FA-10666 / Raster clipping / Open access

Damage tiles exclusive end · case 01

A damage interval ending on a tile boundary invalidates the following clean tile.

Verified by executionVariant 1 · 4 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

A damage interval ending on a tile boundary invalidates the following clean tile.

VERIFIED REPAIR

Use the stage contract: For nonnegative integer damaged span [start,end) with end>=start and positive tile size, list every intersected tile index once.

Unsuccessful approach: Excluding the final quotient omits a partially covered ending tile.

Case contract

For nonnegative integer damaged span [start,end) with end>=start and positive tile size, list every intersected tile index once.

Why this case matters

A deterministic software graphics stage with explicit channel and coordinate conventions; no hardware, device profile or API behavior is inferred.

1 / The failure

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(start, end, tile):
    return list(range(start//tile,end//tile+1))
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1', solve(*(0, 8, 4)), [0, 1])
check('fixture 2', solve(*(1, 5, 4)), [0, 1])
check('fixture 3', solve(*(4, 4, 4)), [])
check('fixture 4', solve(*(4, 8, 4)), [1])
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
fixture 1	`[0, 1, 2]`	`[0, 1]`	Failed
fixture 2	`[0, 1]`	`[0, 1]`	Passed
fixture 3	`[1]`	`[]`	Failed
fixture 4	`[1, 2]`	`[1]`	Failed

SHA-256 / 6cc5a4e106a3699fd731ad3d04352a8434580ce66fc797b8afa7165eaa15c68e

2 / The unsuccessful fix

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(start, end, tile):
    return list(range(start//tile,end//tile))
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1', solve(*(0, 8, 4)), [0, 1])
check('fixture 2', solve(*(1, 5, 4)), [0, 1])
check('fixture 3', solve(*(4, 4, 4)), [])
check('fixture 4', solve(*(4, 8, 4)), [1])
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
fixture 1	`[0, 1]`	`[0, 1]`	Passed
fixture 2	`[0]`	`[0, 1]`	Failed
fixture 3	`[]`	`[]`	Passed
fixture 4	`[1]`	`[1]`	Passed

SHA-256 / 015bad4efc8bc8bf5cc597ebc4cc5a62883cfb2f0f6a00b0f82a7a6c58cca8a7

3 / The verified repair

Exit 0

"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(start, end, tile):
    return list(range(start//tile,(end-1)//tile+1)) if end>start else []
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1', solve(*(0, 8, 4)), [0, 1])
check('fixture 2', solve(*(1, 5, 4)), [0, 1])
check('fixture 3', solve(*(4, 4, 4)), [])
check('fixture 4', solve(*(4, 8, 4)), [1])
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
fixture 1	`[0, 1]`	`[0, 1]`	Passed
fixture 2	`[0, 1]`	`[0, 1]`	Passed
fixture 3	`[]`	`[]`	Passed
fixture 4	`[1]`	`[1]`	Passed

SHA-256 / 518593d0fcfa7bffc96f7fca039ac08fd738685ea0ffc3a55df9c78725aa8442

Verification & scope

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 2026-09-29T14:38:41.166904+00:00.

Case digest / 35293da91be04a553ee71c4325f8db28065dfa4ec3f5087bf9d46619975461cb