File size: 16,531 Bytes
0b0338d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
# server/counterfactual_engine.py
"""
Counterfactual Robustness Engine β€” v4.0

The key scientific question: Is the agent's strategy robust, or is it brittle?

We test this by:
1. Running an episode β†’ recording strategy
2. Applying small, semantically-neutral mutations to the repo
   (rename variable, change a constant, add a dummy function)
3. Measuring whether the agent's recorded strategy would fail on the mutated repo

IMPORTANT: This does NOT re-run the agent. It analyzes whether the
already-recorded navigation pattern was based on deep structure (robust)
or surface signals like filenames/constants (brittle).

This is completely novel β€” no benchmark or tool does this.
"""
from __future__ import annotations
import random
import hashlib
from typing import List, Dict, Any, Tuple
from dataclasses import dataclass, field
from enum import Enum


class BrittlenessLevel(str, Enum):
    ROBUST = "ROBUST"           # Strategy survives all mutations
    MILDLY_BRITTLE = "MILDLY_BRITTLE"  # Survives 60-80% of mutations
    BRITTLE = "BRITTLE"         # Survives < 60%
    FRAGILE = "FRAGILE"         # Survives < 30%


@dataclass
class Mutation:
    """A single counterfactual mutation applied to the repo."""
    mutation_type: str
    target_file: str
    description: str
    would_break_agent: bool  # Would this mutation cause agent's strategy to fail?
    why: str                 # Explanation


@dataclass
class CounterfactualReport:
    """Results of counterfactual robustness testing."""
    episode_id: str
    task: str
    brittleness_level: BrittlenessLevel
    robustness_score: float      # 0.0 – 1.0

    mutations_tested: List[Mutation]
    mutations_survived: int
    mutations_failed: int

    surface_dependencies: List[str]  # What surface signals the agent relied on
    deep_dependencies: List[str]     # What structural signals it used correctly

    explanation: str
    recommendations: List[str]

    def to_dict(self) -> dict:
        return {
            "episode_id": self.episode_id,
            "task": self.task,
            "brittleness_level": self.brittleness_level.value,
            "robustness_score": round(self.robustness_score, 3),
            "mutations_tested": len(self.mutations_tested),
            "mutations_survived": self.mutations_survived,
            "mutations_failed": self.mutations_failed,
            "mutations": [
                {
                    "type": m.mutation_type,
                    "file": m.target_file,
                    "description": m.description,
                    "would_break_agent": m.would_break_agent,
                    "why": m.why,
                }
                for m in self.mutations_tested
            ],
            "surface_dependencies": self.surface_dependencies,
            "deep_dependencies": self.deep_dependencies,
            "explanation": self.explanation,
            "recommendations": self.recommendations,
        }


class CounterfactualEngine:
    """
    Analyzes brittleness by reasoning about what mutations would break the agent.

    We don't need to actually re-run the agent β€” we analyze the recorded
    trajectory and ask: "If file X was named differently / had a different
    constant, would this agent's navigation pattern still work?"

    Brittle signals:
    - Agent found bug file by pattern-matching on filename (not content search)
    - Agent submitted after reading the same file every run
    - Agent ignored test content and relied on positional heuristics

    Robust signals:
    - Agent used search_code to find function by name
    - Agent read test β†’ traced import β†’ found source
    - Agent ran tests and verified result before submitting
    """

    MUTATION_TEMPLATES = [
        {
            "type": "FILENAME_RENAME",
            "description": "Rename src/X.py to src/X_v2.py (same content)",
            "breaks_if": "agent found file by name pattern, not by search or import tracing",
            "surface_signal": "filename",
            "robust_signal": "import tracing or search_code",
        },
        {
            "type": "CONSTANT_CHANGE",
            "description": "Change a numeric constant by Β±1 (semantically neutral for navigation)",
            "breaks_if": "agent hardcoded expected value rather than reading actual code",
            "surface_signal": "constant value pattern matching",
            "robust_signal": "dynamic code reading",
        },
        {
            "type": "DUMMY_FUNCTION",
            "description": "Add a dummy function with a similar name near the bug",
            "breaks_if": "agent used first-match navigation without reading full context",
            "surface_signal": "first result of search or first match in file",
            "robust_signal": "reading complete function signatures before deciding",
        },
        {
            "type": "DIRECTORY_SHUFFLE",
            "description": "Move test file from tests/ to test/ (same content)",
            "breaks_if": "agent hardcoded path prefix tests/ instead of searching",
            "surface_signal": "hardcoded directory prefix",
            "robust_signal": "search or dynamic discovery",
        },
        {
            "type": "DOCSTRING_NOISE",
            "description": "Add misleading docstring claiming a different function causes the bug",
            "breaks_if": "agent read docs instead of tests to understand expected behavior",
            "surface_signal": "docstring content",
            "robust_signal": "test assertions as ground truth",
        },
        {
            "type": "IMPORT_REORDER",
            "description": "Reorder imports in the source file",
            "breaks_if": "agent relied on line numbers instead of function names",
            "surface_signal": "absolute line numbers",
            "robust_signal": "function name search",
        },
    ]

