do-memory-core 0.1.30

Core episodic learning system for AI agents with pattern extraction, reward scoring, and dual storage backend
Documentation
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
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
//! Property-based tests for memory-core types
//!
//! These tests use proptest to verify serialization roundtrips and state invariants
//! across a wide range of generated inputs.

use do_memory_core::*;
use proptest::prelude::*;

// Re-export for use in tests
use std::result::Result as StdResult;

// Import chrono for timestamp handling
use chrono::Utc;

// ============================================================================
// Serialization Roundtrip Tests
// ============================================================================

proptest! {
    /// Test that TaskContext serializes and deserializes correctly
    #[test]
    fn task_context_json_roundtrip(
        language in proptest::option::of("[a-z]{2,10}"),
        framework in proptest::option::of("[a-z]{2,15}"),
        domain in "[a-z]{3,20}",
        tags in proptest::collection::vec("[a-z]{2,15}", 0..10)
    ) {
        let context = TaskContext {
            language,
            framework,
            complexity: ComplexityLevel::Moderate,
            domain,
            tags,
        };

        // JSON roundtrip
        let json = serde_json::to_string(&context).expect("serialize to JSON");
        let deserialized: TaskContext = serde_json::from_str(&json).expect("deserialize from JSON");
        assert_eq!(context, deserialized);
    }

    /// Test that RewardScore serializes and deserializes correctly
    #[test]
    fn reward_score_json_roundtrip(
        total in 0.0f32..2.0f32,
        base in 0.0f32..1.0f32,
        efficiency in 0.5f32..1.5f32,
        complexity_bonus in 1.0f32..1.3f32,
        quality_multiplier in 0.8f32..1.2f32,
        learning_bonus in 0.0f32..0.5f32
    ) {
        let score = RewardScore {
            total,
            base,
            efficiency,
            complexity_bonus,
            quality_multiplier,
            learning_bonus,
        };

        let json = serde_json::to_string(&score).expect("serialize to JSON");
        let deserialized: RewardScore = serde_json::from_str(&json).expect("deserialize from JSON");

        // Use approximate equality for floats
        assert!((score.total - deserialized.total).abs() < 0.001);
        assert!((score.base - deserialized.base).abs() < 0.001);
        assert!((score.efficiency - deserialized.efficiency).abs() < 0.001);
    }

    /// Test that OutcomeStats maintains success rate invariants
    #[test]
    fn outcome_stats_success_rate_invariant(
        success_count in 0usize..1000usize,
        failure_count in 0usize..1000usize,
        avg_duration_secs in 0.0f32..3600.0f32
    ) {
        let stats = OutcomeStats {
            success_count,
            failure_count,
            total_count: success_count + failure_count,
            avg_duration_secs,
        };

        let success_rate = stats.success_rate();

        // Invariant: success rate should be between 0.0 and 1.0
        prop_assert!((0.0..=1.0).contains(&success_rate));

        // Invariant: success rate should equal success_count / total_count
        if stats.total_count > 0 {
            #[allow(clippy::cast_precision_loss)]
            let expected_rate = success_count as f32 / stats.total_count as f32;
            prop_assert!((success_rate - expected_rate).abs() < 0.0001);
        } else {
            prop_assert!((success_rate - 0.0_f32).abs() < f32::EPSILON);
        }
    }

    /// Test Episode tag validation invariants
    #[test]
    fn episode_tag_validation_invariants(
        tag in "[a-zA-Z0-9_-]{1,100}"
    ) {
        let mut episode = Episode::new(
            "Test task".to_string(),
            TaskContext::default(),
            TaskType::CodeGeneration
        );

        // Valid tags should be added successfully
        if tag.len() >= 2 && tag.len() <= 100 {
            let result = episode.add_tag(tag.clone());
            prop_assert!(result.is_ok());

            // Tag should be normalized (lowercase)
            let normalized_tag = tag.trim().to_lowercase();
            prop_assert!(episode.has_tag(&normalized_tag));
        }
    }

