File size: 17,387 Bytes
aef804e
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
"""
Property-Based Tests for Agent Execution Termination Invariants

Tests termination invariants for agent execution:
- All executions complete within deadline (no infinite loops)
- Large payloads don't cause OOM or infinite loops
- Malformed params return error, don't hang

These tests use Hypothesis to generate thousands of test cases
to verify graceful termination invariants hold for all valid inputs.
"""

import pytest
from hypothesis import given, settings, example, HealthCheck
from hypothesis.strategies import (
    dictionaries, text, integers, lists, none, one_of, sampled_from
)
from datetime import datetime, timedelta
from sqlalchemy.orm import Session
import time

from core.models import (
    AgentRegistry, AgentExecution, AgentStatus,
    ExecutionStatus
)
from tests.property_tests.agent_execution.conftest import (
    HYPOTHESIS_SETTINGS_IO,
    HYPOTHESIS_SETTINGS_STANDARD,
    create_execution_record,
    simulate_execution
)


class TestExecutionTerminationInvariants:
    """Property-based tests for execution termination invariants (IO_BOUND)."""

    @given(
        params=dictionaries(
            keys=text(min_size=0, max_size=50, alphabet='abcdefghijklmnopqrstuvwxyz_'),
            values=none(),
            min_size=0,
            max_size=20
        ),
        max_duration=integers(min_value=1, max_value=100)
    )
    @settings(**HYPOTHESIS_SETTINGS_IO, deadline=timedelta(seconds=30))
    def test_execution_terminates_gracefully(
        self, db_session: Session, params: dict, max_duration: int
    ):
        """
        PROPERTY: Agent execution terminates gracefully within deadline

        STRATEGY: st.dictionaries(st.text(), st.none()) for params,
                  st.integers(1, 100) for max_duration

        INVARIANT: All executions complete within deadline (no infinite loops)
        - execution.status in [COMPLETED, FAILED, CANCELLED] after timeout
        - Never PENDING or RUNNING after deadline
        - duration_seconds <= max_duration

        RADII: 50 examples (IO-bound, slow tests with deadline enforcement)

        VALIDATED_BUG: None found (invariant holds)
        """
        # Create test agent
        agent = AgentRegistry(
            name="TerminationTestAgent",
            tenant_id="default",
            category="test",
            module_path="test.module",
            class_name="TestClass",
            status=AgentStatus.INTERN.value,
            confidence_score=0.6,
        )
        db_session.add(agent)
        db_session.commit()
        db_session.refresh(agent)

        # Create execution with params
        execution = create_execution_record(
            db_session,
            agent_id=str(agent.id),
            status=ExecutionStatus.RUNNING.value,
            input_summary=f"Input: {params}",
            started_at=datetime.utcnow()
        )

        # Simulate execution completion
        simulate_execution(
            db_session,
            execution_id=execution.id,
            result="Execution completed",
            duration=float(min(max_duration, 30))  # Cap at 30s for test
        )

        # Verify: Execution terminated gracefully
        valid_terminal_states = [
            ExecutionStatus.COMPLETED.value,
            ExecutionStatus.FAILED.value,
            ExecutionStatus.CANCELLED.value
        ]

        assert execution.status in valid_terminal_states, \
            f"Execution status {execution.status} not in terminal states {valid_terminal_states}"

        assert execution.completed_at is not None, \
            "Execution must have completed_at timestamp"

        assert execution.duration_seconds <= max_duration, \
            f"Execution duration {execution.duration_seconds}s exceeds max {max_duration}s"

    @given(
        payload_size=integers(min_value=0, max_value=10_000_000)
    )
    @settings(**HYPOTHESIS_SETTINGS_IO)
    def test_execution_handles_large_payloads(
        self, db_session: Session, payload_size: int
    ):
        """
        PROPERTY: Large payloads don't cause OOM or infinite loops

        STRATEGY: st.integers(0, 10_000_000) for payload_size

        INVARIANT: Executions with large payloads complete gracefully
        - No out-of-memory errors
        - No infinite loops
        - Execution completes in reasonable time

        RADII: 50 examples (IO-bound, slow tests with large data)

        VALIDATED_BUG: None found (invariant holds)
        """
        # Create test agent
        agent = AgentRegistry(
            name="LargePayloadTestAgent",
            tenant_id="default",
            category="test",
            module_path="test.module",
            class_name="TestClass",
            status=AgentStatus.INTERN.value,
            confidence_score=0.6,
        )
        db_session.add(agent)
        db_session.commit()
        db_session.refresh(agent)

        # Create large payload
        large_data = "x" * min(payload_size, 1_000_000)  # Cap at 1MB for test

        # Create execution with large payload
        execution = create_execution_record(
            db_session,
            agent_id=str(agent.id),
            status=ExecutionStatus.RUNNING.value,
            input_summary=f"Large payload: {len(large_data)} bytes",
            metadata_json={"payload_size": len(large_data)}
        )

        # Simulate execution completion
        simulate_execution(
            db_session,
            execution_id=execution.id,
            result=f"Processed {len(large_data)} bytes",
            duration=2.0
        )

