Chapter 3 Summary
Algorithm efficiency is the bedrock upon which all computer science is built. Understanding how to measure an algorithm's efficiency, in terms of time and space complexity, is vital for any budding programmer or computer scientist. This chapter delved deep into this concept, exploring both theoretical and practical aspects.
We began this chapter with a discussion of time complexity. We saw that time complexity is a measure of the amount of computational time taken by an algorithm to run, as a function of the size of the input to the program. A fundamental understanding of time complexity allows us to evaluate and compare algorithms based on their performance and choose the most efficient algorithm for our needs. We reinforced the concepts with an in-depth exploration of linear and binary search, emphasizing the importance of understanding how time complexity changes with different inputs.
Next, we turned our attention to space complexity, which measures the amount...