This issue addresses multiple problems identified in the item system, such as #180, #191, #192, #193, and many unknown ones. The goal is to refactor the item management data layer to resolve these issues while adhering to project standards and meeting expected behavior.
Objectives
Enhance Performance: Optimize data storage and retrieval to minimize response times and reduce server load. Improve caching mechanisms and streamline database queries to handle large-scale operations more efficiently.
Improve Maintainability: Simplify the overall structure by breaking down complex functionalities into smaller, well-documented components. The code should be easier to understand, debug, and modify for future developers.
Increase Scalability: Design the system to handle increased user traffic and data volume without significant performance degradation. Utilize load balancing and horizontal scaling strategies to ensure stability under heavy loads.
Ensure Code Quality: Follow established coding standards and best practices to enhance readability and consistency across the codebase.
Strengthen Testing: Build comprehensive unit tests (also introducing mutation testing would be a nice-to-have) to cover all critical functions, ensuring that changes don’t introduce new bugs or regressions.
Ensure Flexibility: Use a modular, loosely-coupled architecture to allow future features to be easily integrated. This will ensure the system can evolve with new requirements without major rewrites or disruptions.
Overview
This issue addresses multiple problems identified in the item system, such as #180, #191, #192, #193, and many unknown ones. The goal is to refactor the item management data layer to resolve these issues while adhering to project standards and meeting expected behavior.
Objectives