feat(audit): implement Phase 5 CFE + Phase 6 Decomposition Cost (11 tasks)
Phase 5 CFE: detect_frequency_from_entry_point + 6 caller sets (INIT/HOT/PER_TURN/COLD/PER_DISCUSSION/PER_REQUEST), load_frequency_overrides (tomllib), estimate_call_frequency with 3-tier precedence (override > entry-point > unknown). Phase 6 Decomposition Cost: 6 cost-model constants (per spec 7.5), per_call_cost_us formula, FREQUENCY_MULTIPLIER (7 frequencies), current_total_us, componentize_factor lookup, unify_factor lookup, recommended_direction (5-step precedence with frozen whole_struct -> hold override), generate_rationale auto-string, and compute_decomposition_cost main entry. 33 new unit tests passing (Phase 5: 11, Phase 6: 22). 96 total tests passing. Phase 7 (Cross-audit integration) next.
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@@ -42,6 +42,23 @@ from src.code_path_audit import (
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is_bulk_batched_access,
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dominant_pattern,
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detect_access_pattern,
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detect_frequency_from_entry_point,
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load_frequency_overrides,
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estimate_call_frequency,
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MICROSECOND_BUDGET_PER_LLM_TURN,
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BRANCH_DISPATCH_OVERHEAD_US,
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ALLOCATION_OVERHEAD_US,
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DEAD_FIELD_COST_PER_FIELD_US,
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COMPONENTIZATION_INDIRECTION_US,
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UNIFICATION_INDIRECTION_US,
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per_call_cost_us,
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FREQUENCY_MULTIPLIER,
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current_total_us,
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componentize_factor,
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unify_factor,
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recommended_direction,
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generate_rationale,
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compute_decomposition_cost,
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)
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from src.result_types import Result, ErrorInfo, ErrorKind
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@@ -608,4 +625,217 @@ def test_detect_access_pattern_mixed() -> None:
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"""detect_access_pattern returns 'mixed' when no pattern dominates (2+ distinct keys but <3)."""
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counts: Counter[str] = Counter({"a": 1, "b": 1})
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pattern = detect_access_pattern(counts, has_direct_access=False)
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assert pattern == "mixed"
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assert pattern == "mixed"
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def test_detect_frequency_init() -> None:
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"""detect_frequency_from_entry_point returns 'init' for functions called from __init__."""
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freq = detect_frequency_from_entry_point(caller="__init__", caller_class="App")
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assert freq == "init"
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def test_detect_frequency_hot() -> None:
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"""detect_frequency_from_entry_point returns 'hot' for functions called from render loops."""
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freq = detect_frequency_from_entry_point(caller="render_main_toolbar", caller_class="App")
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assert freq == "hot"
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def test_detect_frequency_per_turn() -> None:
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"""detect_frequency_from_entry_point returns 'per_turn' for functions called from AI send paths."""
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freq = detect_frequency_from_entry_point(caller="_send_anthropic_result", caller_class="AIClient")
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assert freq == "per_turn"
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def test_detect_frequency_cold() -> None:
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"""detect_frequency_from_entry_point returns 'cold' for functions called from cleanup."""
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freq = detect_frequency_from_entry_point(caller="cleanup", caller_class="AppController")
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assert freq == "cold"
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def test_detect_frequency_per_discussion() -> None:
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"""detect_frequency_from_entry_point returns 'per_discussion' for save/load functions."""
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freq = detect_frequency_from_entry_point(caller="save_project", caller_class="ProjectManager")
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assert freq == "per_discussion"
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def test_detect_frequency_unknown() -> None:
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"""detect_frequency_from_entry_point returns 'unknown' for unrecognized callers."""
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freq = detect_frequency_from_entry_point(caller="random_method", caller_class="X")
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assert freq == "unknown"
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def test_load_frequency_overrides_empty() -> None:
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"""load_frequency_overrides returns {} for a missing file."""
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result = load_frequency_overrides("/nonexistent/overrides.toml")
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assert result == {}
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def test_load_frequency_overrides_parses_toml() -> None:
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"""load_frequency_overrides parses [frequency.<function_fqname>] = '<freq>' lines."""
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with tempfile.TemporaryDirectory() as tmp:
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overrides_path = Path(tmp) / "overrides.toml"
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overrides_path.write_text('[frequency]\n"src.cleanup.do_nothing" = "cold"\n')
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result = load_frequency_overrides(str(overrides_path))
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assert result.get("src.cleanup.do_nothing") == "cold"
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def test_estimate_call_frequency_override_wins() -> None:
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"""estimate_call_frequency respects the override file's mapping."""
