Description

Time complexity is normally expressed as an order of magnitude, e.g. O(N^2) means that if the size of the problem (N) doubles then the algorithm will take four times as many steps to complete. The time complexity of an algorithm quantifies the amount of time taken by an algorithm to run as a function of the length of the string representing the input. The time complexity of an algorithm is commonly expressed using big O notation, which excludes coefficients and lower order terms. Space complexity is normally expressed as an order of magnitude, e.g. O(N^2) means that if the size of the problem (N) doubles then four times as much working storage will be needed. This project is used to find space and time complexity of given datasets accurately. If we give a dataset t will calculate it very fast and provide an answer very accurately. And also the proposed system is very eazy to imlplement.