Analysis of algorithm is a field of computer science that is dedicated to understanding the complexity of algorithms. Algorithms are generally defined as processes that perform a series of operations to an end. Algorithms can be expressed in many ways, in flow charts, a natural languages, and computer programming languages.
To analyze an algorithm is to determine the amount of resources (such as time and storage)necessary to execute it.
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.
In order to learn more about an algorithm, we can analyze it. By this we mean to study the specification of the algorithm and to draw conclusions about how the implementations of that algorithm will performin general. We can:
- determine the running time of a program asa a function of its inputs;
- determine the total or maximum memory space needed for program data;
- determine the total size of the program code;
- determine whether the program correctly computes the desired result;
- determine the complexity of the program;
- determine the robustness of the program.
In general, algorithm analysis is most concerned with finding out how much time a program takes to run, and how much memory storage space it needs to execute the program. In particular, computer scientists use algorithm analysis to determine how the data imputed into a program affects its total running time, how much memory space the computer needs for program data, how much space the program's code takes in the computer, whether an algorithm produces correct calculations, how complex a program is, and how well it deals with unexpected results.
Reference:
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