Review update.

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@ -20,3 +20,38 @@ Using my software comes with unlimited warranty. I do take full responsibility f
## Review summary.
This README file is only a summary of the detailed reviews in the [Reviews](.reviews/) directory. The summary could be bigger, but I limited it to something you would actually read. Every file is reviewed in detail and contains metadata like grade, size and line count. In general, this source code is high quality, graded like 8 on average and even a few 9's. 9's are quite exceptional. But a few parts of this source also had the record of worst code (graded a 4, not seen that before).
## General Information
- **Grade**: Average grade across files is **7.48**.
- **Total Lines**: 2000 lines of code.
- **Code Size**: 66,871 bytes.
## Strengths
1. **Well-structured Code**: Organized with clear namespaces, extensions, and separation of concerns.
2. **Modern Swift Features**: Utilizes `Codable`, `Sendable`, and `Hashable` for data modeling and concurrency.
3. **Documentation**: Adequate inline comments enhance maintainability and comprehension.
4. **Error Handling**: Effective optional handling and decoding patterns in most files.
5. **Platform-Specific Handling**: Implements conditional compilation for iOS/macOS distinctions.
## Areas for Improvement
1. **Consistency**: Property naming between `CodingData` structs and main models could be more uniform.
2. **Validation**: Input validation is minimal, especially for dates and optional values.
3. **Optimization Opportunities**:
- Replace string dates with `Date` types where applicable.
- Optimize frequently used operations like dictionary lookups or decoding.
4. **Redundant Access Modifiers**: Some files use unnecessary `public` keywords in extensions.
5. **Error Logging**: Limited error logging in decoding or transformation methods.
## Highlights of Specific Components
- **Rant Feed**: Well-structured but optional handling could be refined.
- **Notifications**: Comprehensive with mappings and unread counts but could use caching for user lookups.
- **Image Handling**: Covers multiple formats effectively but has room for more abstracted platform-specific logic.
## Suggested Focus Areas
1. **Testing and Validation**: Introduce validation checks and testing for edge cases like unexpected input formats.
2. **Performance**: Optimize decoding and data transformations, especially for large datasets.
3. **Readability**: Simplify and comment on complex decoding logic for maintainability.
## Summary
The project is well-built with modern Swift practices but could benefit from consistency and performance enhancements.