Use strict type and source file scoring
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parent
6ff055b9ce
commit
02c0586b43
3 changed files with 194 additions and 3 deletions
15
scripts/patches/forgeguard_evmbench_source_path.patch
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15
scripts/patches/forgeguard_evmbench_source_path.patch
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@ -0,0 +1,15 @@
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diff --git a/scripts/run_evmbench.py b/scripts/run_evmbench.py
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--- a/scripts/run_evmbench.py
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+++ b/scripts/run_evmbench.py
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@@ -598,7 +598,13 @@ def run_benchmark(model, tokenizer, configs_dir, contracts_dir, use_processor=F
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)
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all_raw.append(raw)
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- all_findings.extend(findings)
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+ # Findings are produced per source file, but the legacy result
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+ # aggregated them without retaining that association.
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+ for finding in findings:
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+ finding_with_source = dict(finding)
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+ finding_with_source["source_path"] = sol_path
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+ all_findings.append(finding_with_source)
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if findings:
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detected = True
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@ -4,6 +4,7 @@ set -euo pipefail
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ROOT=/home/daniel/forgeguard
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PROJECT="$ROOT/project"
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ARTIFEX_ROOT=/home/daniel/Artifex
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DATA="$ROOT/artifex_dataset_versions/guard_curated_v03/training.json"
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RUN_ROOT="$PROJECT/artifex_overnight/guard3b_v03_overnight"
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CANARY=artifex-guard3b-v03-canary
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@ -16,24 +17,34 @@ mkdir -p "$RUN_ROOT"
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docker_run() {
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docker run --rm --gpus all --shm-size=16g \
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-v "$PROJECT:/workspace" \
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-v "$ARTIFEX_ROOT/scripts/score_evmbench_type_source_file.py:/workspace/artifex/score_evmbench_type_source_file.py:ro" \
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-v "$ROOT/artifex_dataset_versions:/workspace/artifex_dataset_versions" \
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-v /home/daniel/.cache/huggingface:/root/.cache/huggingface \
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"$IMAGE" "$@"
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}
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install_evaluator_contract() {
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if ! grep -q 'finding_with_source\["source_path"\]' "$PROJECT/scripts/run_evmbench.py"; then
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patch --batch --forward -d "$PROJECT" -p1 < "$ARTIFEX_ROOT/scripts/patches/forgeguard_evmbench_source_path.patch"
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fi
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}
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evaluate() {
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local name=$1 adapter=${2:-}
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local result="$RUN_ROOT/${name}_evmbench.json" score="$RUN_ROOT/${name}_strict.json"
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local args=(python /workspace/scripts/run_evmbench.py --model "$MODEL" --unsloth --save "/workspace/artifex_overnight/guard3b_v03_overnight/${name}_evmbench.json")
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if [[ -n "$adapter" ]]; then args+=(--adapter "/workspace/artifex_overnight/$adapter"); fi
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docker_run "${args[@]}" > "$RUN_ROOT/${name}_evaluation.log" 2>&1
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docker_run python /workspace/scripts/score_evmbench_strict.py "/workspace/artifex_overnight/guard3b_v03_overnight/${name}_evmbench.json" > "$score" 2>&1
