📄️ Time Complexity
Time Complexity is a measure of the amount of time an algorithm takes to solve a problem as a function of the size of the input to the problem. It is commonly estimated by counting the number of elementary operations performed by the algorithm, where an elementary operation takes a fixed amount of time to perform.
📄️ Space Complexity
Space complexity is a measure of the amount of working storage an algorithm needs. It is a measure of the amount of memory space an algorithm needs to solve a problem as a function of the size of the input to the problem. It is the amount of memory space required by the algorithm to execute in its life cycle.
📄️ Time vs Space Complexity
Time and space complexity are two important concepts in computer science. Time complexity is the amount of time an algorithm takes to run, while space complexity is the amount of memory an algorithm uses. Both are important to consider when analyzing the efficiency of an algorithm.
📄️ How to Calculate Time and Space Complexity
Calculating time and space complexity is an essential skill for analyzing the efficiency of algorithms. By understanding how to determine the time and space complexity of an algorithm, you can evaluate its performance and make informed decisions when designing and optimizing algorithms.