ktsu.Containers 1.0.5

ktsu.Containers

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

🚀 Features

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

📦 Collections

OrderedCollection<T>

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<T>, IReadOnlyCollection<T>, IReadOnlyList<T>

Best Use Cases:

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

OrderedSet<T>

A set implementation that maintains unique elements in sorted order.

Key Features:

• O(log n) Add/Remove/Contains operations
• Full ISet<T> 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<T>

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

🏆 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<T> + Sort vs SortedList<T>
• OrderedSet vs HashSet<T> vs SortedSet<T>
• RingBuffer vs Queue<T> vs List<T> with size limiting

📊 Standard Collection Baselines

Performance baselines for all major .NET collections:

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

🔄 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

📈 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

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

📋 Installation

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

🔧 Usage Examples

OrderedCollection<T>

// 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<T>

// 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<T>

// 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)

🛠️ 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

📊 Performance Characteristics

OrderedCollection<T>

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

OrderedSet<T>

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

RingBuffer<T>

• ✅ 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

📝 License

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

🏗️ 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.