In computer science , the analysis of algorithms is the process of finding the  of computational complexity algorithms – the amount of time, storage, or other resources needed to execute them . Usually, this involves determining a function that relates the length of an algorithm's input to the number of steps it takes (its time complexity) or the number of storage locations it uses (its space cpmplexity). An algorithm is said to be efficient when this function's values are small, or grow slowly compared to a growth in the size of the input. Different inputs of the same length may cause the algorithm to have different behavior, so best , worst and average case descriptions might all be of practical interest. 

• Implement the algorithm completely.
• Determine the time required for each basic operation.
• Identify unknown quantities that can be used to describe the frequency of execution of the basic operations.
• Develop a realistic model for the input to the program.
• Analyze the unknown quantities, assuming the modelled input.
• Calculate the total running time by multiplying the time by the frequency for each operation, then adding all the products.