The term "analysis of algorithms" was coined by Donald Knuth. Algorithm analysis is an important part of a broader computational complexity theory, which provides theoretical estimates for the resources needed by any algorithm which solves a given computational problem.
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An algorithm is a set of instructions that performs a particular task making sure that those instructions are followed. Analysis of algorithm question bank is needed when any of the following occurs: when a working program is not good enough, when program may be inefficient or when a running time of a program becomes an issue.
There are so many reasons for a programmer to study algorithm. This will help in proper analysis of problems and coming up with fast solutions that relate to programming.
A priori analysis of an algorithm refers to its time and space complexity analysis using mathematical (algebraic) methods or using a theoritical model such as a finite state machine. (In short, analysis prior to running on real machine.) A posteriori analysis of an algorithm refers to the statistical analysis of its space and time complexity after it is actualy run on a practical machine. (in short, anaysis of its statistics after running it on a real machine)
Analysis of an algorithm means prediction of how fast the algorithm works based on the problem size. It is necesary to analyze an algorithm so that, if we have n no Of algorithms then the fastest and 1 with less time & space complexity can selected. Which will allow and ensure maximum utilization of available resourses.
A sequential algorithm has the following characteristics:a dependence on the standard environment,a relevant name,a main method (function/subroutine) with no parameters,supplementary methods using a top-down modular design,input of boolean values,output exemplifying the relevant criteria.