ABSTRACT
Algorithm analysis is the field that studies how to theoretically estimate the resources that algorithms need in order to solve computational problems. This chapter focuses on analyzing the runtime, also denoted as "computational time complexity", of recursive algorithms that solve problems whose size depends on a single factor. Matrix is a collection of numbers that are arranged in rows and columns forming a rectangular structure. Computational complexity of an algorithm is a theoretical measure of how much time, or how many operations, it needs to solve a problem. Algorithms are often compared according to their efficiency in the worst case. Worst case, which corresponds to an instance of a problem, amongst all that share the same size, for which the algorithm will require more resources. The running time or number of operations carried out by a recursive algorithm is specified through a recurrence relation.
