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Rumen Dimov
Rumen Dimov

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πŸš€ Common C# Performance Optimization Myths

πŸ€” Common Myths That Don't Help

Performance optimization in C# is often misunderstood, leading developers to adopt practices that either have negligible impact or sometimes even hurt performance. Let's explore some common myths and learn what actually works.

1. πŸ” "LINQ is Always Clean and Fast Enough"

LINQ provides elegant and readable code, but it can introduce significant performance overhead. Each LINQ operation potentially creates intermediate collections and unnecessary iterations. While LINQ is excellent for development speed and maintainability, in performance-critical paths it can be a bottleneck.

linq myth performance

linq myth performance

2. πŸ“ "Always Pre-size Your Arrays"

Developers often believe that pre-sizing collections always improves performance. While pre-sizing can help when you know the exact size needed, arbitrarily choosing a large initial capacity can waste memory and potentially slow down your application. The built-in growth algorithms in collections like List are well-optimized for most scenarios.

Premature Array Sizing

3. πŸ—οΈ "Structs Are Always Better for Performance"

While value types can improve performance by reducing heap allocations and garbage collection, using large structs can actually degrade performance. Every time a struct is passed as a parameter or assigned to a variable, its entire contents are copied. For larger objects, this copying overhead can exceed any benefits from avoiding heap allocation.

Using struct Instead of class for Performance

⚑ Real Performance Optimizations That Work

1. 🎯 Efficient Memory Management with Span

Span is like a superhero for memory operations! It provides zero-allocation access to memory and eliminates bounds checking in tight loops.

Efficient Memory Management with Span<T>

2. πŸ”‘ Proper Value-Based Equality Implementation

Think of this as giving your objects a unique fingerprint. Good hash codes and equality implementations can make collections like Dictionary and HashSet blazing fast!

Proper Value-Based Equality Implementation

3. ♻️ Smart Array Pooling

Think of ArrayPool as a recycling center for arrays. Instead of creating new arrays all the time, we can reuse existing ones!

Smart Array Pooling

4. πŸ“ Optimized String Building

StringBuilderCache is like having a personal assistant for string operations. It keeps track of and reuses StringBuilder instances for you!

Optimized String Building

πŸ’‘ Pro Tips

🚦 Don't optimize prematurely - profile first!
πŸ“ Measure, don't guess
🎯 Focus on algorithms first, micro-optimizations last
πŸ§ͺ Always test performance changes with real-world data
πŸ“š Keep learning about new .NET performance features

There is a lot more that can be said and written about performance. In fact, there are books written on that subject but I wanted to share a few quick tips and share some of the common mistakes I have noticed people make. If I have gotten something wrong, please do correct me in the comments below. I always welcome cosntructive criticism, no one is perfect right! :)

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