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e32391fd85
(cherry picked from commit 633cdbc94e7a7b0c5d3b0b135189faf3de6673f4) Reconcile-port: handler_admin.py hunks redirected into cloud/server.py _audit_scorecard (target keeps 6-mixin split; scorecard module itself applied cleanly).
524 lines
25 KiB
Python
524 lines
25 KiB
Python
"""7 维项目级审计评分卡（纯函数、标准库 only）。
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定位：这是一个评分卡，不是门禁、不是审计、不是自动循环。
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它不重写 metrics、arch_conformance、ledger、audit_loop 的逻辑，
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只接受调用方显式传入的结构化证据，算出 7 维各自的分数。
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计分规则（钉死，不可改为平均分达标）：
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- 每维分数 0-10，保留一位小数；>=9 通过，<9 不通过。
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- 总体结论：7 维全部 >=9 才算达标（overall="pass"）。
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任一维 <9，总体就不达标（overall="not_pass"）。
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- 平均分只作参考信息（average_score），绝不能作为达标依据。
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代码里把“平均分达标”写成明确的不通过路径并加测试钉住：
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例如 6 维 10 分、1 维 4 分，平均 9.1 分，总体仍是不达标。
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- 未知处理：任何一维的数据源缺失、未知、未验证，
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该维分数记为 None（未知），不记 0、不记 10、不估算，
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总体直接不达标，并列出缺失项（missing_items）。
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“没数据”既不算通过，也不算 0 分去拉低平均分后又用平均分糊弄。
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- 未实测处理：调用方传入“夹具模拟”“视口替代”“未编译端代码评审”
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这类证据时，该项记为“未实测”（untested_items），而不是“通过”。
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若某维的关键证据全部是未实测，该维记为 None。
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- 阈值：DEFAULT_THRESHOLDS 全部标注 source="test_default_unapproved"
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（测试默认值、未拍板）。生产阈值须用户拍板后，由调用方显式
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传入 thresholds（含 source="user_approved"）才能替换默认值。
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本模块绝不把测试初值写成生产值。
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- 与已定语义的关系（本模块不改它们）：
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#238 evaluate_feedback 的 auto_apply 保持 False；
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#247 纠正为 pass 本身不解封；
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#244 CONDITIONAL 先映射为 fail 再记（本模块只接受已映射的结论，
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若调用方传入 verdict="conditional"，记为未实测/无效证据，不算通过）。
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7 维定义（不要擅自增维、减维、改名换义）：
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1. delivery_quality 交付质量
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2. gate_audit 门禁与审计有效性
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3. arch_contract 架构与契约一致性
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4. test_coverage 测试与验证覆盖
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5. security_ledger 安全与账本可信
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6. cost_quota 成本与配额可观测
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7. ops_scale 生产运维与规模
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10 维到 7 维的合并映射（写进文档，也写在这里）：
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- 流程完整性并入门禁与审计有效性（G0-G8 最终靠门禁和重审证明）；
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- 自动化程度并入门禁与审计有效性 + 生产运维与规模
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（自动化的证据就是自动循环是否真实跑通、真实 App 是否安装）；
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- 文档与技能并入架构与契约一致性
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（技能文本、附录溯源、移植规则最终都是契约一致性的一部分）。
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输入格式：build_scorecard(evidence, thresholds=None)
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evidence: dict，键为上面 7 个维 id，值为该维的证据 dict。
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每个维的证据字段见各 _score_* 函数的 docstring。
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调用方必须带来源、时间、检查名；本模块不自动从测试文件、
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摘要文档、PR 描述里拼凑分数。
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"""
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from __future__ import annotations
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PASS_SCORE = 9.0
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DIMENSIONS = [
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("delivery_quality", "交付质量"),
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("gate_audit", "门禁与审计有效性"),
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("arch_contract", "架构与契约一致性"),
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("test_coverage", "测试与验证覆盖"),
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("security_ledger", "安全与账本可信"),
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("cost_quota", "成本与配额可观测"),
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("ops_scale", "生产运维与规模"),
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]
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DIMENSION_IDS = [d[0] for d in DIMENSIONS]