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f = FunctionRef(fqname="src.cleanup.do_nothing", file="src/cleanup.py", line=1, role="consumer")
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freq = estimate_call_frequency(
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f,
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callers=[],
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overrides={"src.cleanup.do_nothing": "cold"},
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)
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assert freq == "cold"
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def test_estimate_call_frequency_entry_point() -> None:
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"""estimate_call_frequency uses the entry-point detector when no override."""
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f = FunctionRef(fqname="src.x.y", file="src/x.py", line=1, role="consumer")
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freq = estimate_call_frequency(
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f,
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callers=[(FunctionRef(fqname="src.app.App.__init__", file="src/app.py", line=1, role="producer"), "App")],
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overrides={},
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)
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assert freq == "init"
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def test_estimate_call_frequency_unknown_no_callers() -> None:
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"""estimate_call_frequency returns 'unknown' for functions with no callers and no override."""
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f = FunctionRef(fqname="src.lonely.func", file="src/lonely.py", line=1, role="consumer")
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freq = estimate_call_frequency(f, callers=[], overrides={})
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assert freq == "unknown"
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def test_cost_constants() -> None:
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"""The 6 cost-model constants are defined per spec section 7.5."""
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assert MICROSECOND_BUDGET_PER_LLM_TURN == 50_000
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assert BRANCH_DISPATCH_OVERHEAD_US == 100
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assert ALLOCATION_OVERHEAD_US == 50
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assert DEAD_FIELD_COST_PER_FIELD_US == 10
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assert COMPONENTIZATION_INDIRECTION_US == 200
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assert UNIFICATION_INDIRECTION_US == 300
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def test_per_call_cost_us_no_frozen() -> None:
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"""per_call_cost_us = struct_field_count * 50 + max(fields_accessed_in_hot_path, 1) * 100 + 0 (not frozen)."""
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cost = per_call_cost_us(struct_field_count=10, hot_path_field_count=2, struct_frozen=False)
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assert cost == 10 * 50 + 2 * 100
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def test_per_call_cost_us_frozen() -> None:
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"""per_call_cost_us adds 20 for frozen dataclasses."""
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cost = per_call_cost_us(struct_field_count=10, hot_path_field_count=2, struct_frozen=True)
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assert cost == 10 * 50 + 2 * 100 + 20
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def test_per_call_cost_us_min_hot_path() -> None:
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"""per_call_cost_us uses max(hot_path_field_count, 1) to avoid zero branch overhead."""
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cost = per_call_cost_us(struct_field_count=10, hot_path_field_count=0, struct_frozen=False)
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assert cost == 10 * 50 + 1 * 100
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def test_frequency_multiplier_7_values() -> None:
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"""FREQUENCY_MULTIPLIER has 7 entries."""
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assert FREQUENCY_MULTIPLIER["hot"] == 60
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assert FREQUENCY_MULTIPLIER["per_turn"] == 1
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assert FREQUENCY_MULTIPLIER["per_request"] == 1
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assert FREQUENCY_MULTIPLIER["per_discussion"] == 1
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assert FREQUENCY_MULTIPLIER["cold"] == 0.01
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assert FREQUENCY_MULTIPLIER["init"] == 0.001
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assert FREQUENCY_MULTIPLIER["unknown"] == 0
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def test_current_total_us_per_turn() -> None:
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"""current_total_us = per_call_cost * frequency_multiplier for per_turn."""
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total = current_total_us(per_call_cost=500, frequency="per_turn")
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assert total == 500
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def test_current_total_us_hot() -> None:
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"""current_total_us = per_call_cost * 60 for hot."""
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total = current_total_us(per_call_cost=500, frequency="hot")
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assert total == 30_000
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def test_componentize_factor_field_by_field_large() -> None:
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"""componentize_factor=0.30 for field_by_field + struct_field_count > 10 + not frozen."""
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f = componentize_factor(access_pattern="field_by_field", struct_field_count=15, struct_frozen=False)
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assert f == 0.30
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def test_componentize_factor_hot_cold_split_small_hot() -> None:
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"""componentize_factor=0.40 for hot_cold_split + hot_field_count<=2 + struct_field_count>5."""