    def analyze(
        self,
        episode_id: str,
        task: str,
        trajectory_steps: List[dict],
        variant_meta: dict,
        files_read: List[str],
        files_written: List[str],
        final_score: float,
    ) -> CounterfactualReport:
        """
        Analyze robustness by simulating mutations and reasoning about
        whether the agent's recorded pattern would survive them.
        """
        action_types = [s.get("action_type", "") for s in trajectory_steps]
        action_paths = [s.get("action_path") for s in trajectory_steps]

        bug_files = set(variant_meta.get("bug_files", []) or
                        variant_meta.get("files_to_implement", []) or [])
        test_files_meta = set(variant_meta.get("test_files", []) or [])

        # Infer what signals agent used
        used_search = "search_code" in action_types
        used_tests_first = self._tests_read_before_src(trajectory_steps, test_files_meta, bug_files)
        used_run_tests = "run_tests" in action_types
        blind_navigation = not used_search and not used_tests_first
        read_count = action_types.count("read_file")
        write_count = action_types.count("write_file")
        immediate_write = write_count > 0 and action_types.index("write_file") <= 2
        verified_before_submit = self._verified_before_submit(trajectory_steps)

        # ── Evaluate each mutation ────────────────────────────────────────────
        mutations: List[Mutation] = []

        for tmpl in self.MUTATION_TEMPLATES:
            target_file = self._pick_target_file(tmpl["type"], files_read, bug_files)
            would_break, why = self._would_break_agent(
                mutation_type=tmpl["type"],
                used_search=used_search,
                used_tests_first=used_tests_first,
                verified_before_submit=verified_before_submit,
                blind_navigation=blind_navigation,
                immediate_write=immediate_write,
                read_count=read_count,
                tmpl=tmpl,
            )
            mutations.append(Mutation(
                mutation_type=tmpl["type"],
                target_file=target_file or "unknown",
                description=tmpl["description"],
                would_break_agent=would_break,
                why=why,
            ))

        survived = sum(1 for m in mutations if not m.would_break_agent)
        failed = len(mutations) - survived

        robustness_score = survived / len(mutations) if mutations else 0.0

        # ── Surface vs deep dependency analysis ──────────────────────────────
        surface_deps = []
        deep_deps = []

        if not used_search:
            surface_deps.append("Filename-based navigation (no search_code used)")
        if not used_tests_first:
            surface_deps.append("Skipped test-informed navigation")
        if immediate_write:
            surface_deps.append("Immediate write after minimal reading (blind fix)")
        if not verified_before_submit:
            surface_deps.append("Submitted without running tests (no verification)")

        if used_search:
            deep_deps.append("Used search_code to find functions by name (content-based)")
        if used_tests_first:
            deep_deps.append("Read tests first β€” used expected behavior as compass")
        if read_count >= 3:
            deep_deps.append(f"Read {read_count} files β€” explored structure before committing")
        if verified_before_submit:
            deep_deps.append("Verified fix with run_tests before submitting")

        # ── Brittleness classification ────────────────────────────────────────
        if robustness_score >= 0.80:
            level = BrittlenessLevel.ROBUST
        elif robustness_score >= 0.60:
            level = BrittlenessLevel.MILDLY_BRITTLE
        elif robustness_score >= 0.30:
            level = BrittlenessLevel.BRITTLE
        else:
            level = BrittlenessLevel.FRAGILE

        explanations = {
            BrittlenessLevel.ROBUST: (
                "Agent strategy is robust. It relies on deep structural signals (function names, "
                "test assertions, causal chain traversal) rather than surface patterns. "
                "Minor repo mutations would not break its navigation."
            ),
            BrittlenessLevel.MILDLY_BRITTLE: (
                "Agent strategy is mildly brittle. Some mutations would break its navigation, "
                "particularly those that change surface signals it relied on. "
                "Using search_code and test-first navigation consistently would improve robustness."
            ),
            BrittlenessLevel.BRITTLE: (
                "Agent strategy is brittle. Most mutations would break its navigation. "
                "The agent appears to rely on stable surface patterns (filenames, positions) "
                "rather than understanding the semantic structure of the codebase."
            ),
            BrittlenessLevel.FRAGILE: (
                "Agent strategy is fragile. Almost any perturbation to the repo structure "
                "would cause this agent to fail. This indicates pure pattern-matching on "
                "the specific repo layout rather than generalizable code understanding."
            ),
        }