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# 阈值表：每一项都带 source，默认值一律是测试初值、未拍板。
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# “9 分线”是达到 9 分的下限，“10 分线”是达到 10 分的下限，
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# “floor”是低于该值后分数进入 0-5 区间的参考点（不是达标线）。
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# 这些数值本身不是生产标准；生产阈值须用户拍板后显式传入。
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DEFAULT_THRESHOLDS = {
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"defect_rate_nine": {"value": 0.05, "source": "test_default_unapproved"},
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"defect_rate_ten": {"value": 0.02, "source": "test_default_unapproved"},
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"defect_rate_floor": {"value": 0.20, "source": "test_default_unapproved"},
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"first_pass_nine": {"value": 0.90, "source": "test_default_unapproved"},
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"first_pass_ten": {"value": 0.95, "source": "test_default_unapproved"},
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"first_pass_floor": {"value": 0.50, "source": "test_default_unapproved"},
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"rework_rate_nine": {"value": 0.10, "source": "test_default_unapproved"},
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"rework_rate_ten": {"value": 0.05, "source": "test_default_unapproved"},
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"rework_rate_floor": {"value": 0.50, "source": "test_default_unapproved"},
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"overturn_rate_floor": {"value": 0.30, "source": "test_default_unapproved"},
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"coverage_nine": {"value": 0.85, "source": "test_default_unapproved"},
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"coverage_ten": {"value": 0.90, "source": "test_default_unapproved"},
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"coverage_floor": {"value": 0.75, "source": "test_default_unapproved"},
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"sampling_normal": {"value": 0.10, "source": "test_default_unapproved"},
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"sampling_critical": {"value": 0.50, "source": "test_default_unapproved"},
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"parallel_scale_target": {"value": 40, "source": "test_default_unapproved"},
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}
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UNTESTED_KINDS = {"fixture", "viewport_substitute", "code_review_only",
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"fixture_simulated", "dry_run", "estimated"}
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def _thresholds_source(thresholds):
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"""阈值来源：只有调用方显式传入 user_approved 才算已拍板。"""
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if not thresholds:
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return "test_default_unapproved"
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sources = set()
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for entry in thresholds.values():
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if isinstance(entry, dict):
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sources.add(entry.get("source", "test_default_unapproved"))
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else:
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sources.add("test_default_unapproved")
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if sources == {"user_approved"}:
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return "user_approved"
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return "test_default_unapproved"
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def _t(thresholds, key):
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if thresholds and key in thresholds:
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entry = thresholds[key]
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if isinstance(entry, dict):
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return entry["value"]
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return entry
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return DEFAULT_THRESHOLDS[key]["value"]
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def _round1(value):
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return round(float(value) + 1e-9, 1)
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def _score_higher(value, nine, ten, floor):
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"""越高越好：floor->5 分，nine->9 分，ten->10 分，分段线性，低于 floor 按比例。"""
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if value is None:
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return None
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v = float(value)
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if v >= ten:
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return 10.0
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if v >= nine:
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return 9.0 + (v - nine) / (ten - nine) if ten > nine else 10.0
