Overview
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Learn about space complexity in algorithms and how to calculate it in this comprehensive video tutorial. Explore the definition of space complexity, its importance in algorithm analysis, and how it's expressed using Big O notation. Discover the various components that contribute to an algorithm's memory usage, including program instructions, constant values, and variable storage. Understand the concept of auxiliary space and its relationship to overall space complexity. Delve into different classifications of algorithms based on their space requirements, from constant space complexity to recursive algorithms. Master the techniques for calculating space complexity, including analyzing the call stack for recursive functions. Gain valuable insights into optimizing algorithms for efficient memory usage and improving overall program performance.
Syllabus
Introduction
What is Algorithm Analysis
Why do we need Algorithm Analysis
What does a better algorithm mean
Space Complexity Theory
Auxiliary Space
Classification of Algorithms
Calculate Space Complexity
Constant Space Complexity
Recursive Algorithm
Call Stack
Taught by
Simple Snippets