Engineering quicksort

Authors:
S.Mansoor Sarwar;Syed Aqeel Sarwar;Mansour H. A. Jaragh;Jesse Brandeburg
Affiliations:
Department of Electrical Engineering, Multnomah School of Engineering, University of Portland, 5000 N. Willamette Blvd, Portland, OR 97203-5798, U.S.A.;Academic Computing Laboratories, New York Institute of Technology, Harry Schure Hall. Old Westbury, N.Y. 11568, U.S.A.;Department of Electrical and Computer Engineering, Faculty of Engineering and Petroleum, Kuwait University, P.O. Box 5969, 13060 Safat, Kuwait;Department of Electrical Engineering, Multnomah School of Engineering, University of Portland, 5000 N. Willamette Blvd, Portland, OR 97203-5798, U.S.A.
Venue:
Computer Languages
Year:
1996

Citing 5
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Abstract

This paper describes the results of a large empirical study to measure the run-time behavior of Quicksort by using various methods of computing the pivot element for medium to large size randomly generated integer data. The results of our study contradict the common notion that Quicksort gives best performance if median of three scheme is used to compute the pivot element and array partitions having 9% when compared to the method with a cutoff of 10 and sub-arrays with