Optimization Techniques¶

Prerequisites: Algorithm analysis, Basic profiling

Learning Objectives¶

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

Optimization Order¶

Measure current behavior.
Improve algorithmic complexity first.
Reduce repeated work with caching/memoization.
Optimize data structure choice.
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.