1',
[['.#..#~..', '~...#.#~', '..~.~...'], [0, 4], [[3, 7], [2, 5], [3, -1], [1, 0], [3, 1], [-1, -1]], 2, 3],
[[2, 5]]),
('regression spawn tile #2',
[['~...', '~~.~', '....', '#.~#', '..#~', '....', '#.~.'],
[6, 1],
[[1, 1], [-1, 0], [6, 1], [5, 3], [4, 1], [2, 1], [-1, 3], [1, -1], [6, 1]],
1,
1],
[[5, 3]]),
('regression spawn tile #3',
[['..~.#', '..#~.', '.....', '.....', '~~~~.', '.#..#', '...#.', '#.~##'], [7, 1], [[4, 2]], 3, 2],
[]),
('regression spawn tile #4',
[['..~..', '..#..', '.#..~'],
[1, 0],
[[0, 2], [-1, -1], [0, 1], [3, 5], [-1, 3], [3, 4], [-1, 0], [2, 2], [2, 5], [2, 1]],
0,
1],
[[0, 1]]),
('negative index candidate #1', [['...', '...', '..#'], [0, 0], [[-1, -1], [2, 0]], 1, 2], [[2, 0]]),
('diagonal neighbour spawn #1', [['....', '....', '....'], [0, 0], [[1, 2], [2, 3]], 1, 3], [[1, 2]]),
('control #1',
[['.#.#~.', '~.....', '.~#...', '......', '..#.#.'], [0, 0], [[1, 1], [5, 0], [3, 3], [-1, 0]], 0, 5],
[[1, 1], [3, 3]]),
('control #2',
[['...', '~..', '...', '..#', '...', '..~'],
[0, 0],
[[6, 1], [3, 2], [0, 3], [2, -1], [1, 1], [5, 1]],
3,
0],
[])]]
for label, args, expected in cases[N-1]:
check(label, solve(*args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression spawn tile #1 | [[6, 1], [5, 3]] | [[6, 1], [5, 3]] | Passed |
| regression spawn tile #2 | [[1, 0], [5, 2], [1, 4]] | [[1, 0], [5, 2], [1, 4]] | Passed |
| regression spawn tile #3 | [[3, 7]] | [[3, 7]] | Passed |
| regression spawn tile #4 | [] | [] | Passed |
| diagonal neighbour spawn #1 | [[1, 2]] | [[1, 2]] | Passed |
| exact safe radius #1 | [[0, 2]] | [[0, 2]] | Passed |
| negative index candidate #1 | [[2, 0]] | [[2, 0]] | Passed |
| control #1 | [] | [] | Passed |
SHA-256 / 98f7cbd51002ddb7068dd0524b0623ea81b0d96512d2f37a1e192c1851f4d3c0
Verification & scope
Deterministic toy contract stipulated for this model; integer or exact arithmetic only, not a reproduction of any specific game engine. This reproducer isolates one failure mechanism. Results cover the supplied fixtures. Variants within a family share a test contract and should remain grouped when constructing evaluation splits. Related mechanisms with a shared evaluation_group must also remain together; these controlled models are not independent production incidents.
Observations recorded using Python 3.12.14 at 2026-09-29T14:50:49.546296+00:00.
Case digest / 3de658c2f51a77f993e44ba208dae8fdc4af04145dfb9f2ae0f601ce1f79b71d