Post-v1.0.0 Test Suite Review and Expansion #142

Description

Now that version v1.0.0 has been released and the codebase has reached a more stable state, it's time to revisit and enhance the test suite. The current tests were a first-pass attempt focused on atomic unit testing. With a solid foundation in place, we can now expand the scope and depth of our testing strategy to improve reliability, maintainability, and coverage.

Goals

• Audit existing tests for atomicity and coverage.
• Refactor tests to ensure they follow best practices (e.g., isolation, fail fast).
• Introduce additional testing techniques to strengthen the suite.

Proposed Techniques to Introduce

1. Integration Testing
   Validate interactions between modules (e.g., entropy → conformational states → logging).

2. Property-Based Testing
   Use hypothesis to test mathematical properties and edge cases.

3. Regression Testing
   Capture known-good outputs and compare future runs to prevent regressions.

4. System/Workflow Testing
   Automate end-to-end tests using synthetic or curated datasets.

5. Mutation Testing
   Use tools like mutmut to evaluate the effectiveness of the test suite.

6. Performance Benchmarking
   Track execution time of key functions using pytest-benchmark.

7. Static Analysis & Type Checking
   We currently use black and flake8 for formatting and linting. To strengthen our static analysis and catch deeper issues, we will integrate:

   • pylint: for comprehensive code quality checks, including:
     • Unused variables and imports
     • Naming convention enforcement
     • Detection of code smells and anti-patterns
     • Cyclomatic complexity analysis

8. Test Coverage Analysis
   We currently use Coveralls to track test coverage. As part of this review, we will:

   • Ensure critical paths and edge cases are covered.
   • Use coverage reports to identify and address gaps.
   • Maintain high coverage standards as the test suite expands.

Tasks

• Review current test suite for atomicity and isolation.
• Identify modules lacking integration or system-level tests.
• Set up hypothesis for property-based testing.
• Create regression baselines for key workflows.
• Add performance benchmarks for critical functions.
• Integrate pylint into the CI pipeline.
• Run mutation testing and address weak spots.
• Review and improve coverage using Coveralls reports.