What is Time and Space Complexity
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Time Complexity: It is defined as the number of times a particular instruction set is executed rather than the total time is taken. It is because the total time took also depends on some external factors like the compiler used, processor’s speed, etc.
Space Complexity: It is the total memory space required by the program for its execution.
Time Complexity:
Time complexity is a type of computational complexity that describes the time required to execute an algorithm. The time complexity of an algorithm is the amount of time it takes for each statement to complete. As a result, it is highly dependent on the size of the processed data. It also aids in defining an algorithm’s effectiveness and evaluating its performance.
Space Complexity:
When an algorithm is run on a computer, it necessitates a certain amount of memory space. The amount of memory used by a program to execute it is represented by its space complexity. Because a program requires memory to store input data and temporal values while running, the space complexity is auxiliary and input space.
Time complexity example:
This is what we call O(n2).