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FA-36056 / Tab interfaces / Open access

Unpin restoration: new pin count · case 01

The tab workspace reports an incorrect new pin count.

Verified by executionVariant 1 · 6 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The new pin count decision uses len(x['pins']) instead of len(x['pins'])-1.

VERIFIED REPAIR

Use the stipulated workspace rule: len(x['pins'])-1.

Unsuccessful approach: The partial repair 0 still violates a workspace boundary or normal case.

Case contract

Unpin restores a tab after the remaining pin prefix at its saved unpinned rank, clamps rank to the current normal partition and restores surviving group membership.

Why this case matters

Offline tab/panel workspace behavior; no browser or desktop framework is emulated.

1 / The failure

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

N = 1
observations = []
def solve(x):
    r0 = [t for t in x['pins'] if t!=x['unpin']]
    r1 = min(x['rank'],len(x['normal']))
    r2 = len(x['pins'])-1+min(x['rank'],len(x['normal']))
    r3 = x['normal'][:min(x['rank'],len(x['normal']))]+[x['unpin']]+x['normal'][min(x['rank'],len(x['normal'])):]
    r4 = x['saved_group'] if x['saved_group'] in x['groups'] else None
    r5 = len(x['pins'])
    return [r0,r1,r2,r3,r4,r5]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = {1: [({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c'], 'unpin': 'p', 'rank': 0, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 0, 1, ['p', 'a', 'b', 'c'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c'], 'unpin': 'p', 'rank': 9, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 3, 4, ['a', 'b', 'c', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': [], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 0, 1, ['p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c'], None, 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c'], 'unpin': 'q', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['p'], 2, 3, ['a', 'b', 'q', 'c'], 'g', 1])], 2: [({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0'], 'unpin': 'p', 'rank': 0, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 0, 1, ['p', 'a', 'b', 'c', 'extra0'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0'], 'unpin': 'p', 'rank': 9, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 4, 5, ['a', 'b', 'c', 'extra0', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['extra0'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 1, 2, ['extra0', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0'], None, 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0'], 'unpin': 'q', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['p'], 2, 3, ['a', 'b', 'q', 'c', 'extra0'], 'g', 1])], 3: [({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0', 'extra1'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1'], 'unpin': 'p', 'rank': 0, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 0, 1, ['p', 'a', 'b', 'c', 'extra0', 'extra1'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1'], 'unpin': 'p', 'rank': 9, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 5, 6, ['a', 'b', 'c', 'extra0', 'extra1', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['extra0', 'extra1'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['extra0', 'extra1', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0', 'extra1'], None, 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1'], 'unpin': 'q', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['p'], 2, 3, ['a', 'b', 'q', 'c', 'extra0', 'extra1'], 'g', 1])], 4: [({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0', 'extra1', 'extra2'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2'], 'unpin': 'p', 'rank': 0, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 0, 1, ['p', 'a', 'b', 'c', 'extra0', 'extra1', 'extra2'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2'], 'unpin': 'p', 'rank': 9, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 6, 7, ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['extra0', 'extra1', 'extra2'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['extra0', 'extra1', 'p', 'extra2'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0', 'extra1', 'extra2'], None, 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2'], 'unpin': 'q', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['p'], 2, 3, ['a', 'b', 'q', 'c', 'extra0', 'extra1', 'extra2'], 'g', 1])], 5: [({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'unpin': 'p', 'rank': 0, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 0, 1, ['p', 'a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'unpin': 'p', 'rank': 9, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 7, 8, ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['extra0', 'extra1', 'extra2', 'extra3'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['extra0', 'extra1', 'p', 'extra2', 'extra3'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], None, 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'unpin': 'q', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['p'], 2, 3, ['a', 'b', 'q', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'g', 1])]}
for i, (inputs, expected) in enumerate(fixtures[N]):
    check("workspace regression "+str(i), solve(inputs), 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
workspace regression 0[['q'], 2, 3, ['a', 'b', 'p', 'c'], 'g', 2][['q'], 2, 3, ['a', 'b', 'p', 'c'], 'g', 1]Failed
workspace regression 1[['q'], 0, 1, ['p', 'a', 'b', 'c'], 'g', 2][['q'], 0, 1, ['p', 'a', 'b', 'c'], 'g', 1]Failed
workspace regression 2[['q'], 3, 4, ['a', 'b', 'c', 'p'], 'g', 2][['q'], 3, 4, ['a', 'b', 'c', 'p'], 'g', 1]Failed
workspace regression 3[['q'], 0, 1, ['p'], 'g', 2][['q'], 0, 1, ['p'], 'g', 1]Failed
workspace regression 4[['q'], 2, 3, ['a', 'b', 'p', 'c'], None, 2][['q'], 2, 3, ['a', 'b', 'p', 'c'], None, 1]Failed
workspace regression 5[['p'], 2, 3, ['a', 'b', 'q', 'c'], 'g', 2][['p'], 2, 3, ['a', 'b', 'q', 'c'], 'g', 1]Failed