    /// Test tag normalization consistency
    #[test]
    fn tag_normalization_consistency(
        tag in "[a-zA-Z0-9_-]{2,50}"
    ) {
        let mut episode = Episode::new(
            "Test task".to_string(),
            TaskContext::default(),
            TaskType::CodeGeneration
        );

        // Add tag
        episode.add_tag(tag.clone()).unwrap();

        // Should be found with different case variations
        let upper = tag.to_uppercase();
        let mixed: String = tag.chars()
            .enumerate()
            .map(|(i, c)| if i % 2 == 0 { c.to_ascii_uppercase() } else { c })
            .collect();

        prop_assert!(episode.has_tag(&upper));
        prop_assert!(episode.has_tag(&mixed));
        prop_assert!(episode.has_tag(&tag.to_lowercase()));
    }

    /// Test Episode serialization roundtrip with various states
    #[test]
    fn episode_json_roundtrip(
        task_description in "[a-zA-Z0-9 ]{1,100}",
        domain in "[a-z]{3,15}",
        has_outcome in proptest::bool::ANY
    ) {
        let mut episode = Episode::new(
            task_description.clone(),
            TaskContext {
                language: Some("rust".to_string()),
                framework: None,
                complexity: ComplexityLevel::Moderate,
                domain: domain.clone(),
                tags: vec!["test".to_string()],
            },
            TaskType::CodeGeneration,
        );

        // Add some steps
        let step = ExecutionStep::new(
            1,
            "test_tool".to_string(),
            "Test action".to_string()
        );
        episode.add_step(step);

        // Optionally complete the episode
        if has_outcome {
            episode.complete(TaskOutcome::Success {
                verdict: "Test completed".to_string(),
                artifacts: vec!["file.rs".to_string()],
            });
        }

        // Store values before serialization to avoid borrow issues
        let episode_id = episode.episode_id;
        let steps_len = episode.steps.len();
        let is_complete = episode.is_complete();

        // Serialize and deserialize
        let json = serde_json::to_string(&episode).expect("serialize episode");
        let deserialized: Episode = serde_json::from_str(&json).expect("deserialize episode");

        // Store deserialized values
        let deserialized_id = deserialized.episode_id;
        let deserialized_steps_len = deserialized.steps.len();
        let deserialized_is_complete = deserialized.is_complete();
        let deserialized_task_desc = deserialized.task_description.clone();
        let deserialized_domain = deserialized.context.domain.clone();

        // Verify key fields match
        prop_assert_eq!(episode_id, deserialized_id);
        prop_assert_eq!(task_description, deserialized_task_desc);
        prop_assert_eq!(domain, deserialized_domain);
        prop_assert_eq!(steps_len, deserialized_steps_len);
        prop_assert_eq!(is_complete, deserialized_is_complete);
    }
}

// ============================================================================
// State Machine Invariant Tests
// ============================================================================

proptest! {
    /// Test episode state transitions
    #[test]
    fn episode_state_transition_invariants(
        num_steps in 0usize..50usize
    ) {
        let mut episode = Episode::new(
            "Test task".to_string(),
            TaskContext::default(),
            TaskType::CodeGeneration,
        );

        // Initial state: not complete, no steps
        prop_assert!(!episode.is_complete());
        prop_assert_eq!(episode.steps.len(), 0);
        prop_assert!(episode.outcome.is_none());
        prop_assert!(episode.end_time.is_none());

        // Add steps
        for i in 0..num_steps {
            let step = ExecutionStep::new(
                i + 1,
                format!("tool_{i}"),
                format!("Action {i}")
            );
            episode.add_step(step);
        }

        // After adding steps: not complete
        prop_assert!(!episode.is_complete());
        prop_assert_eq!(episode.steps.len(), num_steps);

        // Complete the episode
        episode.complete(TaskOutcome::Success {
            verdict: "Done".to_string(),
            artifacts: vec![],
        });