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if v >= floor:
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return 5.0 + 4.0 * (v - floor) / (nine - floor) if nine > floor else 5.0
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if floor > 0:
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return max(0.0, 5.0 * v / floor)
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return 0.0
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def _score_lower(value, ten, nine, floor):
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"""越低越好：ten->10 分，nine->9 分，floor->5 分，低于 ten 满分，高于 floor 递减。"""
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if value is None:
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return None
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v = float(value)
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if v <= ten:
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return 10.0
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if v <= nine:
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return 9.0 + (nine - v) / (nine - ten) if nine > ten else 10.0
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if v <= floor:
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return 5.0 + 4.0 * (floor - v) / (floor - nine) if floor > nine else 5.0
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return max(0.0, 5.0 * floor / v) if v > 0 else 0.0
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def _result(dim_id, score, basis, missing, untested):
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if score is None:
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status = "unknown"
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elif score >= PASS_SCORE:
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status = "pass"
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else:
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status = "fail"
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return {
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"id": dim_id,
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"score": _round1(score) if score is not None else None,
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"status": status,
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"basis": basis,
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"missing_items": missing,
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"untested_items": untested,
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}
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def _score_delivery(ev, th):
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"""证据：first_pass_rate, defect_rate, rework_rate,
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first_pass_known, defect_known, rework_known, attempts_present,
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evidence_kind（"real" 以外若为 estimated/fixture 则记未实测）。"""
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missing, untested, basis = [], [], []
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for key in ("first_pass_rate", "defect_rate", "rework_rate"):
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if ev.get(key) is None:
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missing.append(key)
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for key in ("first_pass_known", "defect_known", "rework_known"):
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if not ev.get(key):
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missing.append(key + "_not_known")
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if not ev.get("attempts_present"):
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missing.append("attempts_present_false_or_missing")
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kind = ev.get("evidence_kind")
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if kind in UNTESTED_KINDS:
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untested.append("metrics_evidence_kind=%s" % kind)
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if missing or untested:
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return _result("delivery_quality", None, basis, missing, untested)
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subs = [
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("first_pass_rate", _score_higher(ev["first_pass_rate"],
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_t(th, "first_pass_nine"),
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_t(th, "first_pass_ten"),
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_t(th, "first_pass_floor"))),
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("defect_rate", _score_lower(ev["defect_rate"],
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_t(th, "defect_rate_ten"),
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_t(th, "defect_rate_nine"),
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_t(th, "defect_rate_floor"))),
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("rework_rate", _score_lower(ev["rework_rate"],
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_t(th, "rework_rate_ten"),
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_t(th, "rework_rate_nine"),
