Classes vs Structs: Performance Guide

Summary: Unlock the core differences between classes vs structs and learn when to use each for high-performance, predictable code in C#, Swift, C++, and more.

Introduction

The most important distinction in this space is simple: classes are reference types and structs are value types. That difference shapes memory layout, copy behavior, and runtime costs across languages such as C#, C++, and Swift. Choosing the right one improves predictability, reduces unnecessary allocations, and makes hot code paths faster.¹²

What Sets Classes and Structs Apart

When you create a class instance, the variable holds a reference to an object on the heap. Copying that variable copies the reference; multiple variables can point to the same object, so changes through one reference are visible through others. This identity semantics is why classes are a fit for entities that must be shared or mutated in place.¹

A struct contains the data itself. Instantiating a struct produces a concrete bundle of values—often stored on the stack or inline inside arrays—so copying a struct yields an independent duplicate. Mutating a copy does not affect the original, which makes structs well suited to simple, immutable values.¹

For practical guidance on encapsulation and object design, see our guide on object-oriented encapsulation: https://cleancodeguy.com/blog/object-oriented-encapsulation.

Quick comparison: reference vs value types

Use a class when you need shared identity. Use a struct when you want a self-contained value that can be copied without side effects.

This distinction drives performance trade-offs—heap vs stack allocation, cache locality, and garbage collection pressure—which follow.

How Memory Allocation Affects Speed

Memory layout influences CPU efficiency and latency. Accessing a class often requires one indirection: a pointer on the stack references data on the heap. That lookup adds cost and can harm cache behavior. Structs stored inline avoid that indirection and enable tighter memory layouts with better cache locality.⁵

Garbage collection costs

Heap objects are subject to garbage collection. GC cycles can introduce pauses and add CPU overhead, especially when many short-lived objects are allocated. Favoring value types for many small, transient objects reduces heap churn and lowers GC work.³

Heap allocation adds potential GC overhead. Structs avoid that overhead when they remain unboxed and stay value-based.

Cache locality and throughput

Modern CPUs depend on caches. Sequential memory layouts—such as arrays of structs—improve cache hits and throughput. Separate heap allocations for each class tend to scatter data and increase cache misses. In tight loops and data-processing pipelines, contiguous value layouts often give measurable throughput gains in practice.⁶⁵

The boxing trap

Boxing happens when a value type is converted to a reference type—for example, when placed into a collection that expects objects. Boxing allocates on the heap and copies the value into that object, negating the struct’s advantages and increasing GC load. Avoiding boxing is a core principle when using value types for performance-critical code.⁴

How Languages Differ: C#, C++, and Swift

Different languages enforce different rules and idioms. Apply language-specific guidance rather than assuming one model fits all.

C#: clear reference vs value model

In C#, class = reference type and struct = value type. Use classes for entities with identity (for example, Customer or DatabaseConnection) and structs for small, immutable values (for example, Point or Color). Keep structs small and immutable to avoid subtle bugs and copying overhead.¹

Common mistakes include making large or mutable structs; both can cause surprising behavior or performance regressions. Favor the immutable, small-struct guideline in performance-sensitive code.⁵

C++: convention over language restriction

In C++, the only syntactic difference between struct and class is default accessibility. Both can be allocated on the stack or heap, have methods, and support inheritance. The convention is to use struct for plain data aggregates and class for encapsulated objects and RAII resource management.

This flexibility means C++ developers must rely on conventions and design choices rather than language-enforced value/reference distinctions. For guidance on polymorphism and inheritance, see our C++ design notes: https://cleancodeguy.com/blog/polymorphism-vs-inheritance.

Swift: value-oriented by default

Swift encourages using structs for most custom types. Structs in Swift support methods, extensions, and protocol conformance, making them powerful and safe defaults. Choose classes only when reference semantics, identity, or Objective-C interoperability are required.²

Swift’s value-first approach encourages immutability and clearer reasoning about data flow, which is helpful in concurrent code.

When to Choose a Struct for Maximum Efficiency

Structs are ideal for small, immutable bundles of data whose identity is defined entirely by their values. Examples:

• Geometric data: Point2D or RGBColor
• Financial values: Money (amount + currency)
• Small DTOs used in high-throughput pipelines

A practical guideline is the “16–32 byte” rule: if a struct’s fields fit roughly in that range, copying cost is modest and often cheaper than heap allocation. If a struct grows larger or must be mutable, a class is likely the better choice.⁵

Immutability and size rules

• Prefer immutable structs: create values once and return new instances for state changes.
• Keep structs small: copying large structs frequently can be more expensive than passing references.

Following these rules avoids subtle bugs from mutable copies and performance traps from excessive copying or boxing.

Common pitfalls and refactoring

Two frequent problems are mutable structs and excessive boxing.

Mutable structs produce surprising behavior because changes affect only the copy. Refactor mutable structs into immutable ones that return new instances for state changes.

Boxing can happen implicitly in many APIs and collections; locate and remove boxing hotspots to preserve struct performance advantages.

Example: Refactor a mutable Point into an immutable struct (C#)

// PITFALL: Mutable struct
public struct MutablePoint
{
    public int X { get; set; }
    public int Y { get; set; }

    public void Move(int dx, int dy)
    {
        X += dx;
        Y += dy;
    }
}

// REFACTOR: Immutable struct
public readonly struct ImmutablePoint
{
    public int X { get; }
    public int Y { get; }

    public ImmutablePoint(int x, int y)
    {
        X = x;
        Y = y;
    }

    public ImmutablePoint MovedBy(int dx, int dy)
    {
        return new ImmutablePoint(X + dx, Y + dy);
    }
}

This refactor makes intent explicit and eliminates accidental state corruption. For more clean-coding practices, see our principles guide: https://cleancodeguy.com/blog/clean-coding-principles.

Quick Q&A — Common developer questions

Q: When should I prefer a struct over a class?

A: Prefer a struct when the type is small, immutable, and represents a value rather than an identity. Structs are ideal for points, colors, money values, and small DTOs used in performance-sensitive code.¹

Q: What performance pitfalls should I watch for?

A: Avoid mutable structs, large structs that are copied frequently, and implicit boxing into heap objects. These patterns remove value-type benefits and can worsen performance.⁴⁵

Q: How do language differences affect my choice?

A: Follow language idioms: C# enforces value vs reference types, C++ relies on convention, and Swift favors value types by default. Learn the platform rules before applying patterns across languages.¹²

At Clean Code Guy, we help teams apply these principles to real codebases. Our Codebase Cleanups and AI-Ready Refactors make software faster, safer, and easier to maintain. Visit https://cleancode.com to learn more.