FAILURE MAP
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FA-80656 / Bidirectional text layout / Open access

Caret visual position: line start caret · case 01

A caret at offset 0 with backward affinity lands at the end of the line.

Verified by executionVariant 1 · 8 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

Offset 0 is not special-cased, so index -1 wraps to the last character.

VERIFIED REPAIR

Always attach offset 0 to the leading edge of character 0.

Unsuccessful approach: Special-casing offset 1 too misplaces carets after the first character.

Case contract

Input [levels, logical caret offset k, affinity]. Characters are one unit wide and visually ordered by level reversal. Affinity "after" attaches the caret to the leading edge of character k (if k < n), otherwise to the trailing edge of character k-1; offset 0 always uses the leading edge of character 0. The leading edge of an LTR character is its left side, of an RTL (odd) character its right side. Return the visual x.

Why this case matters

Mixed right-to-left and left-to-right text must resolve levels and visual order exactly, or words, numbers and carets land in the wrong place.

1 / The failure

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(x):
    def reorder(lv):
        vis = list(range(len(lv)))
        odd = [l for l in lv if l % 2 == 1]
        if not odd:
            return vis
        for lev in range(max(lv), min(odd) - 1, -1):
            i = 0
            while i < len(vis):
                if lv[vis[i]] >= lev:
                    j = i
                    while j < len(vis) and lv[vis[j]] >= lev:
                        j += 1
                    vis[i:j] = vis[i:j][::-1]
                    i = j
                else:
                    i += 1
        return vis
    
    levels, k, affinity = x
    n = len(levels)
    if n == 0:
        return 0
    vis = reorder(levels)
    pos = [0] * n
    for v, i in enumerate(vis):
        pos[i] = v
    if affinity == 'after' and k < n:
        j = k
        leading = True
    else:
        j = k - 1
        leading = False
    rtl = levels[j] % 2 == 1
    if leading:
        return pos[j] + 1 if rtl else pos[j]
    return pos[j] if rtl else pos[j] + 1