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_t(th, "rework_rate_floor"))),
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]
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for name, sub in subs:
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basis.append("%s=%s -> %.1f" % (name, ev[name], sub))
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return _result("delivery_quality", min(s for _, s in subs), basis, missing, untested)
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def _score_gate(ev, th):
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"""证据：hard_gate_enforced（bool/None）、gate_items_passed、
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gate_items_total、merge_blocked_verified、loop_end_to_end_verified、
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sampling_misjudgment_rate（None 表示未抽查/未知）、
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audit_verdict（"conditional" 记无效证据，不算通过）。"""
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missing, untested, basis = [], [], []
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if ev.get("hard_gate_enforced") is None:
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missing.append("hard_gate_enforced_unknown")
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if ev.get("gate_items_passed") is None or ev.get("gate_items_total") is None:
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missing.append("gate_items_passed_or_total_missing")
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if ev.get("audit_verdict") == "conditional":
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untested.append("audit_verdict=conditional_not_a_pass")
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if ev.get("evidence_kind") in UNTESTED_KINDS:
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untested.append("gate_evidence_kind=%s" % ev["evidence_kind"])
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if missing or untested:
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return _result("gate_audit", None, basis, missing, untested)
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if not ev.get("hard_gate_enforced"):
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basis.append("hard_gate_enforced=False（record 模式）：已知未强制，分数封顶 4.0")
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return _result("gate_audit", 4.0, basis, missing, untested)
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total = ev["gate_items_total"]
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passed = ev["gate_items_passed"]
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rate = passed / total if total else 0.0
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sub_gate = _score_higher(rate, 0.99, 1.0, 0.80)
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basis.append("gate_items %s/%s=%.3f -> %.1f" % (passed, total, rate, sub_gate))
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subs = [sub_gate]
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if not ev.get("merge_blocked_verified"):
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basis.append("merge_blocked_verified=False：合并阻塞未真实验证，分数封顶 4.0")
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return _result("gate_audit", 4.0, basis, missing, untested)
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if not ev.get("loop_end_to_end_verified"):
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basis.append("loop_end_to_end_verified=False：自动循环端到端未真实验证，分数封顶 4.0")
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return _result("gate_audit", 4.0, basis, missing, untested)
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mis = ev.get("sampling_misjudgment_rate")
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if mis is None:
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missing.append("sampling_misjudgment_rate_unknown")
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return _result("gate_audit", None, basis, missing, untested)
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sub_mis = _score_lower(mis, 0.0, 0.02, _t(th, "overturn_rate_floor"))
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basis.append("sampling_misjudgment_rate=%s -> %.1f" % (mis, sub_mis))
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subs.append(sub_mis)
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return _result("gate_audit", min(subs), basis, missing, untested)
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def _score_arch(ev, th):
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"""证据：contract_frozen、arch_violations、directory_violations、
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import_violations、stack_changed_without_approval（bool/None）。"""
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missing, untested, basis = [], [], []
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for key in ("arch_violations", "directory_violations", "import_violations"):
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if ev.get(key) is None:
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missing.append(key + "_unknown")
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if ev.get("contract_frozen") is None:
