132 lines
9.1 KiB
Plaintext
132 lines
9.1 KiB
Plaintext
# Task ID: 50
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# Title: Implement Test Coverage Tracking System by Task
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# Status: pending
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# Dependencies: None
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# Priority: medium
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# 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.
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# Details:
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Develop a comprehensive test coverage tracking system with the following components:
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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.
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2. Build a generator that processes code coverage reports and updates the `tests.json` file to maintain an accurate mapping between tests and tasks.
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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.
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4. Create CLI commands that can:
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- Display test coverage for a specific task/subtask
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- Identify untested code related to a particular task
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- Generate test suggestions for uncovered code using LLMs
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5. Extend the MCP (Mission Control Panel) to visualize test coverage by task, showing percentage covered and highlighting areas needing tests.
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6. Develop an automated test generation system that uses LLMs to create targeted tests for specific uncovered code sections within a task.
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7. Implement a workflow that integrates with the existing task management system, allowing developers to see test requirements alongside implementation requirements.
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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.
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# Test Strategy:
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Testing should verify all components of the test coverage tracking system:
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1. **File Structure Tests**: Verify the `tests.json` file is correctly created and follows the expected schema with proper task/test relationships.
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2. **Coverage Report Processing**: Create mock coverage reports and verify they are correctly parsed and integrated into the `tests.json` file.
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3. **CLI Command Tests**: Test each CLI command with various inputs:
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- Test coverage display for existing tasks
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- Edge cases like tasks with no tests
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- Tasks with partial coverage
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4. **Integration Tests**: Verify the entire workflow from code changes to coverage reporting to task-based test suggestions.
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5. **LLM Test Generation**: Validate that generated tests actually cover the intended code paths by running them against the codebase.
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6. **UI/UX Tests**: Ensure the MCP correctly displays coverage information and that the interface for viewing and managing test coverage is intuitive.
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7. **Performance Tests**: Measure the performance impact of the coverage tracking system, especially for large codebases.
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Create a test suite that can run in CI/CD to ensure the test coverage tracking system itself maintains high coverage and reliability.
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# Subtasks:
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## 1. Design and implement tests.json data structure [pending]
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### Dependencies: None
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### 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.
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### Details:
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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.
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2. Implement bidirectional relationships by creating references between tests.json and tasks.json.
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3. Define fields for tracking statement coverage, branch coverage, and function coverage per task.
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4. Add metadata fields for test quality metrics beyond coverage (complexity, mutation score).
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5. Create utility functions to read/write/update the tests.json file.
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6. Implement validation logic to ensure data integrity between tasks and tests.
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7. Add version control compatibility by using relative paths and stable identifiers.
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8. Test the data structure with sample data representing various test scenarios.
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9. Document the schema with examples and usage guidelines.
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## 2. Develop coverage report parser and adapter system [pending]
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### Dependencies: 50.1
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### 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.
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### Details:
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1. Research and document output formats for major coverage tools (Istanbul/nyc, Jest, Pytest, JaCoCo).
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2. Design a normalized intermediate coverage format that any test tool can map to.
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3. Implement adapter classes for each major testing framework that convert their reports to the intermediate format.
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4. Create a parser registry that can automatically detect and use the appropriate parser based on input format.
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5. Develop a mapping algorithm that associates coverage data with specific tasks based on file paths and code blocks.
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6. Implement file path normalization to handle different operating systems and environments.
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7. Add error handling for malformed or incomplete coverage reports.
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8. Create unit tests for each adapter using sample coverage reports.
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9. Implement a command-line interface for manual parsing and testing.
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10. Document the extension points for adding custom coverage tool adapters.
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## 3. Build coverage tracking and update generator [pending]
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### Dependencies: 50.1, 50.2
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### 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.
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### Details:
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1. Implement a coverage processor that takes parsed coverage data and maps it to task IDs.
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2. Create algorithms to calculate aggregate coverage metrics at the task and subtask levels.
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3. Develop a change detection system that identifies when tests or code have changed and require updates.
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4. Implement incremental update logic to avoid reprocessing unchanged tests.
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5. Create a task-code association system that maps specific code blocks to tasks for granular tracking.
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6. Add historical tracking to monitor coverage trends over time.
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7. Implement hooks for CI/CD integration to automatically update coverage after test runs.
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8. Create a conflict resolution strategy for when multiple tests cover the same code areas.
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9. Add performance optimizations for large codebases and test suites.
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10. Develop unit tests that verify correct aggregation and mapping of coverage data.
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11. Document the update workflow with sequence diagrams and examples.
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## 4. Implement CLI commands for coverage operations [pending]
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### Dependencies: 50.1, 50.2, 50.3
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### Description: Create a set of command-line interface tools that allow developers to view, analyze, and manage test coverage at the task level.
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### Details:
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1. Design a cohesive CLI command structure with subcommands for different coverage operations.
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2. Implement 'coverage show' command to display test coverage for a specific task/subtask.
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3. Create 'coverage gaps' command to identify untested code related to a particular task.
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4. Develop 'coverage history' command to show how coverage has changed over time.
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5. Implement 'coverage generate' command that uses LLMs to suggest tests for uncovered code.
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6. Add filtering options to focus on specific test types or coverage thresholds.
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7. Create formatted output options (JSON, CSV, markdown tables) for integration with other tools.
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8. Implement colorized terminal output for better readability of coverage reports.
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9. Add batch processing capabilities for running operations across multiple tasks.
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10. Create comprehensive help documentation and examples for each command.
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11. Develop unit and integration tests for CLI commands.
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12. Document command usage patterns and example workflows.
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## 5. Develop AI-powered test generation system [pending]
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### Dependencies: 50.1, 50.2, 50.3, 50.4
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### 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.
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### Details:
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1. Design prompt templates for different test types (unit, integration, E2E) that incorporate task descriptions and code context.
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2. Implement code analysis to extract relevant context from uncovered code sections.
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3. Create a test generation pipeline that combines task metadata, code context, and coverage gaps.
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4. Develop strategies for maintaining test context across task changes and updates.
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5. Implement test quality evaluation to ensure generated tests are meaningful and effective.
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6. Create a feedback mechanism to improve prompts based on acceptance or rejection of generated tests.
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7. Add support for different testing frameworks and languages through templating.
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8. Implement caching to avoid regenerating similar tests.
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9. Create a workflow that integrates with the task management system to suggest tests alongside implementation requirements.
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10. Develop specialized generation modes for edge cases, regression tests, and performance tests.
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11. Add configuration options for controlling test generation style and coverage goals.
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12. Create comprehensive documentation on how to use and extend the test generation system.
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13. Implement evaluation metrics to track the effectiveness of AI-generated tests.
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