# Task ID: 50
# Title: Implement Test Coverage Tracking System by Task
# Status: pending
# Dependencies: None
# Priority: medium
# Description: Create a system that maps test coverage to specific tasks and subtasks, enabling targeted test generation and tracking of code coverage at the task level.
# Details:
Develop a comprehensive test coverage tracking system with the following components:

1. Create a `tests.json` file structure in the `tasks/` directory that associates test suites and individual tests with specific task IDs or subtask IDs.

2. Build a generator that processes code coverage reports and updates the `tests.json` file to maintain an accurate mapping between tests and tasks.

3. Implement a parser that can extract code coverage information from standard coverage tools (like Istanbul/nyc, Jest coverage reports) and convert it to the task-based format.

4. Create CLI commands that can:
   - Display test coverage for a specific task/subtask
   - Identify untested code related to a particular task
   - Generate test suggestions for uncovered code using LLMs

5. Extend the MCP (Mission Control Panel) to visualize test coverage by task, showing percentage covered and highlighting areas needing tests.

6. Develop an automated test generation system that uses LLMs to create targeted tests for specific uncovered code sections within a task.

7. Implement a workflow that integrates with the existing task management system, allowing developers to see test requirements alongside implementation requirements.

The system should maintain bidirectional relationships: from tests to tasks and from tasks to the code they affect, enabling precise tracking of what needs testing for each development task.

# Test Strategy:
Testing should verify all components of the test coverage tracking system:

1. **File Structure Tests**: Verify the `tests.json` file is correctly created and follows the expected schema with proper task/test relationships.

2. **Coverage Report Processing**: Create mock coverage reports and verify they are correctly parsed and integrated into the `tests.json` file.

3. **CLI Command Tests**: Test each CLI command with various inputs:
   - Test coverage display for existing tasks
   - Edge cases like tasks with no tests
   - Tasks with partial coverage

4. **Integration Tests**: Verify the entire workflow from code changes to coverage reporting to task-based test suggestions.

5. **LLM Test Generation**: Validate that generated tests actually cover the intended code paths by running them against the codebase.

6. **UI/UX Tests**: Ensure the MCP correctly displays coverage information and that the interface for viewing and managing test coverage is intuitive.

7. **Performance Tests**: Measure the performance impact of the coverage tracking system, especially for large codebases.

Create a test suite that can run in CI/CD to ensure the test coverage tracking system itself maintains high coverage and reliability.

# Subtasks:
## 1. Design and implement tests.json data structure [pending]
### Dependencies: None
### Description: Create a comprehensive data structure that maps tests to tasks/subtasks and tracks coverage metrics. This structure will serve as the foundation for the entire test coverage tracking system.
### Details:
1. Design a JSON schema for tests.json that includes: test IDs, associated task/subtask IDs, coverage percentages, test types (unit/integration/e2e), file paths, and timestamps.
2. Implement bidirectional relationships by creating references between tests.json and tasks.json.
3. Define fields for tracking statement coverage, branch coverage, and function coverage per task.
4. Add metadata fields for test quality metrics beyond coverage (complexity, mutation score).
5. Create utility functions to read/write/update the tests.json file.
6. Implement validation logic to ensure data integrity between tasks and tests.
7. Add version control compatibility by using relative paths and stable identifiers.
8. Test the data structure with sample data representing various test scenarios.
9. Document the schema with examples and usage guidelines.

## 2. Develop coverage report parser and adapter system [pending]
### Dependencies: 50.1
### Description: Create a framework-agnostic system that can parse coverage reports from various testing tools and convert them to the standardized task-based format in tests.json.
### Details:
1. Research and document output formats for major coverage tools (Istanbul/nyc, Jest, Pytest, JaCoCo).
2. Design a normalized intermediate coverage format that any test tool can map to.
3. Implement adapter classes for each major testing framework that convert their reports to the intermediate format.
4. Create a parser registry that can automatically detect and use the appropriate parser based on input format.
5. Develop a mapping algorithm that associates coverage data with specific tasks based on file paths and code blocks.
6. Implement file path normalization to handle different operating systems and environments.
7. Add error handling for malformed or incomplete coverage reports.
8. Create unit tests for each adapter using sample coverage reports.
9. Implement a command-line interface for manual parsing and testing.
10. Document the extension points for adding custom coverage tool adapters.

## 3. Build coverage tracking and update generator [pending]
### Dependencies: 50.1, 50.2
### Description: Create a system that processes code coverage reports, maps them to tasks, and updates the tests.json file to maintain accurate coverage tracking over time.
### Details:
1. Implement a coverage processor that takes parsed coverage data and maps it to task IDs.
2. Create algorithms to calculate aggregate coverage metrics at the task and subtask levels.
3. Develop a change detection system that identifies when tests or code have changed and require updates.
4. Implement incremental update logic to avoid reprocessing unchanged tests.
5. Create a task-code association system that maps specific code blocks to tasks for granular tracking.
6. Add historical tracking to monitor coverage trends over time.
7. Implement hooks for CI/CD integration to automatically update coverage after test runs.
8. Create a conflict resolution strategy for when multiple tests cover the same code areas.
9. Add performance optimizations for large codebases and test suites.
10. Develop unit tests that verify correct aggregation and mapping of coverage data.
11. Document the update workflow with sequence diagrams and examples.

## 4. Implement CLI commands for coverage operations [pending]
### Dependencies: 50.1, 50.2, 50.3
### Description: Create a set of command-line interface tools that allow developers to view, analyze, and manage test coverage at the task level.
### Details:
1. Design a cohesive CLI command structure with subcommands for different coverage operations.
2. Implement 'coverage show' command to display test coverage for a specific task/subtask.
3. Create 'coverage gaps' command to identify untested code related to a particular task.
4. Develop 'coverage history' command to show how coverage has changed over time.
5. Implement 'coverage generate' command that uses LLMs to suggest tests for uncovered code.
6. Add filtering options to focus on specific test types or coverage thresholds.
7. Create formatted output options (JSON, CSV, markdown tables) for integration with other tools.
8. Implement colorized terminal output for better readability of coverage reports.
9. Add batch processing capabilities for running operations across multiple tasks.
10. Create comprehensive help documentation and examples for each command.
11. Develop unit and integration tests for CLI commands.
12. Document command usage patterns and example workflows.

## 5. Develop AI-powered test generation system [pending]
### Dependencies: 50.1, 50.2, 50.3, 50.4
### Description: Create an intelligent system that uses LLMs to generate targeted tests for uncovered code sections within tasks, integrating with the existing task management workflow.
### Details:
1. Design prompt templates for different test types (unit, integration, E2E) that incorporate task descriptions and code context.
2. Implement code analysis to extract relevant context from uncovered code sections.
3. Create a test generation pipeline that combines task metadata, code context, and coverage gaps.
4. Develop strategies for maintaining test context across task changes and updates.
5. Implement test quality evaluation to ensure generated tests are meaningful and effective.
6. Create a feedback mechanism to improve prompts based on acceptance or rejection of generated tests.
7. Add support for different testing frameworks and languages through templating.
8. Implement caching to avoid regenerating similar tests.
9. Create a workflow that integrates with the task management system to suggest tests alongside implementation requirements.
10. Develop specialized generation modes for edge cases, regression tests, and performance tests.
11. Add configuration options for controlling test generation style and coverage goals.
12. Create comprehensive documentation on how to use and extend the test generation system.
13. Implement evaluation metrics to track the effectiveness of AI-generated tests.