SHA-256 / 2de8050647226188073d53c571d3999dfb6dda0a8f03496395fb4c09f8a65a4e

2 / The unsuccessful fix

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

N = 1
observations = []
def solve(x):
    r0 = [t for t in x['pins'] if t!=x['unpin']]
    r1 = min(x['rank'],len(x['normal']))
    r2 = len(x['pins'])-1+min(x['rank'],len(x['normal']))
    r3 = x['normal'][:min(x['rank'],len(x['normal']))]+[x['unpin']]+x['normal'][min(x['rank'],len(x['normal'])):]
    r4 = x['saved_group'] if x['saved_group'] in x['groups'] else None
    r5 = 0
    return [r0,r1,r2,r3,r4,r5]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = {1: [({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c'], 'unpin': 'p', 'rank': 0, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 0, 1, ['p', 'a', 'b', 'c'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c'], 'unpin': 'p', 'rank': 9, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 3, 4, ['a', 'b', 'c', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': [], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 0, 1, ['p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c'], None, 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c'], 'unpin': 'q', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['p'], 2, 3, ['a', 'b', 'q', 'c'], 'g', 1])], 2: [({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0'], 'unpin': 'p', 'rank': 0, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 0, 1, ['p', 'a', 'b', 'c', 'extra0'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0'], 'unpin': 'p', 'rank': 9, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 4, 5, ['a', 'b', 'c', 'extra0', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['extra0'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 1, 2, ['extra0', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0'], None, 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0'], 'unpin': 'q', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['p'], 2, 3, ['a', 'b', 'q', 'c', 'extra0'], 'g', 1])], 3: [({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0', 'extra1'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1'], 'unpin': 'p', 'rank': 0, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 0, 1, ['p', 'a', 'b', 'c', 'extra0', 'extra1'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1'], 'unpin': 'p', 'rank': 9, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 5, 6, ['a', 'b', 'c', 'extra0', 'extra1', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['extra0', 'extra1'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['extra0', 'extra1', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0', 'extra1'], None, 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1'], 'unpin': 'q', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['p'], 2, 3, ['a', 'b', 'q', 'c', 'extra0', 'extra1'], 'g', 1])], 4: [({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0', 'extra1', 'extra2'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2'], 'unpin': 'p', 'rank': 0, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 0, 1, ['p', 'a', 'b', 'c', 'extra0', 'extra1', 'extra2'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2'], 'unpin': 'p', 'rank': 9, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 6, 7, ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['extra0', 'extra1', 'extra2'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['extra0', 'extra1', 'p', 'extra2'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0', 'extra1', 'extra2'], None, 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2'], 'unpin': 'q', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['p'], 2, 3, ['a', 'b', 'q', 'c', 'extra0', 'extra1', 'extra2'], 'g', 1])], 5: [({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'unpin': 'p', 'rank': 0, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 0, 1, ['p', 'a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'unpin': 'p', 'rank': 9, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 7, 8, ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['extra0', 'extra1', 'extra2', 'extra3'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['extra0', 'extra1', 'p', 'extra2', 'extra3'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], None, 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'unpin': 'q', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['p'], 2, 3, ['a', 'b', 'q', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'g', 1])]}
for i, (inputs, expected) in enumerate(fixtures[N]):
    check("workspace regression "+str(i), solve(inputs), 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
workspace regression 0[['q'], 2, 3, ['a', 'b', 'p', 'c'], 'g', 0][['q'], 2, 3, ['a', 'b', 'p', 'c'], 'g', 1]Failed
workspace regression 1[['q'], 0, 1, ['p', 'a', 'b', 'c'], 'g', 0][['q'], 0, 1, ['p', 'a', 'b', 'c'], 'g', 1]Failed
workspace regression 2[['q'], 3, 4, ['a', 'b', 'c', 'p'], 'g', 0][['q'], 3, 4, ['a', 'b', 'c', 'p'], 'g', 1]Failed
workspace regression 3[['q'], 0, 1, ['p'], 'g', 0][['q'], 0, 1, ['p'], 'g', 1]Failed
workspace regression 4[['q'], 2, 3, ['a', 'b', 'p', 'c'], None, 0][['q'], 2, 3, ['a', 'b', 'p', 'c'], None, 1]Failed
workspace regression 5[['p'], 2, 3, ['a', 'b', 'q', 'c'], 'g', 0][['p'], 2, 3, ['a', 'b', 'q', 'c'], 'g', 1]Failed

