⚡ Bolt: [O(N^2) 병목 개선] SARIF 변환 규칙 인덱스 조회 성능 최적화

.jules/bolt.md

@@ -77,3 +77,7 @@
 ## 2024-11-20 - Optimize multiple tuple generation from a single collection
 **Learning:** `build_rule_metadata` derives exactly two collections, `owasp` and `cwe`, from the same references. Replacing its two generator traversals with one explicit loop reduces element visits from about 2N to N. Both versions remain O(N), so this is a constant-factor optimization rather than an asymptotic complexity improvement.
 **Action:** Combine repeated traversal when fixed derived collections share one source, while preserving ordering and classification semantics. Benchmark the production hot path before claiming a material wall-clock improvement.
+
+## 2024-12-10 - O(N^2) Performance from list(dict).index(key)
+**Learning:** Using `list(dict).index(key)` inside loops introduces significant performance overhead, effectively transforming an O(1) dictionary key check into an O(N^2) bottleneck. This requires creating a new list allocation and scanning it linearly for every loop iteration.
+**Action:** When determining the insertion index or position of dictionary keys during list processing, avoid generating lists. Track indices dynamically in a separate companion dictionary mapping the key to its incremental sequence length or insertion order index (e.g. `rule_indices[rule_id] = len(rules)`) for an O(1) constant-time lookup.

appguardrail_core/sarif.py

@@ -39,12 +39,14 @@ def findings_to_sarif(
     normalized = normalize_findings(findings)
 
     rules: dict[str, dict[str, Any]] = {}
+    rule_indices: dict[str, int] = {}
     results: list[dict[str, Any]] = []
     for f in normalized:
         rule_id = f["rule_id"]
         severity = f["severity"]
         refs = f.get("references") or ()
         if rule_id not in rules:
+            rule_idx = len(rules)
             rule: dict[str, Any] = {
                 "id": rule_id,
                 "name": rule_id,
@@ -64,11 +66,14 @@ def findings_to_sarif(
                 },
             }
             rules[rule_id] = rule
+            rule_indices[rule_id] = rule_idx
+        else:
+            rule_idx = rule_indices[rule_id]
 
         results.append(
             {
                 "ruleId": rule_id,
-                "ruleIndex": list(rules).index(rule_id),
+                "ruleIndex": rule_idx,
                 "level": _LEVEL.get(severity, "note"),
                 "message": {"text": f["message"].strip()},
                 "locations": [