ndhanvina/simple-sentiment-analysis-ml

Implement unit tests and testing framework

Ouverte

#5 ouverte le 2 août 2025

 (0 commentaire) (0 réaction) (0 personne assignée) (0 fork)auto 404
good first issuequality assurancetesting

Métriques du dépôt

Stars
 (0 étoile)
Métriques de merge PR
 (Métriques PR en attente)

Description

Task Description

Implement comprehensive unit tests to ensure code reliability and maintainability.

Requirements

  • Set up pytest testing framework
  • Create test files for all main modules:
    • tests/test_data_preprocessing.py
    • tests/test_model.py
    • tests/test_utils.py
  • Implement test cases covering:
    • Data loading and validation
    • Text preprocessing functions
    • Model training and prediction
    • Error handling scenarios
    • Edge cases

Test Coverage Areas

Data Preprocessing Tests

  • Test text cleaning functions with various inputs
  • Test preprocessing pipeline with edge cases
  • Test data loading with valid/invalid files
  • Test data statistics calculation

Model Tests

  • Test model initialization
  • Test training with different datasets
  • Test prediction functionality
  • Test model save/load operations
  • Test evaluation metrics calculation

Integration Tests

  • Test end-to-end pipeline
  • Test model comparison functionality
  • Test with different data formats

Testing Framework Setup

  • Add pytest to requirements.txt
  • Create pytest configuration file (pytest.ini or pyproject.toml)
  • Set up test data fixtures
  • Configure test coverage reporting

Acceptance Criteria

  • All test files are created and properly structured
  • Test coverage is at least 80%
  • All tests pass successfully
  • Tests include both positive and negative test cases
  • Mock objects are used appropriately for external dependencies
  • Test data fixtures are properly set up
  • CI/CD integration is considered (GitHub Actions workflow)
  • Tests are well-documented with clear descriptions

Guide contributeur