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f = componentize_factor(access_pattern="hot_cold_split", struct_field_count=8, struct_frozen=False, hot_field_count=2)
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assert f == 0.40
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def test_componentize_factor_whole_struct_negative() -> None:
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"""componentize_factor=-0.20 for whole_struct (splitting hurts)."""
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f = componentize_factor(access_pattern="whole_struct", struct_field_count=5, struct_frozen=False)
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assert f == -0.20
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def test_componentize_factor_mixed_zero() -> None:
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"""componentize_factor=0.0 for mixed (insufficient evidence)."""
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f = componentize_factor(access_pattern="mixed", struct_field_count=5, struct_frozen=False)
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assert f == 0.0
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def test_unify_factor_bulk_batched_small_frozen() -> None:
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"""unify_factor=0.25 for bulk_batched + struct_field_count <= 3 + frozen."""
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f = unify_factor(access_pattern="bulk_batched", struct_field_count=3, struct_frozen=True)
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assert f == 0.25
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def test_unify_factor_whole_struct_small_frozen() -> None:
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"""unify_factor=0.15 for whole_struct + struct_field_count <= 5 + frozen."""
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f = unify_factor(access_pattern="whole_struct", struct_field_count=5, struct_frozen=True)
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assert f == 0.15
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def test_unify_factor_field_by_field_negative() -> None:
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"""unify_factor=-0.30 for field_by_field (unification widens the data)."""
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f = unify_factor(access_pattern="field_by_field", struct_field_count=15, struct_frozen=True)
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assert f == -0.30
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def test_unify_factor_mixed_zero() -> None:
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"""unify_factor=0.0 for mixed (insufficient evidence)."""
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f = unify_factor(access_pattern="mixed", struct_field_count=5, struct_frozen=True)
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assert f == 0.0
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def test_recommended_direction_componentize_field_by_field() -> None:
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"""recommended_direction='componentize' for field_by_field + struct_field_count>10."""
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d = recommended_direction(access_pattern="field_by_field", struct_field_count=15, struct_frozen=False, frequency="per_turn", hot_field_count=0)
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assert d == "componentize"
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def test_recommended_direction_unify_bulk_batched() -> None:
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"""recommended_direction='unify' for bulk_batched + struct_field_count<=3."""
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d = recommended_direction(access_pattern="bulk_batched", struct_field_count=3, struct_frozen=True, frequency="per_turn", hot_field_count=0)
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assert d == "unify"
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def test_recommended_direction_insufficient_data_mixed() -> None:
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"""recommended_direction='insufficient_data' for mixed (needs runtime profiling)."""
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d = recommended_direction(access_pattern="mixed", struct_field_count=5, struct_frozen=True, frequency="per_turn", hot_field_count=0)
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assert d == "insufficient_data"
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def test_recommended_direction_hold_frozen_whole_struct() -> None:
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"""recommended_direction='hold' for frozen + whole_struct (ideal shape)."""
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d = recommended_direction(access_pattern="whole_struct", struct_field_count=5, struct_frozen=True, frequency="per_turn", hot_field_count=0)
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assert d == "hold"
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def test_generate_rationale_includes_pattern() -> None:
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"""generate_rationale includes the access pattern."""
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s = generate_rationale(
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aggregate="Metadata",
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access_pattern="field_by_field",
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frequency="per_turn",
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struct_field_count=15,
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struct_frozen=False,
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direction="componentize",
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)
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assert "field_by_field" in s
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assert "per_turn" in s
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assert "componentize" in s
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assert "Metadata" in s
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def test_compute_decomposition_cost_hold() -> None:
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"""compute_decomposition_cost returns 'hold' for the canonical frozen + whole_struct case."""
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cost = compute_decomposition_cost(
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aggregate="Metadata",
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access_pattern="whole_struct",
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struct_field_count=8,
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struct_frozen=True,
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frequency="per_turn",
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)
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assert cost.recommended_direction == "hold"
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assert cost.struct_field_count == 8
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assert cost.struct_frozen is True
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def test_compute_decomposition_cost_componentize() -> None:
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"""compute_decomposition_cost returns 'componentize' for field_by_field + large struct."""
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cost = compute_decomposition_cost(
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aggregate="BigStruct",
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access_pattern="field_by_field",
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struct_field_count=15,
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struct_frozen=False,
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frequency="per_turn",
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)
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assert cost.recommended_direction == "componentize"
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assert cost.componentize_savings > 0
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