Introduction to Computational Complexity
A problem solving technique is a process to solve a problem by performing some activities in a sequence. After defining the process, an algorithm is written. Algorithm is a procedure to accomplish a specific task. To complete a task, the stepwise process is followed. In computer terminology, an algorithm is a way to solve a problem, which is sufficiently precise and can be programmed on a computer. Once an algorithm is designed, a flow chart is used to show the step by step representation of it. An algorithm is a way or procedure to solve a problem. It can be programmed on a computer. Thus, a program is an implementation of an algorithm. Effectiveness and efficiency are the two quality parameters of an algorithm. Effectiveness represents that an algorithm carries out its function correctly. Efficiency refers to the performance of an algorithm. Efficiency is the measure of computational complexity of an algorithm. Computational complexity refers to the study of factors that affect the performance of an algorithm for solving a problem. Computation involves solving a problem using an algorithm and complexity refers to the study of how an algorithm solves a problem. In single term, it can be called computational complexity. It refers to the study of factors that affect the performance of an algorithm for solving a problem.