Complexity Analysis
Master the art of predicting algorithm performance. Learn time and space complexity analysis to make informed decisions about code efficiency before you write it.
Overview
In this lesson, you'll learn how to analyze algorithm performance using complexity analysis. We'll cover time complexity (how execution time grows with input size) and space complexity (how memory usage scales), giving you the tools to predict performance before writing code.
Complexity analysis is the mathematical framework for understanding how algorithms behave as data grows. Instead of timing code execution, we analyze the fundamental operations and predict scalability patterns that hold true across different computers and programming languages.
Key concepts you'll master:
- Understanding time complexity and space complexity
- Analyzing loops, nested operations, and recursive functions
- Comparing different algorithmic approaches
- Predicting performance bottlenecks before coding
- Building intuition for scalable algorithm design
Next: Memory →