        recs = []
        if not used_search:
            recs.append("Use search_code to find functions by name β€” survives filename renames.")
        if not used_tests_first:
            recs.append("Read tests first to anchor your navigation in expected behavior, not filenames.")
        if immediate_write:
            recs.append("Read source files before writing to them β€” avoid blind writes.")
        if not verified_before_submit:
            recs.append("Run tests after writing β€” verify your fix holds on the actual behavior.")

        return CounterfactualReport(
            episode_id=episode_id,
            task=task,
            brittleness_level=level,
            robustness_score=robustness_score,
            mutations_tested=mutations,
            mutations_survived=survived,
            mutations_failed=failed,
            surface_dependencies=surface_deps,
            deep_dependencies=deep_deps,
            explanation=explanations[level],
            recommendations=recs,
        )

    # ── Helpers ───────────────────────────────────────────────────────────────

    def _tests_read_before_src(
        self, steps: List[dict], test_files: set, bug_files: set
    ) -> bool:
        test_steps = [
            s.get("step_number", 99) for s in steps
            if s.get("action_type") == "read_file"
            and any(tf in (s.get("action_path") or "") for tf in test_files)
        ]
        src_steps = [
            s.get("step_number", 99) for s in steps
            if s.get("action_type") == "read_file"
            and any(bf in (s.get("action_path") or "") for bf in bug_files)
        ]
        if test_steps and src_steps:
            return min(test_steps) < min(src_steps)
        return False

    def _verified_before_submit(self, steps: List[dict]) -> bool:
        submit_step = next(
            (s.get("step_number", 9999) for s in steps if s.get("action_type") == "submit"),
            None,
        )
        if submit_step is None:
            return False
        return any(
            s.get("action_type") == "run_tests"
            and s.get("step_number", 0) < submit_step
            for s in steps
        )

    def _pick_target_file(
        self, mutation_type: str, files_read: List[str], bug_files: set
    ) -> str:
        if mutation_type in ("FILENAME_RENAME", "DUMMY_FUNCTION", "IMPORT_REORDER"):
            for f in bug_files:
                return f
            return files_read[0] if files_read else "src/main.py"
        if mutation_type == "DIRECTORY_SHUFFLE":
            for f in files_read:
                if "test" in f.lower():
                    return f
        return files_read[0] if files_read else "unknown"

    def _would_break_agent(
        self,
        mutation_type: str,
        used_search: bool,
        used_tests_first: bool,
        verified_before_submit: bool,
        blind_navigation: bool,
        immediate_write: bool,
        read_count: int,
        tmpl: dict,
    ) -> Tuple[bool, str]:
        """
        Return (would_break, explanation) by reasoning about the agent's signals.
        """
        if mutation_type == "FILENAME_RENAME":
            if used_search:
                return False, "Agent used search_code β€” finds function by name, not filename"
            if blind_navigation:
                return True, "Agent navigated by filename without search β€” rename breaks it"
            return True, "Agent likely relied on filename pattern without search fallback"

        if mutation_type == "CONSTANT_CHANGE":
            # Almost never breaks well-behaved agents
            if read_count >= 2:
                return False, "Agent read files dynamically β€” adapts to any constant value"
            return True, "Agent may have hardcoded expected value in navigation heuristic"

        if mutation_type == "DUMMY_FUNCTION":
            if used_search and read_count >= 3:
                return False, "Agent searched and read thoroughly β€” would disambiguate"
            return True, "Agent took first match without thorough reading"

        if mutation_type == "DIRECTORY_SHUFFLE":
            if used_search:
                return False, "search_code finds tests regardless of directory"
            return True, "Agent used hardcoded path prefix β€” directory change breaks it"

        if mutation_type == "DOCSTRING_NOISE":
            if used_tests_first:
                return False, "Agent used test assertions as ground truth, not docstrings"
            return True, "Agent may have read misleading docstring instead of test"

        if mutation_type == "IMPORT_REORDER":
            # Only brittle if agent relied on line numbers
            if read_count <= 1:
                return True, "Agent skimmed β€” likely used line numbers for navigation"
            return False, "Agent read full files β€” import reorder doesn't change function content"

        return False, "Neutral mutation"