Generated: 2025-09-24
Excellent coverage for provider common functionality including authentication, rate limiting, and error handling.
Good coverage for configuration loading, validation, and environment overrides.
Tests cover basic provider functionality, message serialization, and connection handling.
Basic tests for Databento provider creation and configuration.
Tests for streaming provider creation and message serialization.
Tests for trait implementations and provider interfaces.
Tests for feature extraction and technical indicators.
Tests for data types, serialization, and validation.
⚠️ Gap: Large utility module with many uncovered helper functions for data processing, validation, and formatting.
⚠️ Gap: Main library module needs more comprehensive integration tests.
⚠️ Gap: Provider module coordination and management functions need testing.
⚠️ Gap: Interactive Brokers integration has extensive functionality that needs more test coverage.
⚠️ Gap: Complex feature extraction logic needs comprehensive testing.
⚠️ Gap: ML training pipeline has minimal test coverage for critical functionality.
Error handling and conversion tests.
Common broker functionality tests.
⚠️ Gap: Data validation logic needs more comprehensive testing.
🚨 Critical Gap: Database storage operations have no test coverage - this is critical for data integrity.
🚨 Critical Gap: Parquet file persistence has no tests - data corruption risks.
Example code - tests not necessarily required but recommended.
Module file - may only contain re-exports.
| File | Risk Level | Issue | Recommendation |
|---|---|---|---|
| storage.rs | 🚨 Critical | No tests for database operations | Add comprehensive tests for CRUD operations, transaction handling, and error scenarios |
| parquet_persistence.rs | 🚨 Critical | No tests for file persistence | Add tests for file I/O, compression, and data integrity |
| utils.rs | ⚠️ High | 8% coverage, 59 functions | Add tests for data processing utilities and helper functions |
| unified_feature_extractor.rs | ⚠️ High | 6% coverage, complex ML logic | Add tests for feature extraction algorithms and edge cases |
| training_pipeline.rs | ⚠️ High | 5% coverage, ML pipeline | Add tests for training workflow and model validation |
Current estimated functional coverage: ~15-20%
To reach 95% coverage, approximately 150-200 additional test functions needed.