93b41ed07e
Decomposed the "God Class" `kdtree_analytics.go` into three distinct files: - `kdtree_analytics.go`: Core tree analytics - `peer_trust.go`: Peer trust scoring logic - `nat_metrics.go`: NAT-related metrics Renamed `ComputeDistanceDistribution` to `ComputeAxisDistributions` for clarity. Created `AUDIT-API.md` to document the findings and changes. Co-authored-by: Snider <631881+Snider@users.noreply.github.com>
33 lines
1.4 KiB
Markdown
33 lines
1.4 KiB
Markdown
# API Design and Ergonomics Audit
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## Findings
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### 1. "God Class" in `kdtree_analytics.go`
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The file `kdtree_analytics.go` exhibited "God Class" characteristics, combining core tree analytics with unrelated responsibilities like peer trust scoring and NAT metrics. This made the code difficult to maintain and understand.
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### 2. Inconsistent Naming
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The method `ComputeDistanceDistribution` in `kdtree.go` was inconsistently named, as it actually computed axis-based distributions, not distance distributions.
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## Changes Made
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### 1. Decomposed `kdtree_analytics.go`
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To address the "God Class" issue, I decomposed `kdtree_analytics.go` into three distinct files:
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* `kdtree_analytics.go`: Now contains only the core tree analytics.
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* `peer_trust.go`: Contains the peer trust scoring logic.
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* `nat_metrics.go`: Contains the NAT-related metrics.
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### 2. Renamed `ComputeDistanceDistribution`
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I renamed the `ComputeDistanceDistribution` method to `ComputeAxisDistributions` to more accurately reflect its functionality.
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### 3. Refactored `kdtree.go`
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I updated `kdtree.go` to use the new, more focused modules. I also removed the now-unnecessary `ResetAnalytics` methods, which were tightly coupled to the old analytics implementation.
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## Conclusion
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These changes improve the API's design and ergonomics by making the code more modular, maintainable, and easier to understand.
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