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('line start before', [[1, 1, 0], 0, 'before'], 2), ('regression: line start caret', [[2, 3], 0, 'before'], 0), ('partial-repair probe', [[4, 1, 1, 1, 3, 3, 1], 1, 'before'], 7), ('partial-repair probe', [[1, 0], 1, 'before'], 0), ('line end', [[1, 1, 1], 3, 'after'], 0), ('caret at direction boundary', [[0, 0, 1, 1], 2, 'before'], 2), ('control layout', [[3], 0, 'after'], 1), ('control layout', [[1, 1, 1, 1, 1, 1, 1, 3], 6, 'before'], 2)], [('regression: line start caret', [[2], 0, 'before'], 0), ('regression: line start caret', [[2, 2], 0, 'before'], 0), ('partial-repair probe', [[4, 1, 4, 4], 1, 'before'], 4), ('partial-repair probe', [[4, 1, 1, 1, 3, 3, 1], 1, 'before'], 7), ('caret at direction boundary', [[0, 0, 1, 1], 2, 'before'], 2), ('same boundary after', [[0, 0, 1, 1], 2, 'after'], 4), ('control layout', [[3, 3, 0, 2, 0, 0], 0, 'after'], 2), ('control layout', [[1, 1, 1, 1, 3], 2, 'after'], 3)], [('regression: line start caret', [[1], 0, 'before'], 1), ('regression: line start caret', [[1], 0, 'before'], 1), ('partial-repair probe', [[1, 0], 1, 'before'], 0), ('partial-repair probe', [[4, 1, 1, 1, 3, 3, 1], 1, 'before'], 7), ('same boundary after', [[0, 0, 1, 1], 2, 'after'], 4), ('caret at direction boundary', [[0, 0, 1, 1], 2, 'before'], 2), ('control layout', [[2, 2, 2, 2, 2, 2, 2, 2, 1], 6, 'after'], 7), ('control layout', [[0, 0, 0], 2, 'after'], 2)], [('regression: line start caret', [[2, 3, 3, 3, 1, 1, 1], 0, 'before'], 3), ('regression: line start caret', [[2, 1, 1, 1], 0, 'before'], 3), ('partial-repair probe', [[2, 1, 1, 1, 1, 1, 1, 1, 2], 1, 'before'], 9), ('partial-repair probe', [[1, 0], 1, 'before'], 0), ('line start before', [[1, 1, 0], 0, 'before'], 2), ('same boundary after', [[0, 0, 1, 1], 2, 'after'], 4), ('control layout', [[0, 0, 1, 1, 2, 2, 2, 0, 0], 6, 'before'], 4), ('control layout', [[1, 1, 1, 2, 2, 2, 2, 3], 3, 'before'], 5)], [('regression: line start caret', [[2, 2, 2, 2, 2, 3, 3, 2, 1], 0, 'before'], 1), ('regression: line start caret', [[2], 0, 'before'], 0), ('partial-repair probe', [[4, 1, 4, 4], 1, 'before'], 4), ('partial-repair probe', [[1, 0], 1, 'before'], 0), ('line end', [[1, 1, 1], 3, 'after'], 0), ('caret at direction boundary', [[0, 0, 1, 1], 2, 'before'], 2), ('control layout', [[0, 1, 1, 2, 2, 2, 3, 3, 3, 1], 3, 'before'], 8), ('control layout', [[0, 0, 0], 2, 'after'], 2)]]
for label, args, expected in fixtures[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 fixtureActualExpectedOutcome
line start before32Failed
regression: line start caret10Failed
partial-repair probe77Passed
partial-repair probe00Passed
line end00Passed
caret at direction boundary22Passed
control layout11Passed
control layout22Passed

