Solution Strategy
Quality Goals and Architectural Approaches
Quality Goal | Solution Approach | Details |
---|---|---|
Extensibility |
* Abstract base classes * Plugin architecture * Clear interfaces |
* New rules can be added by extending base classes * Plugin system allows external rule packages * Well-defined interfaces for rule implementation |
Reliability |
* Comprehensive testing * Strong typing * Defensive programming |
* High test coverage * Type hints throughout the code * Careful input validation |
Usability |
* Clear error messages * Context information * Configuration options |
* Detailed error descriptions * Line and column information * Configurable rule severity |
Performance |
* Efficient algorithms * Lazy loading * Caching |
* Line-by-line processing * Rules loaded on demand * Cache parsing results |
Maintainability |
* Clean architecture * SOLID principles * Documentation |
* Clear separation of concerns * Single responsibility principle * Comprehensive documentation |
Technology Decisions
Technology | Decision | Rationale |
---|---|---|
Python |
Primary implementation language |
* Strong standard library * Great text processing capabilities * Wide adoption in tooling |
Regular Expressions |
Pattern matching |
* Built into Python * Efficient for text processing * Well understood by developers |
YAML |
Configuration format |
* Human readable * Standard format * Good library support |
unittest |
Testing framework |
* Part of Python standard library * Well known to developers * Good IDE support |
Implementation Patterns
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