        // After completion: is_complete should be true
        prop_assert!(episode.is_complete());
        prop_assert!(episode.outcome.is_some());
        prop_assert!(episode.end_time.is_some());

        // Duration should be available
        prop_assert!(episode.duration().is_some());
    }

    /// Test successful vs failed step counting
    #[test]
    fn step_success_counting_invariants(
        results in proptest::collection::vec(
            proptest::bool::ANY,
            1..100usize
        )
    ) {
        let mut episode = Episode::new(
            "Test task".to_string(),
            TaskContext::default(),
            TaskType::Testing,
        );

        let expected_successes = results.iter().filter(|&&r| r).count();
        let expected_failures = results.iter().filter(|&&r| !r).count();

        for (i, is_success) in results.iter().enumerate() {
            let mut step = ExecutionStep::new(
                i + 1,
                "test_tool".to_string(),
                "Test".to_string()
            );

            step.result = if *is_success {
                Some(ExecutionResult::Success {
                    output: "OK".to_string()
                })
            } else {
                Some(ExecutionResult::Error {
                    message: "Failed".to_string()
                })
            };

            episode.add_step(step);
        }

        // Verify counting invariants
        prop_assert_eq!(episode.successful_steps_count(), expected_successes);
        prop_assert_eq!(episode.failed_steps_count(), expected_failures);
        prop_assert_eq!(
            episode.successful_steps_count() + episode.failed_steps_count(),
            results.len()
        );
    }

    /// Test ExecutionResult success/failure invariants
    #[test]
    fn execution_result_invariants(
        output in "[a-zA-Z0-9 ]{0,100}",
        error_msg in "[a-zA-Z0-9 ]{0,100}"
    ) {
        let success = ExecutionResult::Success {
            output: output.clone()
        };
        let error = ExecutionResult::Error {
            message: error_msg.clone()
        };
        let timeout = ExecutionResult::Timeout;

        prop_assert!(success.is_success());
        prop_assert!(!error.is_success());
        prop_assert!(!timeout.is_success());
    }

    /// Test PatternEffectiveness calculation invariants
    #[test]
    fn pattern_effectiveness_invariants(
        retrieved in 0usize..100usize,
        _applied in 0usize..100usize,
        successes in 0usize..100usize,
        failures in 0usize..100usize
    ) {
        let mut effectiveness = PatternEffectiveness::default();

        // Simulate retrievals
        for _ in 0..retrieved {
            effectiveness.record_retrieval();
        }

        // Simulate applications with outcomes
        for _ in 0..successes {
            effectiveness.record_application(true, 0.1);
        }

        for _ in 0..failures {
            effectiveness.record_application(false, -0.1);
        }

        // Invariant: times_applied should equal successes + failures
        prop_assert_eq!(
            effectiveness.times_applied,
            successes + failures
        );

        // Invariant: usage rate should be applied / retrieved (or 0 if none)
        let expected_usage_rate = if retrieved == 0 {
            0.0
        } else {
            #[allow(clippy::cast_precision_loss)]
            { (successes + failures) as f32 / retrieved as f32 }
        };
        prop_assert!(
            (effectiveness.usage_rate() - expected_usage_rate).abs() < 0.0001
        );

        // Invariant: application success rate should be successes / applied (or 0.5 if none)
        if effectiveness.times_applied > 0 {
            #[allow(clippy::cast_precision_loss)]
            let expected_success_rate = successes as f32 / effectiveness.times_applied as f32;
            prop_assert!(
                (effectiveness.application_success_rate() - expected_success_rate).abs() < 0.0001
            );
        } else {
            prop_assert!((effectiveness.application_success_rate() - 0.5_f32).abs() < f32::EPSILON);
        }
    }
}

