WWDC 2025 - Improve memory usage and performance with Swift

Performance optimization in Swift requires a systematic approach that goes beyond micro-optimizations. The introduction of Swift 6 brings powerful new tools that can dramatically improve application performance when applied correctly. This guide explores proven strategies for eliminating performance bottlenecks while maintaining code safety.

The Performance Investigation Process

Start with Instruments

• Always begin performance analysis with concrete data, not assumptions
• Use the Time Profiler to identify where code spends most execution time
• The Allocations instrument reveals memory usage patterns and potential leaks
• Flame graphs provide visual representation of performance hotspots
• Focus on the heaviest stack traces to find the most impactful optimization opportunities

Common Performance Anti-Patterns

• Quadratic algorithms masquerading as linear operations - Operations that appear simple but scale poorly with data size
• Excessive memory allocations - Creating temporary objects in tight loops
• Unnecessary data copying - Moving large data structures when references would suffice
• Runtime exclusivity checks - Class-based architectures that force runtime safety verification

Algorithmic Optimizations: The Foundation

Data Structure Selection Matters

• Collections like Data and Array provide convenience methods that may hide performance costs
• The popFirst() method on collections often performs better than manual index manipulation
• Understand the complexity characteristics of collection operations before using them in performance-critical paths

Allocation Strategy Optimization

• Pre-allocate collections with known final sizes rather than growing them incrementally
• Replace chains of functional operations (flatMap, prefix) with direct iteration when performance is critical
• Eliminate intermediate array creation by processing data in-place
• Consider the allocation patterns of functional programming constructs in hot code paths

Memory Management Optimization

Moving from Heap to Stack

• Swift's automatic memory management provides safety but introduces overhead
• Reference counting (swift_retain/swift_release) becomes significant in tight loops
• Uniqueness checks for copy-on-write semantics add runtime cost
• Runtime exclusivity checking (swift_beginAccess/swift_endAccess) can be eliminated with proper architecture

Class vs Struct Architecture

• Classes require runtime exclusivity checking for property access
• Moving properties from class instances to value types eliminates this overhead
• Mutating methods on structs are often more performant than class method calls
• Consider the trade-offs between reference semantics and performance

Swift 6 Performance Features

InlineArray: Fixed-Size, Zero-Overhead Collections

• Compile-time size specification using value generics
• Stack allocation eliminates heap overhead and reference counting
• Ideal for fixed-size buffers like caches or lookup tables
• Cannot be resized - no append/remove operations available

Span Types: Safe Memory Access

• Non-escapable types prevent lifetime issues that plague unsafe pointers
• Zero-copy access to existing collection memory
• Compiler-enforced safety prevents dangling pointer scenarios
• Performance equivalent to unsafe pointers without the safety risks
• Multiple variants: Span, RawSpan, OutputSpan, UTF8Span

OutputSpan: Efficient Buffer Writing

• Uninitialized memory access for building data structures
• Automatic bounds checking prevents buffer overflows
• Append-based API simplifies sequential data writing
• Integration with Data initialization for seamless adoption

Practical Implementation Strategies

Profiling-Driven Development

• Profile early and often during performance-critical development
• Use test-driven profiling to isolate specific code paths
• Filter Instruments results to focus on application code
• Measure before and after each optimization to verify impact

Progressive Optimization Approach

1. Fix algorithmic issues first - Often provides 10x+ improvements
2. Eliminate unnecessary allocations - Typically 2-5x improvements
3. Reduce memory management overhead - Usually 2-6x additional gains
4. Apply low-level optimizations - Final polish for critical paths

Safety Considerations

• Swift 6's new features maintain memory safety while improving performance
• Non-escapable types prevent common pointer misuse patterns
• Compiler enforcement eliminates entire classes of runtime errors
• Performance gains don't require sacrificing Swift's safety guarantees

Key Takeaways

Performance optimization is systematic, not accidental. Start with profiling, fix the biggest issues first, and use Swift 6's new features to eliminate overhead while maintaining safety. The language continues to evolve toward zero-cost abstractions that don't compromise on developer experience or code safety.

Modern Swift development balances performance, safety, and maintainability through compiler-enforced constraints rather than developer discipline.