Poindexter/AUDIT-API.md
2026-02-02 06:33:56 +00:00

4.8 KiB

API Audit: Poindexter Go Library

This document audits the public API of the Poindexter Go library, focusing on design, consistency, documentation, and security best practices for a Go library.

1. API Design and Consistency

1.1. Naming Conventions

  • Consistency: The library generally follows Go's naming conventions (camelCase for unexported, PascalCase for exported).
  • Clarity: Function names are clear and descriptive (e.g., SortInts, SortByKey, NewKDTree).
  • Minor Inconsistency: IsSorted exists, but IsSortedStrings and IsSortedFloat64s are more verbose. A more consistent naming scheme might be IntsAreSorted, StringsAreSorted, etc., to mirror the standard library's sort package.

1.2. Generics

  • Effective Use: The use of generics in SortBy and SortByKey is well-implemented and improves type safety and usability.
  • KDPoint: The KDPoint struct effectively uses generics for its Value field, allowing users to associate any data type with a point.

1.3. Error Handling

  • Exported Errors: The library exports sentinel errors (ErrEmptyPoints, ErrDimMismatch, etc.), which is a good practice, allowing users to check for specific error conditions.
  • Constructor Errors: The NewKDTree constructor correctly returns an error value, forcing callers to handle potential issues during tree creation.

1.4. Options Pattern

  • NewKDTree: The use of the options pattern with KDOption functions (WithMetric, WithBackend) is a great choice. It provides a flexible and extensible way to configure the KDTree without requiring a large number of constructor parameters.

2. Documentation

  • Package-Level: The package-level documentation is good, providing a clear overview of the library's features.
  • Exported Symbols: All exported functions, types, and constants have clear and concise documentation comments.
  • Examples: The README.md includes excellent quick-start examples, and the examples/ directory provides more detailed, runnable examples.

3. Security

3.1. Input Validation

  • NewKDTree: The constructor performs thorough validation of its inputs, checking for empty point sets, zero dimensions, and dimensional mismatches. This prevents the creation of invalid KDTree instances.
  • KDTree Methods: Methods like Nearest and KNearest validate the dimensionality of the query vector, preventing panics or incorrect behavior.
  • DeleteByID: This method correctly handles cases where the ID is not found or is empty.

3.2. Panics

  • The public API appears to be free of potential panics. The library consistently uses error returns and input validation to handle exceptional cases.

4. Recent API Design and Ergonomics Improvements

4.1. "God Class" Refactoring in kdtree_analytics.go

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.

Changes Made: To address the "God Class" issue, kdtree_analytics.go was decomposed into three distinct files:

  • kdtree_analytics.go: Now contains only the core tree analytics.
  • peer_trust.go: Contains the peer trust scoring logic.
  • nat_metrics.go: Contains the NAT-related metrics.

4.2. Method Naming Improvements

The method ComputeDistanceDistribution in kdtree.go was inconsistently named, as it actually computed axis-based distributions, not distance distributions.

Changes Made: Renamed the ComputeDistanceDistribution method to ComputeAxisDistributions to more accurately reflect its functionality.

4.3. Refactored kdtree.go

Updated kdtree.go to use the new, more focused modules. Removed the now-unnecessary ResetAnalytics methods, which were tightly coupled to the old analytics implementation.

Summary and Recommendations

The Poindexter library's public API is well-designed, consistent, and follows Go best practices. The use of generics, the options pattern, and clear error handling make it a robust and user-friendly library. Recent refactoring efforts have improved modularity and maintainability.

Recommendations:

  1. Naming Consistency: Consider renaming IsSorted, IsSortedStrings, and IsSortedFloat64s to IntsAreSorted, StringsAreSorted, and Float64sAreSorted to align more closely with the standard library's sort package.
  2. Defensive Copying: The Points() method returns a copy of the internal slice, which is excellent. Ensure that any future methods that expose internal state also return copies to prevent mutation by callers.
  3. Continued Modularization: The recent decomposition of kdtree_analytics.go is a positive step. Continue to evaluate the codebase for opportunities to separate concerns and improve maintainability.