// ============================================================================
// TaskOutcome and Type Tests
// ============================================================================

proptest! {
    /// Test TaskOutcome serialization roundtrip
    #[test]
    fn task_outcome_json_roundtrip(
        verdict in "[a-zA-Z0-9 ]{1,100}",
        reason in "[a-zA-Z0-9 ]{1,100}"
    ) {
        let outcomes = vec![
            TaskOutcome::Success {
                verdict: verdict.clone(),
                artifacts: vec!["file1.rs".to_string()],
            },
            TaskOutcome::PartialSuccess {
                verdict: verdict.clone(),
                completed: vec!["item1".to_string()],
                failed: vec!["item2".to_string()],
            },
            TaskOutcome::Failure {
                reason: reason.clone(),
                error_details: Some("Detailed error".to_string()),
            },
        ];

        for outcome in outcomes {
            let json = serde_json::to_string(&outcome).expect("serialize outcome");
            let deserialized: TaskOutcome = serde_json::from_str(&json).expect("deserialize outcome");

            // Check variant matches
            prop_assert_eq!(
                std::mem::discriminant(&outcome),
                std::mem::discriminant(&deserialized)
            );
        }
    }

    /// Test TaskType roundtrip through string conversion
    #[test]
    fn task_type_string_roundtrip(
        task_type in prop::sample::select(vec![
            TaskType::CodeGeneration,
            TaskType::Debugging,
            TaskType::Refactoring,
            TaskType::Testing,
            TaskType::Analysis,
            TaskType::Documentation,
            TaskType::Other,
        ])
    ) {
        let string_repr = task_type.to_string();
        let parsed: TaskType = string_repr.parse().expect("parse task type");
        prop_assert_eq!(task_type, parsed);
    }

    /// Test ComplexityLevel serialization
    #[test]
    fn complexity_level_roundtrip(
        level in prop::sample::select(vec![
            ComplexityLevel::Simple,
            ComplexityLevel::Moderate,
            ComplexityLevel::Complex,
        ])
    ) {
        let json = serde_json::to_string(&level).expect("serialize complexity");
        let deserialized: ComplexityLevel = serde_json::from_str(&json).expect("deserialize complexity");
        prop_assert_eq!(level, deserialized);
    }
}

// ============================================================================
// Edge Case Tests
// ============================================================================

proptest! {
    /// Test episode with empty/edge case values
    #[test]
    fn episode_edge_cases(
        empty_desc in "",
        long_desc in "[a-z]{200,300}"
    ) {
        // Empty description should still work
        let episode1 = Episode::new(
            empty_desc.clone(),
            TaskContext::default(),
            TaskType::Other,
        );

        // Long description should work
        let _episode2 = Episode::new(
            long_desc.clone(),
            TaskContext::default(),
            TaskType::CodeGeneration,
        );
        prop_assert!(!episode1.is_complete());

        // Long description should work
        let episode2 = Episode::new(
            long_desc.clone(),
            TaskContext::default(),
            TaskType::CodeGeneration,
        );
        prop_assert_eq!(episode2.task_description.len(), long_desc.len());
    }

    /// Test Reflection serialization with various content sizes
    #[test]
    fn reflection_serialization_roundtrip(
        successes in proptest::collection::vec("[a-zA-Z0-9 ]{1,50}", 0..20),
        improvements in proptest::collection::vec("[a-zA-Z0-9 ]{1,50}", 0..20),
        insights in proptest::collection::vec("[a-zA-Z0-9 ]{1,50}", 0..20)
    ) {
        let reflection = Reflection {
            successes,
            improvements,
            insights,
            generated_at: Utc::now(),
        };

        let json = serde_json::to_string(&reflection).expect("serialize reflection");
        let deserialized: Reflection = serde_json::from_str(&json).expect("deserialize reflection");

        prop_assert_eq!(reflection.successes.len(), deserialized.successes.len());
        prop_assert_eq!(reflection.improvements.len(), deserialized.improvements.len());
        prop_assert_eq!(reflection.insights.len(), deserialized.insights.len());
    }

