Summary
In this chapter, we delved into the fundamental concept of Big O notation, a powerful tool for analyzing and expressing the efficiency of algorithms. We explored how to calculate both time complexity (the relationship between input size and runtime) and space complexity (the relationship between input size and memory usage). We also discussed how Big O analysis is a crucial skill for software developers, aiding in algorithm selection, performance optimization, and technical interviews.
In the next chapter, we will dive into our first data structure: the versatile Array. We will explore its common operations, analyze their time complexities, and tackle some practical coding challenges.