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docker_run python /workspace/artifex/score_evmbench_type_source_file.py \
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"/workspace/artifex_overnight/guard3b_v03_overnight/${name}_evmbench.json" \
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--output "/workspace/artifex_overnight/guard3b_v03_overnight/${name}_strict.json" \
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> "$RUN_ROOT/${name}_scoring.log" 2>&1
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[[ -s "$result" && -s "$score" ]]
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}
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qwen_choice() {
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local summary
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summary=$(tail -c 10000 "$RUN_ROOT/base_strict.json" 2>/dev/null; tail -c 10000 "$RUN_ROOT/current_strict.json" 2>/dev/null || true)
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summary=$(jq -c '{acceptance_metric,summary:{targets,canonical_type_and_target_source_file_match}}' "$RUN_ROOT/base_strict.json"; jq -c '{acceptance_metric,summary:{targets,canonical_type_and_target_source_file_match}}' "$RUN_ROOT/current_strict.json")
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local body
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body=$(jq -n --arg prompt "You are MODEL_DIRECTOR for a bounded Guard 3B overnight run. Same-harness strict-score evidence follows: $summary Choose one JSON decision only: {\"action\":\"CONTINUE\"|\"REPLICATE\"|\"STOP\",\"rationale\":\"...\"}. CONTINUE means resume the current adapter with lower LR; REPLICATE means fresh seed from the immutable base; STOP means evidence/remaining time does not justify another run." '{model:"qwen38",messages:[{role:"user",content:$prompt}],temperature:0,max_tokens:200}')
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curl -fsS --max-time 180 http://127.0.0.1:8002/v1/chat/completions -H 'Content-Type: application/json' -d "$body" | jq -r '.choices[0].message.content' > "$RUN_ROOT/qwen_plan.json" || true
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@ -55,10 +66,11 @@ if [[ "$(cat "$RUN_ROOT/canary_exit_code.txt")" != "0" ]]; then
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exit 1
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fi
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cp "$PROJECT/artifex_overnight/guard3b_v03_canary/pilot_metrics.json" "$RUN_ROOT/canary_metrics.json"
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install_evaluator_contract
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# Base and the initial Challenger use the identical fixed harness/version.
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# Reuse a completed base result when resuming after an infrastructure repair.
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if [[ ! -s "$RUN_ROOT/base_evmbench.json" ]]; then evaluate base; else docker_run python /workspace/scripts/score_evmbench_strict.py "/workspace/artifex_overnight/guard3b_v03_overnight/base_evmbench.json" > "$RUN_ROOT/base_strict.json" 2>&1; fi
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if [[ ! -s "$RUN_ROOT/base_evmbench.json" ]]; then evaluate base; else docker_run python /workspace/artifex/score_evmbench_type_source_file.py "/workspace/artifex_overnight/guard3b_v03_overnight/base_evmbench.json" --output "/workspace/artifex_overnight/guard3b_v03_overnight/base_strict.json" > "$RUN_ROOT/base_scoring.log" 2>&1; fi
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cp "$RUN_ROOT/base_strict.json" "$RUN_ROOT/current_strict.json"
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CURRENT=guard3b_v03_canary
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evaluate canary "$CURRENT"
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164
scripts/score_evmbench_type_source_file.py
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164
scripts/score_evmbench_type_source_file.py
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@ -0,0 +1,164 @@
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#!/usr/bin/env python3
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"""Score EVMBench by canonical vulnerability type and patch-mapped source file.
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This is the acceptance scorer for the Guard 3B program. It deliberately does
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not score the legacy "any finding" detection rate. EVMBench's runnable issue
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inventory has a reviewed patch-mapped source file but no reviewed function or
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line anchor, so function/line accuracy is reported as unavailable rather than
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being guessed from model text.