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missing.append("contract_frozen_unknown")
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if missing:
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return _result("arch_contract", None, basis, missing, untested)
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total_violations = (ev["arch_violations"] + ev["directory_violations"]
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+ ev["import_violations"])
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basis.append("violations total=%s (arch=%s dir=%s import=%s)"
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% (total_violations, ev["arch_violations"],
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ev["directory_violations"], ev["import_violations"]))
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if not ev.get("contract_frozen"):
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basis.append("contract_frozen=False：已知未冻结，分数封顶 4.0")
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return _result("arch_contract", 4.0, basis, missing, untested)
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if ev.get("stack_changed_without_approval"):
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basis.append("stack_changed_without_approval=True：分数封顶 4.0")
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return _result("arch_contract", 4.0, basis, missing, untested)
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if total_violations > 0:
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basis.append("violations>0：分数封顶 5.0")
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return _result("arch_contract", 5.0, basis, missing, untested)
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return _result("arch_contract", 10.0, basis, missing, untested)
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def _score_test(ev, th):
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"""证据：prd_coverage_rate、agent_six_complete、cross_matrix_coverage_rate、
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coverage_pct、lint_items、mypy_items、bandit_high、
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cross_matrix_kind（"real" 以外记未实测）、real_pg（bool）、
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real_service（bool）。"""
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missing, untested, basis = [], [], []
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for key in ("prd_coverage_rate", "cross_matrix_coverage_rate", "coverage_pct"):
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if ev.get(key) is None:
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missing.append(key + "_missing")
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kind = ev.get("cross_matrix_kind")
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if kind in UNTESTED_KINDS or kind in ("viewport_substitute", "code_review_only"):
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untested.append("cross_matrix_kind=%s" % kind)
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if kind is not None and kind != "real":
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untested.append("cross_matrix_not_real")
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if not ev.get("real_pg"):
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untested.append("real_pg_not_verified")
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if not ev.get("real_service"):
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untested.append("real_service_not_verified")
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if missing or untested:
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return _result("test_coverage", None, basis, missing, untested)
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if not ev.get("agent_six_complete"):
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basis.append("agent_six_complete=False：agent 专属六项缺项，分数封顶 4.0")
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return _result("test_coverage", 4.0, basis, missing, untested)
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subs = [
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("prd_coverage_rate", _score_higher(ev["prd_coverage_rate"], 0.99, 1.0, 0.80)),
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("cross_matrix_coverage_rate", _score_higher(ev["cross_matrix_coverage_rate"], 0.99, 1.0, 0.80)),
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("coverage_pct", _score_higher(ev["coverage_pct"],
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_t(th, "coverage_nine"),
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_t(th, "coverage_ten"),
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_t(th, "coverage_floor"))),
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]
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for name, sub in subs:
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basis.append("%s=%s -> %.1f" % (name, ev[name], sub))
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# 静态检查：数值缺失记缺失，不估算；有值时，>0 即封顶（9 分线要求接近清零）。
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for key in ("lint_items", "mypy_items", "bandit_high"):
