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Epic: Comprehensive Integration Test Coverage for All Modules #615

@ooples

Description

@ooples

Overview

This epic tracks the creation of comprehensive integration tests for all modules in the AiDotNet library. The goal is to:

  1. Find bugs through edge cases, numerical stability testing, and error condition handling
  2. Verify correctness by comparing against established frameworks (PyTorch, scikit-learn, TensorFlow)

Testing Philosophy

All integration tests should:

  • NOT trust the code - verify mathematical correctness independently
  • Test edge cases (empty inputs, single elements, very large/small values)
  • Test numerical stability (NaN, Infinity, very small gradients)
  • Test error handling (mismatched dimensions, invalid parameters)
  • Compare results against reference implementations where possible
  • Test serialization/deserialization round-trips
  • Test Clone() produces identical behavior

Child Issues Summary

Total: 53 child issues created

P0 - CRITICAL (6 issues)

Issue Module Coverage Files
#616 NeuralNetworks 0% 110+
#617 Clustering 0% 90+
#618 Optimizers 7% 42
#619 LossFunctions 85% 34
#620 DecompositionMethods 62% 21
#621 Regression 0% 45

P1 - HIGH (7 issues)

Issue Module Files
#622 ReinforcementLearning 83
#623 MetaLearning 3
#624 FeatureSelectors 8
#625 CrossValidators 9
#626 Preprocessing 5
#627 Engines 1
#628 Autodiff 5

P2 - MEDIUM (14 issues)

Issue Module Files
#630 ActiveLearning 46
#631 AdversarialRobustness 15
#632 Augmentation 58
#633 ContinualLearning 36
#634 CurriculumLearning 18
#635 FederatedLearning 60
#636 KnowledgeDistillation 46
#637 PhysicsInformed 49
#638 SelfSupervisedLearning 56
#639 NestedLearning 2
#640 FineTuning 16
#641 LoRA 37
#642 MixedPrecision 4
#643 Pruning 5

P3 - STANDARD (30 issues)

Issue Module Files
#644 Agents 7
#645 Benchmarking 16
#646 CheckpointManagement 2
#647 ComputerVision 59
#648 Configuration 37
#649 DataProcessor 1
#650 DataVersionControl 2
#651 DataVersioning 2
#652 Deployment 51
#653 Diagnostics 2
#654 DistributedTraining 34
#655 Evaluation 2
#656 ExperimentTracking 2
#657 HyperparameterOptimization 9
#658 InferenceOptimization 36
#659 Interpretability 18
#660 JitCompiler 228
#661 LanguageModels 9
#662 Logging 9
#663 Metrics 9
#664 ModelRegistry 2
#665 ProgramSynthesis 104
#666 PromptEngineering 48
#667 Prototypes 5
#668 Reasoning 56
#669 Serialization 6
#670 Serving 8
#671 Tokenization 25
#672 Tools 22
#673 TrainingMonitoring 16

Existing Tests (Complete - May Need Review)

These modules already have integration tests:

  • Classification - 8 test files (PR test: add comprehensive classification integration tests #614)
  • Helpers - 14 test files
  • Statistics - 15 test files
  • AdvancedLinearAlgebra - 15 test files
  • LinearAlgebra - 5 test files
  • AutoML - 5 test files
  • TransferLearning - 3 test files
  • Genetics - 2 test files
  • Geometry - 2 test files
  • Caching - 3 test files
  • FitDetectors - 3 test files
  • And 20+ more single-file test modules...

Progress Tracking

Priority Issues Status
P0 Critical 6 All issues created
P1 High 7 All issues created
P2 Medium 14 All issues created
P3 Standard 30 All issues created
Total 57 All created

Definition of Done

A module is considered complete when:

  1. All public classes have integration tests
  2. Edge cases are tested (empty, null, boundary values)
  3. Numerical stability is verified (no NaN/Infinity leaks)
  4. Error handling is tested (appropriate exceptions thrown)
  5. Serialization round-trip works correctly
  6. Clone() produces identical predictions
  7. Tests pass on both net8.0 and net471
  8. Code coverage for the module is at least 80%

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