What is Space Complexity?
The space Complexity of an algorithm is the space taken by an algorithm to run the program for a given input size. The program has some space requirements necessary for its execution these include auxiliary space and input space. The important standard for comparison of algorithms is the space taken by the algorithm to run for a given input size Hence it needs to be optimized.
What is Logarithmic Time Complexity? A Complete Tutorial
Logarithmic time complexity is denoted as O(log n). It is a measure of how the runtime of an algorithm scales as the input size increases. In this comprehensive tutorial. In this article, we will look in-depth into the Logarithmic Complexity. We will also do various comparisons between different logarithmic complexities, when and where such logarithmic complexities are used, several examples of logarithmic complexities, and much more. So let’s get started.
Table of Content
- What is a Logarithm?
- What is Complexity Analysis?
- What is Space Complexity?
- What is Time Complexity?
- How to measure complexities?
- What is a Logarithm?
- Different Types of Logarithmic Complexities
- Simple Log Complexity (Log a)
- Double Logarithm (log log N)
- N logarithm N (N * log N)
- logarithm^2 N (log^2 N)
- N^2 logarithm N (N^2 * log N)
- N^3 logarithm N (N^3 log N)
- logarithm √N (log √N)
- Examples To Demonstrate Logarithmic Time Complexity
- Practice Problems for Logarithmic Time Complexity
- Comparison of various Logarithmic Time Complexities
- Frequently Asked Questions(FAQ’s) on Logarithmic Time Complexity
- Conclusion
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