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if ev.get(key) is None:
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missing.append(key + "_missing")
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if missing:
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return _result("test_coverage", None, basis, missing, untested)
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static_total = ev["lint_items"] + ev["mypy_items"] + ev["bandit_high"]
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basis.append("static total lint=%s mypy=%s bandit_high=%s"
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% (ev["lint_items"], ev["mypy_items"], ev["bandit_high"]))
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if static_total > 0:
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basis.append("static_total>0：分数封顶 8.0（静态检查未接近清零）")
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return _result("test_coverage", min(8.0, min(s for _, s in subs)), basis, missing, untested)
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return _result("test_coverage", min(s for _, s in subs), basis, missing, untested)
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def _score_security(ev, th):
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"""证据：ledger_verify_ok（bool/None）、ledger_coverage_rate、
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shell_whitelist_pass_rate、branch_protection
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（"protected"/"unprotected"/"unknown"/None）、anchor_check_recent。"""
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missing, untested, basis = [], [], []
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if ev.get("ledger_verify_ok") is None:
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missing.append("ledger_verify_ok_unknown")
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if ev.get("ledger_coverage_rate") is None:
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missing.append("ledger_coverage_rate_missing")
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bp = ev.get("branch_protection")
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if bp is None or bp == "unknown":
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missing.append("branch_protection_unknown")
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if missing:
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return _result("security_ledger", None, basis, missing, untested)
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if bp == "unprotected":
|
||
basis.append("branch_protection=unprotected：已知未保护，分数封顶 4.0")
|
||
return _result("security_ledger", 4.0, basis, missing, untested)
|
||
if not ev.get("ledger_verify_ok"):
|
||
basis.append("ledger_verify_ok=False：账本校验未通过，分数封顶 4.0")
|
||
return _result("security_ledger", 4.0, basis, missing, untested)
|
||
subs = [_score_higher(ev["ledger_coverage_rate"], 0.99, 1.0, 0.80)]
|
||
basis.append("ledger_coverage_rate=%s -> %.1f" % (ev["ledger_coverage_rate"], subs[0]))
|
||
rate = ev.get("shell_whitelist_pass_rate")
|
||
if rate is not None:
|
||
sub = _score_higher(rate, 0.99, 1.0, 0.80)
|
||
subs.append(sub)
|
||
basis.append("shell_whitelist_pass_rate=%s -> %.1f" % (rate, sub))
|
||
if not ev.get("anchor_check_recent"):
|
||
basis.append("anchor_check_recent=False：锚点定期校验未落地，分数封顶 8.0")
|
||
return _result("security_ledger", min(8.0, min(subs)), basis, missing, untested)
|
||
return _result("security_ledger", min(subs), basis, missing, untested)
|
||
|
||
|
||
def _score_cost(ev, th):
|
||
"""证据：cost_records_complete（bool）、unpriced_as_zero（bool，
|
||
True 即违规）、per_creator_present、quota_cutoff_verified、
|
||
thresholds_approved（bool，仅影响阈值来源标注，不封顶分数）。"""
|
||
missing, untested, basis = [], [], []
|
||
if not ev.get("cost_records_complete"):
|
||
missing.append("cost_records_complete_false_or_missing"
|
||
"（turns/llm_requests/usd_micros 缺失）")
|
||
if ev.get("unpriced_as_zero") is None:
|
||
missing.append("unpriced_as_zero_unknown")
|
||
if missing:
|
||
return _result("cost_quota", None, basis, missing, untested)
|
||
if ev.get("unpriced_as_zero"):
|
||
basis.append("unpriced_as_zero=True：无价记成 0/免费，分数封顶 0.0")
|
||
return _result("cost_quota", 0.0, basis, missing, untested)
|
||
if not ev.get("quota_cutoff_verified"):
|
||
basis.append("quota_cutoff_verified=False：配额硬切断未真实验证，分数封顶 4.0")
|
||
return _result("cost_quota", 4.0, basis, missing, untested)
|
||
if not ev.get("per_creator_present"):
|
||
basis.append("per_creator_present=False：按创建者成本未落地，分数封顶 8.0")
|
||
return _result("cost_quota", 8.0, basis, missing, untested)
|
||
basis.append("cost_records_complete=True, quota_cutoff_verified=True, "
|
||
"per_creator_present=True, unpriced_as_zero=False")
|
||
return _result("cost_quota", 10.0, basis, missing, untested)
|
||
|
||
|
||
def _score_ops(ev, th):
|
||
"""证据：ci_green_rate（None 表示 CI 未绿/未知）、deploy_success_rate、
|
||
rollback_drill_done、ha_status
|
||
（"second_host"/"single_host_accepted"/"single_host_unaccepted"/None）、
|
||
parallel_scale_proven（int/None）、parallel_scale_accepted_alternative（bool）。"""
|
||
missing, untested, basis = [], [], []
|
||
if ev.get("ci_green_rate") is None:
|
||
missing.append("ci_green_rate_unknown（CI 未绿或未统计）")
|
||
