Fix : Improve Backend Test Coverage from 65% to 95%

Description

The current backend test coverage is approximately 65%, which is below the expected quality standard of 95%. Increasing test coverage is critical to improving code reliability, minimizing production issues, and ensuring stability across complex AI/ML workflows such as streaming, background processing, and model integrations.

Objective

Increase the overall backend test coverage from 65% to 95% by implementing comprehensive unit and integration tests for under-tested modules and critical execution paths.

Current Challenges

The backend includes several complex components that make testing more challenging, including:

  • WebSocket-based real-time streaming logic
  • Background job processing and lifecycle management
  • AI/ML model integrations and inference workflows Additionally, the project relies on heavy external dependencies such as PyTorch, Transformers, and Librosa, which can increase test execution time and complexity. Several utility modules, fallback mechanisms, and error-handling paths currently have low or no test coverage.

Proposed Approach

  1. Identify Low-Coverage Modules

    • Analyze existing coverage reports to identify files and modules with coverage below 70%
    • Prioritize critical services, utilities, and workflow-related components

  2. Expand Unit Test Coverage

    • Add unit tests for core business logic, utility functions, and service layers
    • Include edge cases, exception handling, and fallback scenarios

  3. Mock External Dependencies

    • Use mocking frameworks to simulate AI/ML models, external APIs, and third-party services
    • Ensure tests remain fast, isolated, and reliable

  4. Validate State-Based Workflows

    • Add tests covering complete job lifecycle transitions such as:
      • Created → Processing → Completed
      • Created → Processing → Failed
    • Verify all possible state transitions and failure conditions

  5. Improve Async and Streaming Test Coverage

    • Simulate WebSocket communication and streaming workflows
    • Add coverage for VAD (Voice Activity Detection), buffering, and real-time event processing

  6. Add Targeted Coverage Improvements

    • Introduce focused tests for uncovered branches, fallback paths, and low-coverage utilities where necessary

Expected Outcome

  • Achieve 95% or higher overall test coverage
  • Improve reliability and resilience of backend workflows
  • Ensure robust handling of edge cases, failures, and asynchronous processing
  • Enhance maintainability and long-term code quality

Acceptance Criteria

  • Coverage report shows ≥95% total test coverage
  • All test cases pass successfully without failures
  • Critical modules such as services, streaming, and job management achieve ≥90% coverage
  • No significant degradation in test execution performance.
Edited by Vemuri priya