EASY UNDERSTANDING OF COMPUTATIONAL COMPLEXITY THEORY – A STUDENT’S PERSPECTIVE

Bhalchandra P.U.1*, More U.L.2, Rawangaonkar R.R.3, Tammewar P.R.4, Kulkarni P.P.5
1School of Computational Sciences, Swami Ramanand Teerth Marathwada University, Nanded, 431606, MS, India
2School of Computational Sciences, Swami Ramanand Teerth Marathwada University, Nanded, 431606, MS, India
3School of Computational Sciences, Swami Ramanand Teerth Marathwada University, Nanded, 431606, MS, India
4School of Computational Sciences, Swami Ramanand Teerth Marathwada University, Nanded, 431606, MS, India
5School of Computational Sciences, Swami Ramanand Teerth Marathwada University, Nanded, 431606, MS, India
* Corresponding Author : pub1976@rediffmail.com

Received : -     Accepted : -     Published : 15-06-2010
Volume : 2     Issue : 1       Pages : 40 - 45
Int J Mach Intell 2.1 (2010):40-45
DOI : http://dx.doi.org/10.9735/0975-2927.2.1.40-45

Keywords : Complexity Theory, P, NP completeness
Conflict of Interest : None declared

Cite - MLA : Bhalchandra P.U., et al "EASY UNDERSTANDING OF COMPUTATIONAL COMPLEXITY THEORY – A STUDENT’S PERSPECTIVE." International Journal of Machine Intelligence 2.1 (2010):40-45. http://dx.doi.org/10.9735/0975-2927.2.1.40-45

Cite - APA : Bhalchandra P.U., More U.L., Rawangaonkar R.R., Tammewar P.R., Kulkarni P.P. (2010). EASY UNDERSTANDING OF COMPUTATIONAL COMPLEXITY THEORY – A STUDENT’S PERSPECTIVE. International Journal of Machine Intelligence, 2 (1), 40-45. http://dx.doi.org/10.9735/0975-2927.2.1.40-45

Cite - Chicago : Bhalchandra P.U., More U.L., Rawangaonkar R.R., Tammewar P.R., and Kulkarni P.P. "EASY UNDERSTANDING OF COMPUTATIONAL COMPLEXITY THEORY – A STUDENT’S PERSPECTIVE." International Journal of Machine Intelligence 2, no. 1 (2010):40-45. http://dx.doi.org/10.9735/0975-2927.2.1.40-45

Copyright : © 2010, Bhalchandra P.U., et al, Published by Bioinfo Publications. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

Abstract

Computer Science is largely concerned about a single question - how long does it take to execute a given algorithm? But computer scientists don’t give the answer in minutes or milliseconds; they give it relative to the number of elements the algorithm has to manipulate resulting into formation of computational complexity theory. For entry level students in Data Structures and Analysis of Algorithms, understanding this theory is quite hard as literature review seen so far is dedicated to classifying problems by how hard they are. We have attempted for rigorous analysis of literature review and discovered different types of problems. A division of problem space is suggested in order to put these concepts in simple and conceptually understandable format.

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