SHA-256 / 8588363434846328dc6edffccc3aa198ecc062c6421a2cfd285006019337c19e

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(x):
    def reorder(lv):
        vis = list(range(len(lv)))
        odd = [l for l in lv if l % 2 == 1]
        if not odd:
            return vis
        for lev in range(max(lv), min(odd) - 1, -1):
            i = 0
            while i < len(vis):
                if lv[vis[i]] >= lev:
                    j = i
                    while j < len(vis) and lv[vis[j]] >= lev:
                        j += 1
                    vis[i:j] = vis[i:j][::-1]
                    i = j
                else:
                    i += 1
        return vis
    
    levels, k, affinity = x
    n = len(levels)
    if n == 0:
        return 0
    vis = reorder(levels)
    pos = [0] * n
    for v, i in enumerate(vis):
        pos[i] = v
    if affinity == 'after' and k < n or k <= 1:
        j = k
        leading = True
    else:
        j = k - 1
        leading = False
    rtl = levels[j] % 2 == 1
    if leading:
        return pos[j] + 1 if rtl else pos[j]
    return pos[j] if rtl else pos[j] + 1
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('line start before', [[1, 1, 0], 0, 'before'], 2), ('regression: line start caret', [[2, 3], 0, 'before'], 0), ('partial-repair probe', [[4, 1, 1, 1, 3, 3, 1], 1, 'before'], 7), ('partial-repair probe', [[1, 0], 1, 'before'], 0), ('line end', [[1, 1, 1], 3, 'after'], 0), ('caret at direction boundary', [[0, 0, 1, 1], 2, 'before'], 2), ('control layout', [[3], 0, 'after'], 1), ('control layout', [[1, 1, 1, 1, 1, 1, 1, 3], 6, 'before'], 2)], [('regression: line start caret', [[2], 0, 'before'], 0), ('regression: line start caret', [[2, 2], 0, 'before'], 0), ('partial-repair probe', [[4, 1, 4, 4], 1, 'before'], 4), ('partial-repair probe', [[4, 1, 1, 1, 3, 3, 1], 1, 'before'], 7), ('caret at direction boundary', [[0, 0, 1, 1], 2, 'before'], 2), ('same boundary after', [[0, 0, 1, 1], 2, 'after'], 4), ('control layout', [[3, 3, 0, 2, 0, 0], 0, 'after'], 2), ('control layout', [[1, 1, 1, 1, 3], 2, 'after'], 3)], [('regression: line start caret', [[1], 0, 'before'], 1), ('regression: line start caret', [[1], 0, 'before'], 1), ('partial-repair probe', [[1, 0], 1, 'before'], 0), ('partial-repair probe', [[4, 1, 1, 1, 3, 3, 1], 1, 'before'], 7), ('same boundary after', [[0, 0, 1, 1], 2, 'after'], 4), ('caret at direction boundary', [[0, 0, 1, 1], 2, 'before'], 2), ('control layout', [[2, 2, 2, 2, 2, 2, 2, 2, 1], 6, 'after'], 7), ('control layout', [[0, 0, 0], 2, 'after'], 2)], [('regression: line start caret', [[2, 3, 3, 3, 1, 1, 1], 0, 'before'], 3), ('regression: line start caret', [[2, 1, 1, 1], 0, 'before'], 3), ('partial-repair probe', [[2, 1, 1, 1, 1, 1, 1, 1, 2], 1, 'before'], 9), ('partial-repair probe', [[1, 0], 1, 'before'], 0), ('line start before', [[1, 1, 0], 0, 'before'], 2), ('same boundary after', [[0, 0, 1, 1], 2, 'after'], 4), ('control layout', [[0, 0, 1, 1, 2, 2, 2, 0, 0], 6, 'before'], 4), ('control layout', [[1, 1, 1, 2, 2, 2, 2, 3], 3, 'before'], 5)], [('regression: line start caret', [[2, 2, 2, 2, 2, 3, 3, 2, 1], 0, 'before'], 1), ('regression: line start caret', [[2], 0, 'before'], 0), ('partial-repair probe', [[4, 1, 4, 4], 1, 'before'], 4), ('partial-repair probe', [[1, 0], 1, 'before'], 0), ('line end', [[1, 1, 1], 3, 'after'], 0), ('caret at direction boundary', [[0, 0, 1, 1], 2, 'before'], 2), ('control layout', [[0, 1, 1, 2, 2, 2, 3, 3, 3, 1], 3, 'before'], 8), ('control layout', [[0, 0, 0], 2, 'after'], 2)]]
for label, args, expected in fixtures[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 fixtureActualExpectedOutcome
line start before22Passed
regression: line start caret00Passed
partial-repair probe67Failed
partial-repair probe10Failed
line end00Passed
caret at direction boundary22Passed
control layout11Passed
control layout22Passed

SHA-256 / 84a273ff0ec885f085c77bdc37a9c9297cea6348f40ceb472882a3b5787a056a

3 / The verified repair

Exit 0
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(x):
    def reorder(lv):
        vis = list(range(len(lv)))
        odd = [l for l in lv if l % 2 == 1]
        if not odd:
            return vis
        for lev in range(max(lv), min(odd) - 1, -1):
            i = 0
            while i < len(vis):
                if lv[vis[i]] >= lev:
                    j = i
                    while j < len(vis) and lv[vis[j]] >= lev:
                        j += 1
                    vis[i:j] = vis[i:j][::-1]
                    i = j
                else:
                    i += 1
        return vis
    