if ev.get("rollback_drill_done") is None:
|
||
missing.append("rollback_drill_done_unknown")
|
||
ha = ev.get("ha_status")
|
||
if ha is None:
|
||
missing.append("ha_status_unknown")
|
||
if missing:
|
||
return _result("ops_scale", None, basis, missing, untested)
|
||
if not ev.get("rollback_drill_done"):
|
||
basis.append("rollback_drill_done=False：回滚演练未真实跑过，分数封顶 4.0")
|
||
return _result("ops_scale", 4.0, basis, missing, untested)
|
||
subs = [_score_higher(ev["ci_green_rate"], 0.99, 1.0, 0.80)]
|
||
basis.append("ci_green_rate=%s -> %.1f" % (ev["ci_green_rate"], subs[0]))
|
||
if ev.get("deploy_success_rate") is not None:
|
||
sub = _score_higher(ev["deploy_success_rate"], 0.99, 1.0, 0.80)
|
||
subs.append(sub)
|
||
basis.append("deploy_success_rate=%s -> %.1f" % (ev["deploy_success_rate"], sub))
|
||
if ha == "single_host_unaccepted":
|
||
basis.append("ha_status=single_host_unaccepted：分数封顶 5.0")
|
||
return _result("ops_scale", 5.0, basis, missing, untested)
|
||
proven = ev.get("parallel_scale_proven")
|
||
target = _t(th, "parallel_scale_target")
|
||
if proven is None and not ev.get("parallel_scale_accepted_alternative"):
|
||
missing.append("parallel_scale_proven_unknown")
|
||
return _result("ops_scale", None, basis, missing, untested)
|
||
if proven is not None:
|
||
sub = _score_higher(min(proven, target) / target if target else 0,
|
||
0.99, 1.0, 0.5)
|
||
# 规模是离散证据：40 人满分，18 人约 4.5 分，上面线性公式在
|
||
# 0.5-1.0 区间给出 5-10 分，与“18 人约 4.5”不一致，故直接用比例*10。
|
||
sub = _round1(10.0 * min(proven, target) / target) if target else 0.0
|
||
subs.append(sub)
|
||
basis.append("parallel_scale_proven=%s target=%s -> %.1f"
|
||
% (proven, target, sub))
|
||
return _result("ops_scale", min(subs), basis, missing, untested)
|
||
|
||
|
||
_SCORERS = {
|
||
"delivery_quality": _score_delivery,
|
||
"gate_audit": _score_gate,
|
||
"arch_contract": _score_arch,
|
||
"test_coverage": _score_test,
|
||
"security_ledger": _score_security,
|
||
"cost_quota": _score_cost,
|
||
"ops_scale": _score_ops,
|
||
}
|
||
|
||
|
||
def build_scorecard(evidence, thresholds=None):
|
||
"""算出 7 维评分卡。evidence 缺键按空证据处理（该维记 None）。"""
|
||
evidence = evidence or {}
|
||
th = thresholds or {}
|
||
dimensions = []
|
||
missing_all, untested_all = [], []
|
||
for dim_id, _name in DIMENSIONS:
|
||
result = _SCORERS[dim_id](evidence.get(dim_id) or {}, th)
|
||
dimensions.append(result)
|
||
missing_all.extend("%s: %s" % (dim_id, m) for m in result["missing_items"])
|
||
untested_all.extend("%s: %s" % (dim_id, u) for u in result["untested_items"])
|
||
scores = [d["score"] for d in dimensions if d["score"] is not None]
|
||
average = _round1(sum(scores) / len(scores)) if scores else None
|
||
# 总体规则钉死：平均分绝不能作为达标依据。
|
||
overall_pass = all(d["score"] is not None and d["score"] >= PASS_SCORE
|
||
for d in dimensions)
|
||
return {
|
||
"dimensions": dimensions,
|
||
"average_score": average,
|
||
"average_is_not_pass_criterion": True,
|
||
"overall": "pass" if overall_pass else "not_pass",
|
||
"overall_pass": overall_pass,
|
||
"pass_score": PASS_SCORE,
|
||
"missing_items": missing_all,
|
||
"untested_items": untested_all,
|
||
"thresholds_source": _thresholds_source(th),
|
||
"thresholds": {k: v for k, v in DEFAULT_THRESHOLDS.items()},
|
||
}
|
||
|
||
|
||
def example_scorecard_as_of_2026_10_31():
|
||
"""2026-10-31 快照示例卡（历史示例，不是当前系统得分）。
|
||
|
||
证据是本函数 2026-10-31 落笔时记录的快照值（生产 v0.2、
|
||
main aebc623、覆盖率 0.7787 等），此后未重新实测；调用方
|
||
绝不能把它读成当前系统得分。要当前分数，须显式把新证据
|
||
传给 build_scorecard()。凡是只到 PR、未合并部署、未真实
|
||
验证的，在这里都记为未知或已知未强制，不估算、不写成
|
||
判断分。阈值仍为测试默认值
|
||
（source="test_default_unapproved"），未拍板。
|
||
总体结论必然是不达标。
|
||
"""
|
||
evidence = {
|
||
"delivery_quality": {
|
||
"first_pass_rate": None, "defect_rate": None, "rework_rate": None,
|
||
"first_pass_known": False, "defect_known": False,
|
||
"rework_known": False, "attempts_present": False,
|
||
},
|
||
"gate_audit": {
|
||
"hard_gate_enforced": False, "gate_items_passed": 0,
|
||
"gate_items_total": 5, "merge_blocked_verified": False,
|
||
"loop_end_to_end_verified": False,
|
||
"sampling_misjudgment_rate": None,
|
||
},
|
||
"arch_contract": {
|
||
"contract_frozen": None, "arch_violations": None,
|
||
"directory_violations": None, "import_violations": None,
|
||
},
|
||
"test_coverage": {
|
||
"prd_coverage_rate": None, "cross_matrix_coverage_rate": None,
|
||
"coverage_pct": 0.7787, "cross_matrix_kind": "viewport_substitute",
|
||
"real_pg": False, "real_service": False,
|
||
"agent_six_complete": True,
|
||
"lint_items": 109, "mypy_items": 0, "bandit_high": 4,
|
||
},
|
||
"security_ledger": {
|
||
"ledger_verify_ok": None, "ledger_coverage_rate": None,
|
||
"branch_protection": "unknown",
|
||
},
|
||
"cost_quota": {
|
||
"cost_records_complete": False, "unpriced_as_zero": False,
|
||
"per_creator_present": False, "quota_cutoff_verified": False,
|
||
},
|
||
"ops_scale": {
|
||
"ci_green_rate": None, "rollback_drill_done": False,
|
||
"ha_status": "single_host_unaccepted",
|
||
"parallel_scale_proven": 18,
|
||
},
|
||
}
|
||
report = build_scorecard(evidence)
|
||
report["evidence_as_of"] = "2026-10-31"
|
||
report["evidence_kind"] = "historical_example_snapshot"
|
||
report["not_current_system_score"] = True
|
||
return report
|