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devel / comp.lang.python / new sorting algorithm

SubjectAuthor
o new sorting algorithmNas Bayedil

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new sorting algorithm

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From: nbaye...@gmail.com (Nas Bayedil)
Newsgroups: comp.lang.python
Subject: new sorting algorithm
Date: Sun, 1 May 2022 19:31:45 +0600
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 by: Nas Bayedil - Sun, 1 May 2022 13:31 UTC

*Dear, Sir/Madam*

Let me first tell you briefly who we are and where we are from, what we do.

My name is Nas (full name Nasipa Bayedil) from Kazakhstan.

In December 2020, we registered a company online in Dover, Delaware, the
United States, because all major corporations are based in the United
States. Direction of the company: research and development technologies of
sorting and searching in databases and in Big Data. Our research and
developments should be of interest to a rapidly growing tech market.

My father Nurgali has a mathematics education, he has been interested in
mathematics' and physics all his life, now he is retired and continues to
study his favorite mathematics, when he became a pensioner to this love an
interest in programming was added. And this new interest in programming led
him to invent his own method of developing sorting algorithms.

*In a nutshell about what we are doing.*

We have developed several variants of sorting algorithms based on new ideas
and improvements to well-known ideas.

Our development is carried out in the application of the idea of the
article Peter McIlroy's 1993 paper "Optimistic Sorting and Information
Theoretic Complexity", which was implemented by *Tim Peters TimSort in a
sorting algorithm in 2002 for use in Python.*

The variant implemented by Tim Peters is improved by us as it does not take
full advantage of Peter McIlroy's idea.

This has been achieved through the development of new methods:

1. data recognition

2. data fusion

We also used the research work Sorting N-Elements Using Natural Order: A
New Adaptive Sorting Approach** but added some new ideas of our own. As a
result, we got a hybrid NDsort algorithm, which uses the above particular
algorithms.

Existing sorting algorithms that are used in practice, very fast, I will
not list their advantages; for improvement let's just indicate that some of
them start to work slowly on certain types of data. The author tried to
deal with this from a general, *mathematical position*, and not from the
point of view of programming techniques, *and achieved the goal*.

Fragments of the general theory of sorting by comparison have been
developed, *several facts have been discovered that are subject to
patenting *and which allow developing various variants of sorting
algorithms.

We believe that using this method to develop completely new, fast
algorithms, approaching the speed of the famous *QuickSort*, the speed of
which cannot be surpassed, but its drawback can be circumvented, in the
sense of stack overflow, on some data.

Additionally our general sorting algorithm can be applied to design data
sorting chips. This is, of course, the business of specialists in this
field, but we believe that our algorithm opens up a new approach to this
problem. The fact is that there are currently two ways to develop data
sorting chips. The first is that data is entered in parallel; the second is
that data is entered sequentially. Our sorting algorithm allows
parallel-sequential data input, which would speed up the entire sorting
process.

I hope our research will pique your interest. The distinctive features of
our sorting algorithms are the minimization of the number of comparisons, a
new approach to the sorting problem, the maximum use of common sense, and
the use of a principle from philosophy "Occam's razor".

We use C# (Visual Studio 2019 demo version) for research and write
fragments of algorithms. We would like to ask for help from Python.org
engineers in implementation of our idea for the Python language together.

We will be glad to hear from you any comments and questions about our idea.

Kind regards,

Nas Bayedil

Twitter: @NasBayedil

Website: www.bazony.com.kz

**June 2010 Journal of Computer Science 6(2) Project: Algorithm Analysis,

Authors: Shamim Akhter, International University of Business Agriculture
and Technology M. Tanveer Hasan.

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