Learn Algorithms & Data structure.

Learn algorithms and data structure using javascript.

Course Topics:

• Algorithms
• Measuring performance
• Time & Space complexity
• Big O notation
• Math algorithms
• Sort
• Search
• Misc. algorithms and problems solving

Algorithms analysis contd.

The absolute running time of an algorithms cannot be predicted, since it depends on a number of factors.

• Programming language used to implement the algorithm.
• The computer the program runs on.
• Other programs running at the same time.
• Quality of the operating system.

We evaluate the performance of an algorithm in terms of its input size.

Time complexity -> Amount of time taken by an algorithm to run, as a function of input size.
Space complexity -> Amount of memory taken by an algorithm to run, as a function of input size.
=> By evaluating against the input size, the analysis is not only machine independent but the comparison is also more appropriate.

How to represent complexity?

Asymptotic notations:

• Big O Notation (O - Notation) -> Worst case complexity
• Omega Notation (0 Notation) -> Best case complexity
• Theta Notation (0 Notation) -> Average case complexity

Learn on: Codevolution