SHA-256 / 304abf59c907f17e7ef8b36aeeb41be6b80a92b0ed3db066a85d4fc2e4542602

3 / The verified repair

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

N = 1
observations = []
def solve(x):
    r0 = [t for t in x['pins'] if t!=x['unpin']]
    r1 = min(x['rank'],len(x['normal']))
    r2 = len(x['pins'])-1+min(x['rank'],len(x['normal']))
    r3 = x['normal'][:min(x['rank'],len(x['normal']))]+[x['unpin']]+x['normal'][min(x['rank'],len(x['normal'])):]
    r4 = x['saved_group'] if x['saved_group'] in x['groups'] else None
    r5 = len(x['pins'])-1
    return [r0,r1,r2,r3,r4,r5]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = {1: [({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c'], 'unpin': 'p', 'rank': 0, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 0, 1, ['p', 'a', 'b', 'c'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c'], 'unpin': 'p', 'rank': 9, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 3, 4, ['a', 'b', 'c', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': [], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 0, 1, ['p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c'], None, 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c'], 'unpin': 'q', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['p'], 2, 3, ['a', 'b', 'q', 'c'], 'g', 1])], 2: [({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0'], 'unpin': 'p', 'rank': 0, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 0, 1, ['p', 'a', 'b', 'c', 'extra0'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0'], 'unpin': 'p', 'rank': 9, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 4, 5, ['a', 'b', 'c', 'extra0', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['extra0'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 1, 2, ['extra0', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0'], None, 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0'], 'unpin': 'q', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['p'], 2, 3, ['a', 'b', 'q', 'c', 'extra0'], 'g', 1])], 3: [({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0', 'extra1'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1'], 'unpin': 'p', 'rank': 0, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 0, 1, ['p', 'a', 'b', 'c', 'extra0', 'extra1'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1'], 'unpin': 'p', 'rank': 9, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 5, 6, ['a', 'b', 'c', 'extra0', 'extra1', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['extra0', 'extra1'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['extra0', 'extra1', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0', 'extra1'], None, 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1'], 'unpin': 'q', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['p'], 2, 3, ['a', 'b', 'q', 'c', 'extra0', 'extra1'], 'g', 1])], 4: [({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0', 'extra1', 'extra2'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2'], 'unpin': 'p', 'rank': 0, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 0, 1, ['p', 'a', 'b', 'c', 'extra0', 'extra1', 'extra2'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2'], 'unpin': 'p', 'rank': 9, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 6, 7, ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['extra0', 'extra1', 'extra2'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['extra0', 'extra1', 'p', 'extra2'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0', 'extra1', 'extra2'], None, 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2'], 'unpin': 'q', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['p'], 2, 3, ['a', 'b', 'q', 'c', 'extra0', 'extra1', 'extra2'], 'g', 1])], 5: [({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'unpin': 'p', 'rank': 0, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 0, 1, ['p', 'a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'unpin': 'p', 'rank': 9, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 7, 8, ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3', 'p'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['extra0', 'extra1', 'extra2', 'extra3'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['q'], 2, 3, ['extra0', 'extra1', 'p', 'extra2', 'extra3'], 'g', 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'unpin': 'p', 'rank': 2, 'saved_group': 'g', 'groups': ['h']}, [['q'], 2, 3, ['a', 'b', 'p', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], None, 1]), ({'pins': ['p', 'q'], 'normal': ['a', 'b', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'unpin': 'q', 'rank': 2, 'saved_group': 'g', 'groups': ['g', 'h']}, [['p'], 2, 3, ['a', 'b', 'q', 'c', 'extra0', 'extra1', 'extra2', 'extra3'], 'g', 1])]}
for i, (inputs, expected) in enumerate(fixtures[N]):
    check("workspace regression "+str(i), solve(inputs), 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
workspace regression 0[['q'], 2, 3, ['a', 'b', 'p', 'c'], 'g', 1][['q'], 2, 3, ['a', 'b', 'p', 'c'], 'g', 1]Passed
workspace regression 1[['q'], 0, 1, ['p', 'a', 'b', 'c'], 'g', 1][['q'], 0, 1, ['p', 'a', 'b', 'c'], 'g', 1]Passed
workspace regression 2[['q'], 3, 4, ['a', 'b', 'c', 'p'], 'g', 1][['q'], 3, 4, ['a', 'b', 'c', 'p'], 'g', 1]Passed
workspace regression 3[['q'], 0, 1, ['p'], 'g', 1][['q'], 0, 1, ['p'], 'g', 1]Passed
workspace regression 4[['q'], 2, 3, ['a', 'b', 'p', 'c'], None, 1][['q'], 2, 3, ['a', 'b', 'p', 'c'], None, 1]Passed
workspace regression 5[['p'], 2, 3, ['a', 'b', 'q', 'c'], 'g', 1][['p'], 2, 3, ['a', 'b', 'q', 'c'], 'g', 1]Passed

SHA-256 / 8448d4219d7dddba55403fee9e8f51f14d563a6823c1cec56288ebed8a6b6345

Verification & scope

Finite stipulated workspace snapshots only. Independent result fields describe observable obligations, not a full UI runtime. 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 2026-09-29T14:42:47.501680+00:00.

Case digest / cfeb84406e479f84002251b024e4f305bab099cf18bf9b6a836c7a432863bd0f