Lecture 11 - Space Complexity | DSA Basics For Beginners | Placement Course
Welcome to Lecture 11 - Space Complexity of our DSA Placement Course. In this lecture, we will get an understanding of the Space Complexities of Algorithms and how to implement them in coding.
What does 'Space Complexity' mean?
Space complexity refers to the total amount of memory space used by an algorithm/program, including the space of input values for execution.
Why is space complexity O 1?
O(1) — Constant Space: The algorithm uses a fixed amount of memory that does not depend on the input size. O(n) — Linear Space: The algorithm's memory usage grows linearly with the input size.
What is worst space complexity?
In computer science (specifically computational complexity theory), the worst-case complexity measures the resources (e.g. running time, memory) that an algorithm requires given an input of arbitrary size (commonly denoted as n in asymptotic notation). It gives an upper bound on the resources required by the algorithm.
This Data Structures and Algorithms course is a part of our Data Structures and Algorithms playlist: • Video
🔗Follow Us:
Our Website: https://myprojectideas.com/
Github: https://github.com/myprojectideas/DSA...
Join this channel to get access to the perks like 1-to-1 error resolution:
/ @myprojectideas
#dsa #algorithm #spacecomplexity #placement #course #coding
