UDC 681.3.(07)
DOI: 10.36871/2618-9976.2021.10.003
Authors
Kozhemyakina E.V.
Master's Student of the Department of Higher Mathematics, Perm National Research Polytechnic University
Abstract
Sorting is a fundamental building block for many tasks and is ubiquitous both in theory and in practice of computing, being one of the most important operations in database systems, where its effectiveness can significantly affect the overall performance of the system. A sorting network is a combinational sorting scheme constructed from comparisonswap units. The depth of such a contour is a measure of its working time. The Shell sorting method and the bubble method act as basic methods in the use of sorting methods. They are based on the "comparison" sorting algorithm, which uses insertion sorting at each iteration to make the list of alternating elements almost sorted so that at the last iteration the list is almost sorted. The time complexity of sorting depends on the alternation method (called the increment sequence. In this paper, by implementing sorting algorithms in the Python programming language, two methods are compared, and on a large array of data, the optimal sorting method for computational complexity is determined by a key time criterion.
Keywords
Sorting
Shell method
Bubble method
Computing power
Big data
PYTHON programming language
Optimization process
