Improved Double Selection Sort using Algorithm
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Abstract
In this paper, we present the work regarding the selection sorting technique for double ended selection sort. This sorting algorithm is both theoretical and programmatically analysis show that the introduce advance selection sort algorithm which enhances the performance of selection sort. It is much faster than the selection sort because of its selection of minimum and maximum elements simultaneously. Advance selection sort algorithm possibility of enhancing execution speed up to 30%. Code for this algorithm is written in C programming Language. So easy to understand the concept of this sorting algorithm by everyone because C is the popular language. Results and discusion show a higher level of performance for the sorting algorithm. It can theoretically prove that the algorithm can reduce steps with the selection short and will improve N2 sorts toward NlogN sort.
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Pathak, N., & Tiwari, S. (2017). Improved Double Selection Sort using Algorithm. SAMRIDDHI : A Journal of Physical Sciences, Engineering and Technology, 9(02), 85-88. https://doi.org/10.18090/samriddhi.v9i02.10866
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Research Article
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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annual ACM symposium on Theory of computing.
ACM, 2002.
[2] R. B. Patel, and M. M. S. Rauthan. “Expert Data
Structures with C++.” (2000).
[3] Gray J Bronson, “Program development and design
using C++”. Brooks/Cole Publishing Co., 2000.
[4] D P Chavey, “Double sorting: testing their sorting
skills.” Proceedings of the 41st ACM technical
symposium on Computer science education. ACM,
2010.
[5] T Tiwari, S. Singh, R Srivastava, and N. Kumar,
(2009, August). A bi-partitioned insertion algorithm
for sorting. 2nd IEEE International Conference on
In Computer Science and Information Technology
ICCSIT, pp. 139-143, 2009.
[6] Ming Zhou, and Hongfa Wang. “An efficient
selection sorting algorithm for two-dimensional
arrays.”, Fourth International Conference on Genetic
and Evolutionary Computing (ICGEC), 2010.
[7] Oyelami Olufemi Moses, “Improving the
performance of bubble sort using a modified
diminishing increment sorting.” Scientific Research
and Essays 4.8, pp. 740-744, 2009.
[8] Mikkel Thorup,. “Randomized sorting in O
(nloglogn) time and linear space using addition, shift,
and bit-wise boolean operations.” Journal of
Algorithms, 42.2, pp. 205-230, 2002.
[9] Arne Andersson et al. “Sorting in linear time.”
Proceedings of the twenty-seventh annual ACM
symposium on Theory of computing. ACM, 1995.
[10] Paul Beame, and Faith E. Fich. “Optimal bounds for
the predecessor problem and related problems.”
Journal of Computer and System Sciences 65.1, pp.
38-72, 2002.
[11] Genshiro Kitagawa, “Monte Carlo filter and
smoother for non-Gaussian nonlinear state space
models.” Journal of computational and graphical
statistics 5.1, pp. 1-25, 1996.
[12] Mikkel Thorup, “Undirected single-source shortest
paths with positive integer weights in linear time.”
Journal of the ACM (JACM), 46.3, pp. 362-394,
1999.
[13] Nalluri, S. K., & Parasaram, V. K. B. (2015).
Automating Software Builds with Jenkins: Design
Patterns and Failure Handling. International
Journal of Technology, Management and
Humanities, 1(01), 16-33.