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ktsu.Containers

A high-performance collection library for .NET providing specialized container implementations with focus on performance, memory efficiency, and developer experience.

πŸš€ Features

  • OrderedCollection: Maintains elements in sorted order with efficient binary search operations
  • OrderedSet: Unique elements maintained in sorted order with full ISet support
  • RingBuffer: Fixed-size circular buffer optimized for streaming data scenarios
  • Comprehensive Benchmarking: World-class performance validation against .NET collections

πŸ“¦ Collections

OrderedCollection

A collection that maintains elements in sorted order with efficient insertion and search operations.

Key Features:

  • O(log n) insertion maintaining sort order
  • O(log n) search operations via binary search
  • Multiple constructors with capacity and comparer support
  • Implements ICollection, IReadOnlyCollection, IReadOnlyList

Best Use Cases:

  • Incremental sorted data building
  • Frequent search operations on ordered data
  • Scenarios requiring both order and random access

OrderedSet

A set implementation that maintains unique elements in sorted order.

Key Features:

  • O(log n) Add/Remove/Contains operations
  • Full ISet interface support (Union, Intersection, Except, etc.)
  • Sorted enumeration without additional sorting cost
  • Memory-efficient list-based implementation

Best Use Cases:

  • Unique sorted collections
  • Set operations with maintained order
  • Mathematical set operations with sorted results

RingBuffer

A fixed-size circular buffer optimized for continuous data streams.

Key Features:

  • O(1) insertion and access operations
  • Automatic wrapping when capacity is reached
  • Index-based access to buffer elements
  • Resizing and resampling capabilities
  • Power-of-two sizing for optimal performance

Best Use Cases:

  • Streaming data processing
  • Fixed-size caches
  • Sliding window algorithms
  • Audio/signal processing buffers

πŸ† Performance & Benchmarking

We've implemented a comprehensive benchmarking system using BenchmarkDotNet that validates our implementations against standard .NET collections.

Benchmark Categories

🎯 Container-Specific Benchmarks

  • OrderedCollection vs List + Sort vs SortedList
  • OrderedSet vs HashSet vs SortedSet
  • RingBuffer vs Queue vs List with size limiting

πŸ“Š Standard Collection Baselines

Performance baselines for all major .NET collections:

  • List, HashSet, SortedSet
  • Dictionary<TKey,TValue>, SortedDictionary<TKey,TValue>
  • Queue, Stack
  • ConcurrentDictionary<TKey,TValue>, ConcurrentQueue

πŸ”„ Cross-Collection Comparisons

Direct comparisons for common scenarios:

  • Building ordered collections (incremental vs bulk)
  • Set operations across different implementations
  • Memory efficiency patterns
  • Real-world usage workflows

πŸ“ˆ Performance Analysis

Advanced scenarios including:

  • Scalability testing (1K to 100K+ elements)
  • Edge cases and worst-case scenarios
  • Memory pressure analysis
  • Specialized use cases (sliding windows, priority queues)

Running Benchmarks

Quick Start

# Fast development feedback
.\scripts\run-benchmarks.ps1 -Target Quick

# Compare specific containers
.\scripts\run-benchmarks.ps1 -Target OrderedSet -Export Html

# Cross-collection analysis
.\scripts\run-benchmarks.ps1 -Target CrossComparison -Export All

# Full benchmark suite
.\scripts\run-benchmarks.ps1 -Target All -Export Html

Available Targets

Target Description
Quick Fast subset for development feedback
OrderedCollection OrderedCollection vs alternatives
OrderedSet OrderedSet vs alternatives
RingBuffer RingBuffer vs alternatives
Standard Built-in .NET collection baselines
CrossComparison Direct cross-collection comparisons
PerformanceAnalysis Scalability and edge case analysis
All Complete benchmark suite

Command Line Options

# Manual benchmark execution
dotnet run --project Containers.Benchmarks --configuration Release

# Filtered benchmarks
dotnet run --project Containers.Benchmarks --configuration Release -- --filter "*Add*"

# Export results
dotnet run --project Containers.Benchmarks --configuration Release -- --exporters html,csv,json

πŸ“‹ Installation

<PackageReference Include="ktsu.Containers" Version="1.0.0" />

πŸ”§ Usage Examples

OrderedCollection

// Create and populate
var collection = new OrderedCollection<int>();
collection.Add(3);
collection.Add(1);
collection.Add(2);
// Collection automatically maintains order: [1, 2, 3]

// Efficient search
bool contains = collection.Contains(2); // O(log n) binary search

// Access by index
int first = collection[0]; // 1

OrderedSet

// Create with initial data
var set = new OrderedSet<int> { 3, 1, 4, 1, 5 };
// Set contains unique elements in order: [1, 3, 4, 5]

// Set operations
var other = new OrderedSet<int> { 4, 5, 6 };
set.UnionWith(other); // [1, 3, 4, 5, 6]

RingBuffer

// Create fixed-size buffer
var buffer = new RingBuffer<int>(3);
buffer.PushBack(1);
buffer.PushBack(2);
buffer.PushBack(3);
buffer.PushBack(4); // Overwrites first element
// Buffer contains: [2, 3, 4]

// Index access
int latest = buffer[buffer.Count - 1]; // 4 (most recent)

πŸ› οΈ Development

Building

dotnet build

Testing

dotnet test

Benchmarking

# Quick performance check
.\scripts\run-benchmarks.ps1 -Target Quick

# Comprehensive analysis
.\scripts\run-benchmarks.ps1 -Target All -Export Html

πŸ“Š Performance Characteristics

OrderedCollection

  • βœ… Excellent for: Incremental sorted insertions, frequent searches
  • ⚠️ Consider alternatives for: Large bulk operations (List + Sort may be faster)
  • 🎯 Sweet spot: 100-10,000 elements with mixed insert/search operations

OrderedSet

  • βœ… Excellent for: Unique sorted collections, set operations with order
  • ⚠️ Consider alternatives for: Pure membership testing (HashSet is faster)
  • 🎯 Sweet spot: Mathematical set operations requiring sorted results

RingBuffer

  • βœ… Excellent for: Streaming data, fixed-size caches, sliding windows
  • ⚠️ Consider alternatives for: Dynamic growth requirements
  • 🎯 Sweet spot: Continuous data streams with occasional random access

🀝 Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Add comprehensive tests
  5. Run benchmarks to validate performance
  6. Submit a pull request

Adding New Containers

When adding new containers:

  1. Implement the container in Containers/
  2. Add comprehensive tests in Containers.Test/
  3. Create benchmark comparisons in Containers.Benchmarks/
  4. Update documentation

πŸ“ License

Licensed under the MIT License. See LICENSE.md for details.

πŸ—οΈ Architecture

The library is built with performance and reliability in mind:

  • Zero-allocation operations where possible
  • Power-of-two sizing for optimal memory access patterns
  • Binary search algorithms for O(log n) performance
  • Comprehensive test coverage ensuring reliability
  • Benchmark-driven development validating performance claims

🎯 Design Principles

  1. Performance First: Every operation is optimized for speed and memory efficiency
  2. Standard Compliance: Full compatibility with .NET collection interfaces
  3. Predictable Behavior: Clear performance characteristics and edge case handling
  4. Developer Experience: Intuitive APIs with comprehensive documentation
  5. Validation: Extensive testing and benchmarking ensures reliability

This library provides high-performance alternatives to standard .NET collections while maintaining familiar APIs and adding specialized functionality for common use cases.

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