Optimization Techniques

Learning Objectives

• Optimize code based on measured bottlenecks.
• Apply safe and maintainable optimizations.
• Validate gains with benchmarks.

Optimization Order

1. Measure current behavior.
2. Improve algorithmic complexity first.
3. Reduce repeated work with caching/memoization.
4. Optimize data structure choice.
5. Re-measure and verify no regression.

Useful Techniques

Swapping Operations

Swapping values is a fundamental operation. While using a temporary variable is common and clear, some languages offer atomic or optimized ways to swap. Minimizing unnecessary swaps in sorting algorithms is a key performance win.

Bitwise Operations

Bitwise operations (AND, OR, XOR, shifts) are extremely fast as they operate directly on the binary representation of numbers. They can be used for:

• Efficiently checking for odd/even numbers.
• Swapping numbers without a temporary variable (XOR swap).
• Fast multiplication or division by powers of two.

Memory Optimization

Reducing memory footprint can improve performance by increasing cache hits and reducing garbage collection frequency.

• Reuse objects instead of creating new ones.
• Choose data structures that use less overhead.
• Use primitive types instead of wrapper objects where possible.

Summary

Optimize where it matters most, and always verify with data.