    /// Test Evidence serialization
    #[test]
    fn evidence_serialization_roundtrip(
        sample_size in 1usize..100usize,
        success_rate in 0.0f32..1.0f32
    ) {
        use uuid::Uuid;

        let evidence = Evidence {
            episode_ids: (0..sample_size).map(|_| Uuid::new_v4()).collect(),
            success_rate,
            sample_size,
        };

        let json = serde_json::to_string(&evidence).expect("serialize evidence");
        let deserialized: Evidence = serde_json::from_str(&json).expect("deserialize evidence");

        prop_assert_eq!(evidence.episode_ids.len(), deserialized.episode_ids.len());
        prop_assert!((evidence.success_rate - deserialized.success_rate).abs() < 0.0001);
    }
}

// ============================================================================
// Determinism Tests
// ============================================================================

proptest! {
    /// Test that serialization is deterministic
    #[test]
    fn serialization_determinism(
        task_description in "[a-zA-Z0-9 ]{1,50}",
        domain in "[a-z]{3,15}"
    ) {
        let episode = Episode::new(
            task_description.clone(),
            TaskContext {
                language: Some("rust".to_string()),
                framework: None,
                complexity: ComplexityLevel::Moderate,
                domain: domain.clone(),
                tags: vec!["test".to_string()],
            },
            TaskType::CodeGeneration,
        );

        // Serialize twice
        let json1 = serde_json::to_string(&episode).expect("serialize 1");
        let json2 = serde_json::to_string(&episode).expect("serialize 2");

        // Should be identical
        prop_assert_eq!(json1.clone(), json2.clone());

        // Deserializing both should give the same result
        let de1: Episode = serde_json::from_str(&json1).expect("deserialize 1");
        let de2: Episode = serde_json::from_str(&json2).expect("deserialize 2");
        prop_assert_eq!(de1, de2);
    }

    /// Test tag operations are deterministic
    #[test]
    fn tag_operations_deterministic(
        tags in proptest::collection::hash_set("[a-z]{2,20}", 1..50)
    ) {
        let mut episode1 = Episode::new(
            "Test".to_string(),
            TaskContext::default(),
            TaskType::Analysis,
        );

        let mut episode2 = Episode::new(
            "Test".to_string(),
            TaskContext::default(),
            TaskType::Analysis,
        );

        // Add same tags in same order
        let tag_vec: Vec<_> = tags.iter().cloned().collect();
        for tag in &tag_vec {
            episode1.add_tag(tag.clone()).unwrap();
            episode2.add_tag(tag.clone()).unwrap();
        }

        // Should have identical tags
        prop_assert_eq!(episode1.get_tags(), episode2.get_tags());

        // Tag presence should be identical
        for tag in &tag_vec {
            prop_assert_eq!(
                episode1.has_tag(tag),
                episode2.has_tag(tag)
            );
        }
    }
}

// ============================================================================
// Postcard Serialization Tests (Binary format used in storage)
// ============================================================================

#[cfg(test)]
mod postcard_tests {
    use super::*;

    proptest! {
        /// Test TaskContext postcard roundtrip
        #[test]
        fn task_context_postcard_roundtrip(
            language in proptest::option::of("[a-z]{2,10}"),
            framework in proptest::option::of("[a-z]{2,15}"),
            domain in "[a-z]{3,20}",
            tags in proptest::collection::vec("[a-z]{2,15}", 0..10)
        ) {
            let context = TaskContext {
                language,
                framework,
                complexity: ComplexityLevel::Moderate,
                domain,
                tags,
            };

            // Postcard roundtrip
            let serialized = postcard::to_allocvec(&context).expect("postcard serialize");
            let deserialized: TaskContext = postcard::from_bytes(&serialized).expect("postcard deserialize");
            assert_eq!(context, deserialized);
        }