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"""
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import argparse
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import json
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import re
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from pathlib import Path
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ROOT = Path(__file__).resolve().parent.parent
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DEFAULT_INVENTORY = ROOT / "docs" / "evmbench_runnable_issue_inventory.json"
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TYPE_ALIASES = {
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"reentrancy": "reentrancy",
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"re-entrancy": "reentrancy",
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"flash loan": "flash_loan",
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"flash_loan": "flash_loan",
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"oracle manipulation": "oracle_manipulation",
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"oracle_manipulation": "oracle_manipulation",
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"access control": "access_control",
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"access_control": "access_control",
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"integer overflow": "integer_overflow",
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"integer_overflow": "integer_overflow",
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"integer underflow": "integer_overflow",
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"front running": "front_running",
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"front-running": "front_running",
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"front_running": "front_running",
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"delegate call": "delegate_call",
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"delegatecall": "delegate_call",
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"delegate_call": "delegate_call",
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"logic error": "logic_error",
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"logic_error": "logic_error",
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}
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def read_json(path):
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with path.open(encoding="utf-8") as handle:
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return json.load(handle)
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def normalize_type(value):
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value = re.sub(r"[ _-]+", " ", str(value or "").strip().lower())
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return TYPE_ALIASES.get(value, "unknown")
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def normalize_path(value):
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return str(value or "").replace("\\", "/").strip("/").lower()
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def source_file_matches(reported_path, expected_paths):
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reported = normalize_path(reported_path)
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return bool(reported) and any(
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reported.endswith(normalize_path(expected)) for expected in expected_paths
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)
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def rate(count, total):
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return round(100 * count / total, 1) if total else 0
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def main():
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parser = argparse.ArgumentParser(
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description="Score canonical type plus patch-mapped target source file"
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)
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parser.add_argument("results", type=Path)
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parser.add_argument("--inventory", type=Path, default=DEFAULT_INVENTORY)
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parser.add_argument("--output", type=Path, required=True)
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args = parser.parse_args()
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result = read_json(args.results)
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inventory = read_json(args.inventory)
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records = result.get("vulnerabilities")
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if not isinstance(records, list):
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raise ValueError("results lacks per-vulnerability findings")
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by_key = {
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f"{record.get('audit_id')}:{record.get('vuln_id')}": record
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for record in records
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}
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rows = []
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missing_source_path = 0
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for issue in inventory.get("issues", []):
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key = f"{issue['audit_id']}:{issue['vulnerability_id']}"
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record = by_key.get(key, {})
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expected_paths = [
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source["path"] for source in issue.get("source_files", [])
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if source.get("exists")
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]
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findings = record.get("findings", [])
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if not isinstance(findings, list):
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findings = []
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annotated = []
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for finding in findings:
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source_path = finding.get("source_path", "")
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if not source_path:
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missing_source_path += 1
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type_match = normalize_type(finding.get("type")) == issue["canonical_type"]
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file_match = source_file_matches(source_path, expected_paths)
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annotated.append({
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"reported_type": finding.get("type", ""),
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"normalized_type": normalize_type(finding.get("type")),
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"reported_source_path": source_path,
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"reported_location": finding.get("location", ""),
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"canonical_type_match": type_match,
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"target_source_file_match": file_match,
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"canonical_type_and_target_source_file_match": type_match and file_match,
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})
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rows.append({
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"target": key,
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"canonical_type": issue["canonical_type"],
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"expected_source_files": expected_paths,
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"any_finding": bool(findings),
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"canonical_type_match": any(item["canonical_type_match"] for item in annotated),
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"canonical_type_and_target_source_file_match": any(
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item["canonical_type_and_target_source_file_match"]
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for item in annotated
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),
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"findings": annotated,
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})
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total = len(rows)
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canonical_count = sum(row["canonical_type_match"] for row in rows)
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strict_count = sum(
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row["canonical_type_and_target_source_file_match"] for row in rows
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)
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artifact = {
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"schema_version": 1,
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"scorer": "score_evmbench_type_source_file.py",
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"input_result": str(args.results),
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"inventory": str(args.inventory),
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"acceptance_metric": "canonical_type_and_target_source_file_match",
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"metric_definition": (
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"A finding must match the inventory canonical type and be produced "
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"while evaluating an inventory patch-mapped target source file."
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),
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"location_label_coverage": "target source file only; reviewed function/line anchors are unavailable",
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"summary": {
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"targets": total,
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"canonical_type_match": {"count": canonical_count, "rate_percent": rate(canonical_count, total)},
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"canonical_type_and_target_source_file_match": {
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"count": strict_count,
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"rate_percent": rate(strict_count, total),
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},
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},
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"validation": {
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"findings_missing_source_path": missing_source_path,
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"legacy_any_finding_excluded_from_acceptance": True,
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},
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"rows": rows,
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}
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args.output.parent.mkdir(parents=True, exist_ok=True)
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with args.output.open("w", encoding="utf-8") as handle:
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json.dump(artifact, handle, indent=2)
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handle.write("\n")
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print(json.dumps(artifact["summary"], sort_keys=True))
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if __name__ == "__main__":
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main()
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