    levels, k, affinity = x
    n = len(levels)
    if n == 0:
        return 0
    vis = reorder(levels)
    pos = [0] * n
    for v, i in enumerate(vis):
        pos[i] = v
    if affinity == 'after' and k < n or k == 0:
        j = k
        leading = True
    else:
        j = k - 1
        leading = False
    rtl = levels[j] % 2 == 1
    if leading:
        return pos[j] + 1 if rtl else pos[j]
    return pos[j] if rtl else pos[j] + 1
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('line start before', [[1, 1, 0], 0, 'before'], 2), ('regression: line start caret', [[2, 3], 0, 'before'], 0), ('partial-repair probe', [[4, 1, 1, 1, 3, 3, 1], 1, 'before'], 7), ('partial-repair probe', [[1, 0], 1, 'before'], 0), ('line end', [[1, 1, 1], 3, 'after'], 0), ('caret at direction boundary', [[0, 0, 1, 1], 2, 'before'], 2), ('control layout', [[3], 0, 'after'], 1), ('control layout', [[1, 1, 1, 1, 1, 1, 1, 3], 6, 'before'], 2)], [('regression: line start caret', [[2], 0, 'before'], 0), ('regression: line start caret', [[2, 2], 0, 'before'], 0), ('partial-repair probe', [[4, 1, 4, 4], 1, 'before'], 4), ('partial-repair probe', [[4, 1, 1, 1, 3, 3, 1], 1, 'before'], 7), ('caret at direction boundary', [[0, 0, 1, 1], 2, 'before'], 2), ('same boundary after', [[0, 0, 1, 1], 2, 'after'], 4), ('control layout', [[3, 3, 0, 2, 0, 0], 0, 'after'], 2), ('control layout', [[1, 1, 1, 1, 3], 2, 'after'], 3)], [('regression: line start caret', [[1], 0, 'before'], 1), ('regression: line start caret', [[1], 0, 'before'], 1), ('partial-repair probe', [[1, 0], 1, 'before'], 0), ('partial-repair probe', [[4, 1, 1, 1, 3, 3, 1], 1, 'before'], 7), ('same boundary after', [[0, 0, 1, 1], 2, 'after'], 4), ('caret at direction boundary', [[0, 0, 1, 1], 2, 'before'], 2), ('control layout', [[2, 2, 2, 2, 2, 2, 2, 2, 1], 6, 'after'], 7), ('control layout', [[0, 0, 0], 2, 'after'], 2)], [('regression: line start caret', [[2, 3, 3, 3, 1, 1, 1], 0, 'before'], 3), ('regression: line start caret', [[2, 1, 1, 1], 0, 'before'], 3), ('partial-repair probe', [[2, 1, 1, 1, 1, 1, 1, 1, 2], 1, 'before'], 9), ('partial-repair probe', [[1, 0], 1, 'before'], 0), ('line start before', [[1, 1, 0], 0, 'before'], 2), ('same boundary after', [[0, 0, 1, 1], 2, 'after'], 4), ('control layout', [[0, 0, 1, 1, 2, 2, 2, 0, 0], 6, 'before'], 4), ('control layout', [[1, 1, 1, 2, 2, 2, 2, 3], 3, 'before'], 5)], [('regression: line start caret', [[2, 2, 2, 2, 2, 3, 3, 2, 1], 0, 'before'], 1), ('regression: line start caret', [[2], 0, 'before'], 0), ('partial-repair probe', [[4, 1, 4, 4], 1, 'before'], 4), ('partial-repair probe', [[1, 0], 1, 'before'], 0), ('line end', [[1, 1, 1], 3, 'after'], 0), ('caret at direction boundary', [[0, 0, 1, 1], 2, 'before'], 2), ('control layout', [[0, 1, 1, 2, 2, 2, 3, 3, 3, 1], 3, 'before'], 8), ('control layout', [[0, 0, 0], 2, 'after'], 2)]]
for label, args, expected in fixtures[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 fixtureActualExpectedOutcome
line start before22Passed
regression: line start caret00Passed
partial-repair probe77Passed
partial-repair probe00Passed
line end00Passed
caret at direction boundary22Passed
control layout11Passed
control layout22Passed

SHA-256 / d7cf0a9ebcb973c3b12bd34ec4f03537d328086045dd294ba635e7f804bac2c0

Verification & scope

A deterministic toy bidi model over stipulated class labels and integer levels; it is inspired by, but does not claim conformance to, any published algorithm. 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 2026-09-29T14:49:56.039867+00:00.

Case digest / 178ba8fbd63fdd9cfd19e2c31c0e302ed17f84e6085b1cf0470ddd9403ae2307