        /// Test RewardScore postcard roundtrip
        #[test]
        fn reward_score_postcard_roundtrip(
            total in 0.0f32..2.0f32,
            base in 0.0f32..1.0f32,
            efficiency in 0.5f32..1.5f32,
        ) {
            let score = RewardScore {
                total,
                base,
                efficiency,
                complexity_bonus: 1.0,
                quality_multiplier: 1.0,
                learning_bonus: 0.0,
            };

            let serialized = postcard::to_allocvec(&score).expect("postcard serialize");
            let deserialized: RewardScore = postcard::from_bytes(&serialized).expect("postcard deserialize");

            assert!((score.total - deserialized.total).abs() < 0.001);
        }

        /// Test Episode postcard serialization with DateTime handling
        /// Note: DateTime fields may require special handling in postcard
        #[test]
        fn episode_postcard_size_check(
            task_description in "[a-zA-Z0-9 ]{1,200}",
            num_steps in 0usize..20usize
        ) {
            let mut episode = Episode::new(
                task_description.clone(),
                TaskContext::default(),
                TaskType::CodeGeneration,
            );

            // Add steps
            for i in 0..num_steps {
                let step = ExecutionStep::new(
                    i + 1,
                    format!("tool_{}", i % 10),
                    format!("Action {i}")
                );
                episode.add_step(step);
            }

            // Postcard serialization - DateTime may have compatibility issues
            // Test that we can at least attempt serialization without panic
            let serialized = postcard::to_allocvec(&episode);

            // If serialization succeeds, verify roundtrip
            if let Ok(bytes) = serialized {
                let deserialized: StdResult<Episode, _> = postcard::from_bytes(&bytes);
                // Episode contains chrono::DateTime which may not serialize cleanly with postcard
                // This test documents the behavior rather than enforcing success
                if let Ok(de) = deserialized {
                    prop_assert_eq!(episode.steps.len(), de.steps.len());
                }
            }
            // If serialization fails, that's acceptable for this test
            // as it documents the limitation
        }
    }
}

// ============================================================================
// Property Test Configuration
// ============================================================================

/// Custom test runner configuration for expensive tests
fn configure_proptest() -> ProptestConfig {
    ProptestConfig {
        cases: 100,           // Number of test cases to run
        max_shrink_iters: 50, // Max shrinking iterations on failure
        ..ProptestConfig::default()
    }
}

// Example of using custom config for specific test groups
proptest! {
    #![proptest_config(configure_proptest())]

    /// Comprehensive integration test with more cases
    #[test]
    fn comprehensive_episode_lifecycle(
        task_type in prop::sample::select(vec![
            TaskType::CodeGeneration,
            TaskType::Testing,
            TaskType::Debugging,
        ]),
        complexity in prop::sample::select(vec![
            ComplexityLevel::Simple,
            ComplexityLevel::Moderate,
            ComplexityLevel::Complex,
        ]),
        num_steps in 0usize..100usize,
    ) {
        let context = TaskContext {
            language: Some("rust".to_string()),
            framework: Some("tokio".to_string()),
            complexity,
            domain: "test-domain".to_string(),
            tags: vec!["test".to_string()],
        };

        let mut episode = Episode::new(
            "Comprehensive test".to_string(),
            context,
            task_type,
        );

        // Add varying number of steps
        for i in 0..num_steps {
            let result = if i % 3 == 0 {
                ExecutionResult::Error { message: "Error".to_string() }
            } else {
                ExecutionResult::Success { output: "OK".to_string() }
            };

            let mut step = ExecutionStep::new(
                i + 1,
                format!("step_{i}"),
                "Action".to_string()
            );
            step.result = Some(result);
            episode.add_step(step);
        }

        // Complete episode
        episode.complete(TaskOutcome::Success {
            verdict: "Completed".to_string(),
            artifacts: vec![],
        });

        // Verify invariants
        prop_assert!(episode.is_complete());
        prop_assert_eq!(episode.steps.len(), num_steps);
        prop_assert!(episode.duration().is_some());

        // Serialization roundtrip
        let json = serde_json::to_string(&episode).expect("serialize");
        let deserialized: Episode = serde_json::from_str(&json).expect("deserialize");
        prop_assert_eq!(episode.steps.len(), deserialized.steps.len());
    }
}