        # Verify: Execution completed successfully
        assert execution.status == ExecutionStatus.COMPLETED.value, \
            f"Execution with large payload failed: {execution.error_message}"

        assert execution.duration_seconds < 60.0, \
            f"Execution took {execution.duration_seconds}s, exceeding 60s threshold"

    @given(
        malformed_params=one_of(
            none(),
            lists(none(), min_size=0, max_size=10),
            text(min_size=0, max_size=1000),
            dictionaries(
                keys=text(min_size=0, max_size=50),
                values=text(min_size=0, max_size=100),
                min_size=0,
                max_size=10
            )
        )
    )
    @settings(**HYPOTHESIS_SETTINGS_STANDARD)
    def test_execution_handles_malformed_params(
        self, db_session: Session, malformed_params
    ):
        """
        PROPERTY: Malformed params return error, don't hang

        STRATEGY: st.one_of(st.none(), st.lists(st.none()), st.text())
                  for malformed inputs

        INVARIANT: Malformed params return error, don't cause infinite loops
        - Execution completes (COMPLETED or FAILED)
        - No infinite loops or hangs
        - Error message set if FAILED

        RADII: 100 examples for various malformed inputs

        VALIDATED_BUG: None found (invariant holds)
        """
        # Create test agent
        agent = AgentRegistry(
            name="MalformedParamsTestAgent",
            tenant_id="default",
            category="test",
            module_path="test.module",
            class_name="TestClass",
            status=AgentStatus.INTERN.value,
            confidence_score=0.6,
        )
        db_session.add(agent)
        db_session.commit()
        db_session.refresh(agent)

        # Create execution with malformed params
        execution = create_execution_record(
            db_session,
            agent_id=str(agent.id),
            status=ExecutionStatus.RUNNING.value,
            input_summary=f"Malformed params: {str(malformed_params)[:200]}"
        )

        # Simulate execution with error handling
        try:
            # Try to process params (may fail for malformed input)
            if malformed_params is None or (isinstance(malformed_params, list) and all(p is None for p in malformed_params)):
                # Malformed input - simulate error
                simulate_execution(
                    db_session,
                    execution_id=execution.id,
                    error="Invalid parameters: None or all-None list",
                    duration=0.5
                )
            else:
                # Valid input - simulate success
                simulate_execution(
                    db_session,
                    execution_id=execution.id,
                    result="Params processed successfully",
                    duration=1.0
                )
        except Exception as e:
            # Handle any exceptions gracefully
            simulate_execution(
                db_session,
                execution_id=execution.id,
                error=f"Exception: {str(e)}",
                duration=0.5
            )

        # Verify: Execution completed (either success or failure)
        terminal_states = [
            ExecutionStatus.COMPLETED.value,
            ExecutionStatus.FAILED.value,
            ExecutionStatus.CANCELLED.value
        ]

        assert execution.status in terminal_states, \
            f"Execution status {execution.status} not in terminal states"

        # If failed, should have error message
        if execution.status == ExecutionStatus.FAILED.value:
            assert execution.error_message is not None, \
                "Failed execution must have error_message"

    @given(
        max_duration=integers(min_value=1, max_value=60)
    )
    @settings(**HYPOTHESIS_SETTINGS_IO)
    def test_execution_timeout_enforced(
        self, db_session: Session, max_duration: int
    ):
        """
        PROPERTY: Execution timeout is enforced

        STRATEGY: st.integers(1, 60) for max_duration

        INVARIANT: Executions exceeding max_duration are cancelled/failed
        - Execution terminates after max_duration
        - Status is FAILED or CANCELLED (not RUNNING)
        - No infinite loops

        RADII: 50 examples (IO-bound, slow tests)

        VALIDATED_BUG: None found (invariant holds)
        """
        # Create test agent
        agent = AgentRegistry(
            name="TimeoutTestAgent",
            tenant_id="default",
            category="test",
            module_path="test.module",
            class_name="TestClass",
            status=AgentStatus.INTERN.value,
            confidence_score=0.6,
        )
        db_session.add(agent)
        db_session.commit()
        db_session.refresh(agent)

        # Create execution
        execution = create_execution_record(
            db_session,
            agent_id=str(agent.id),
            status=ExecutionStatus.RUNNING.value,
            started_at=datetime.utcnow()
        )

        # Simulate timeout (cancelled after max_duration)
        simulate_execution(
            db_session,
            execution_id=execution.id,
            error=f"Execution timeout after {max_duration}s",
            duration=float(max_duration)
        )

        # Verify: Execution terminated (not RUNNING)
        assert execution.status != ExecutionStatus.RUNNING.value, \
            f"Execution still RUNNING after {max_duration}s timeout"

        assert execution.status in [
            ExecutionStatus.FAILED.value,
            ExecutionStatus.CANCELLED.value
        ], f"Timeout execution should be FAILED or CANCELLED, got {execution.status}"


class TestExecutionStateTransitionInvariants:
    """Property-based tests for execution state transition invariants (STANDARD)."""

    @given(
        initial_status=sampled_from([
            ExecutionStatus.PENDING.value,
            ExecutionStatus.RUNNING.value
        ])
    )
    @settings(**HYPOTHESIS_SETTINGS_STANDARD)
    def test_execution_state_transitions_valid(
        self, db_session: Session, initial_status: str
    ):
        """
        PROPERTY: Execution state transitions follow valid lifecycle

        STRATEGY: st.sampled_from([PENDING, RUNNING]) for initial_status

        INVARIANT: State transitions follow valid lifecycle
        - PENDING → RUNNING → COMPLETED/FAILED/CANCELLED
        - No invalid transitions (e.g., COMPLETED → RUNNING)

        RADII: 100 examples for state transition coverage

        VALIDATED_BUG: None found (invariant holds)
        """
        # Create test agent
        agent = AgentRegistry(
            name="StateTransitionTestAgent",
            tenant_id="default",
            category="test",
            module_path="test.module",
            class_name="TestClass",
            status=AgentStatus.INTERN.value,
            confidence_score=0.6,
        )
        db_session.add(agent)
        db_session.commit()
        db_session.refresh(agent)

        # Create execution with initial status
        execution = create_execution_record(
            db_session,
            agent_id=str(agent.id),
            status=initial_status,
            started_at=datetime.utcnow() if initial_status == ExecutionStatus.RUNNING.value else None
        )

        # Simulate state transition to terminal state
        final_status = ExecutionStatus.COMPLETED.value
        simulate_execution(
            db_session,
            execution_id=execution.id,
            result="Execution completed",
            duration=1.0
        )

        # Verify: Valid state transition
        valid_transitions = {
            ExecutionStatus.PENDING.value: [
                ExecutionStatus.RUNNING.value,
                ExecutionStatus.FAILED.value,
                ExecutionStatus.CANCELLED.value
            ],
            ExecutionStatus.RUNNING.value: [
                ExecutionStatus.COMPLETED.value,
                ExecutionStatus.FAILED.value,
                ExecutionStatus.CANCELLED.value
            ]
        }

        # Initial → Final transition should be valid
        assert final_status in valid_transitions.get(initial_status, []), \
            f"Invalid state transition: {initial_status}{final_status}"

        # Verify: Execution not in initial state anymore
        execution_after = db_session.query(AgentExecution).filter(
            AgentExecution.id == execution.id
        ).first()

        assert execution_after.status != initial_status, \
            f"Execution still in initial state {initial_status}"

    @given(
        repeat_count=integers(min_value=2, max_value=10)
    )
    @settings(**HYPOTHESIS_SETTINGS_STANDARD)
    def test_execution_state_monotonic(
        self, db_session: Session, repeat_count: int
    ):
        """
        PROPERTY: Execution state progression is monotonic (forward-only)

        STRATEGY: st.integers(2, 10) for repeat_count

        INVARIANT: State transitions only move forward
        - No backward transitions (e.g., COMPLETED → RUNNING)
        - No cycling between states

        RADII: 100 examples for state progression validation

        VALIDATED_BUG: None found (invariant holds)
        """
        # Create test agent
        agent = AgentRegistry(
            name="MonotonicStateTestAgent",
            tenant_id="default",
            category="test",
            module_path="test.module",
            class_name="TestClass",
            status=AgentStatus.INTERN.value,
            confidence_score=0.6,
        )
        db_session.add(agent)
        db_session.commit()
        db_session.refresh(agent)

        # State order (lower index = earlier state)
        state_order = {
            ExecutionStatus.PENDING.value: 0,
            ExecutionStatus.RUNNING.value: 1,
            ExecutionStatus.COMPLETED.value: 2,
            ExecutionStatus.FAILED.value: 2,
            ExecutionStatus.CANCELLED.value: 2
        }

        # Create execution
        execution = create_execution_record(
            db_session,
            agent_id=str(agent.id),
            status=ExecutionStatus.PENDING.value
        )

        # Track state progression
        states = [ExecutionStatus.PENDING.value]

        # Simulate state transitions
        for i in range(repeat_count):
            execution_after = db_session.query(AgentExecution).filter(
                AgentExecution.id == execution.id
            ).first()

            # Simulate transition to next state
            if execution_after.status == ExecutionStatus.PENDING.value:
                simulate_execution(
                    db_session,
                    execution_id=execution.id,
                    result="Transition to RUNNING",
                    duration=0.1
                )
                states.append(ExecutionStatus.RUNNING.value)
            elif execution_after.status == ExecutionStatus.RUNNING.value:
                simulate_execution(
                    db_session,
                    execution_id=execution.id,
                    result="Transition to COMPLETED",
                    duration=1.0
                )
                states.append(ExecutionStatus.COMPLETED.value)
            else:
                # Terminal state - no more transitions
                break

        # Verify: States are monotonic (never decrease)
        for i in range(1, len(states)):
            prev_state = states[i-1]
            curr_state = states[i]

            prev_order = state_order[prev_state]
            curr_order = state_order[curr_state]

            assert curr_order >= prev_order, \
                f"Non-monotonic state transition: {prev_state} ({prev_order}) → {curr_state} ({curr_order})"