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Empirical Analysis on the Running Time of a Searching Algorithm, Chunk Algorithm

Year 2019, Volume: 3 Issue: 1, 24 - 29, 15.05.2019

Abstract

Searching and sorting, by no doubt, represent two
of the most fundamental and widely encountered problems in computer science.
Given a collection of objects, the goal of search is to find a particular
object in this collection or to recognize that the object does not exist in the
collection. A major goal of computer sciences is to understand and develop a
solution for the particular problem. 
Typically solving the problem involves at least four steps: (1) design
an algorithm, (2) analyze the correctness and efficiency of the procedure, (3)
implement that procedure in some programming language, and (4) test that
implementation.  An important issue is to
describe the efficiency of a given procedure for solving a problem. Informally,
usually we speak in terms of  “fast” or
“slow” programs, but the absolute execution time of an algorithm depends on
many factors such as: the size of the input, 
the programming language used to implement the algorithm, the quality of
the implementation and  the machine on
which the code is run (a supercomputer is faster than a laptop). In this paper
we will analyze the performances of a searching algorithm, precisely the chunk
algorithm. In analyzing the efficiency of chunk algorithm, we will only concentrate
on searching items, using the Chunk-Search Algorithm, on one-dimensional arrays
with integers. We wanted to see how does different chunk size, input size
(i.e., the “speed” of the algorithm as a function of the size of the input on
which it is run), and the machine on which the code is run. 

References

  • [1]. Profs. Aslam & Fell, Analysis of Algorithms: Running Time September 7, 2005. Available from http://www.psnacet.edu.in/courses/MCA/Design%20and%20analysis%20of%20Algorithms/Lecture1.pdf
  • [2]. A. Levitin. Introduction to the Design and Analysis of Algorithms. 3e, Addison-Wesley, 2011. ISBN 978-0132316811.
  • [3]. Searching Arrays: Algorithms and Efficiency. Available from http://research.cs.queensu.ca/home/cisc121/2006s/webnotes/search.html (Accessed June, 2016).
  • [4]. Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. Introduction to Algorithms, Second Edition. MIT Press and McGraw-Hill, 2001. ISBN 0-262-03293-7. Bentley, Programming Pearls, Addison-Wesley
  • [5]. R. Sedgewick, Bundle of Algorithms in C++, Addison-Wesley, 2001, 3rd Edition.
  • [6]. Design and Analysis of Algorithms, Available from https://www.cs.cornell.edu/~kozen/papers/daa.pdf
Year 2019, Volume: 3 Issue: 1, 24 - 29, 15.05.2019

Abstract

References

  • [1]. Profs. Aslam & Fell, Analysis of Algorithms: Running Time September 7, 2005. Available from http://www.psnacet.edu.in/courses/MCA/Design%20and%20analysis%20of%20Algorithms/Lecture1.pdf
  • [2]. A. Levitin. Introduction to the Design and Analysis of Algorithms. 3e, Addison-Wesley, 2011. ISBN 978-0132316811.
  • [3]. Searching Arrays: Algorithms and Efficiency. Available from http://research.cs.queensu.ca/home/cisc121/2006s/webnotes/search.html (Accessed June, 2016).
  • [4]. Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. Introduction to Algorithms, Second Edition. MIT Press and McGraw-Hill, 2001. ISBN 0-262-03293-7. Bentley, Programming Pearls, Addison-Wesley
  • [5]. R. Sedgewick, Bundle of Algorithms in C++, Addison-Wesley, 2001, 3rd Edition.
  • [6]. Design and Analysis of Algorithms, Available from https://www.cs.cornell.edu/~kozen/papers/daa.pdf
There are 6 citations in total.

Details

Subjects Engineering
Journal Section Makaleler
Authors

Gazmend Xhaferi

Florinda Imeri This is me

Flamure Sadiki This is me

Agon Memeti

Publication Date May 15, 2019
Published in Issue Year 2019 Volume: 3 Issue: 1

Cite

APA Xhaferi, G., Imeri, F., Sadiki, F., Memeti, A. (2019). Empirical Analysis on the Running Time of a Searching Algorithm, Chunk Algorithm. European Journal of Sustainable Development Research, 3(1), 24-29.
AMA Xhaferi G, Imeri F, Sadiki F, Memeti A. Empirical Analysis on the Running Time of a Searching Algorithm, Chunk Algorithm. EJSDR. May 2019;3(1):24-29.
Chicago Xhaferi, Gazmend, Florinda Imeri, Flamure Sadiki, and Agon Memeti. “Empirical Analysis on the Running Time of a Searching Algorithm, Chunk Algorithm”. European Journal of Sustainable Development Research 3, no. 1 (May 2019): 24-29.
EndNote Xhaferi G, Imeri F, Sadiki F, Memeti A (May 1, 2019) Empirical Analysis on the Running Time of a Searching Algorithm, Chunk Algorithm. European Journal of Sustainable Development Research 3 1 24–29.
IEEE G. Xhaferi, F. Imeri, F. Sadiki, and A. Memeti, “Empirical Analysis on the Running Time of a Searching Algorithm, Chunk Algorithm”, EJSDR, vol. 3, no. 1, pp. 24–29, 2019.
ISNAD Xhaferi, Gazmend et al. “Empirical Analysis on the Running Time of a Searching Algorithm, Chunk Algorithm”. European Journal of Sustainable Development Research 3/1 (May 2019), 24-29.
JAMA Xhaferi G, Imeri F, Sadiki F, Memeti A. Empirical Analysis on the Running Time of a Searching Algorithm, Chunk Algorithm. EJSDR. 2019;3:24–29.
MLA Xhaferi, Gazmend et al. “Empirical Analysis on the Running Time of a Searching Algorithm, Chunk Algorithm”. European Journal of Sustainable Development Research, vol. 3, no. 1, 2019, pp. 24-29.
Vancouver Xhaferi G, Imeri F, Sadiki F, Memeti A. Empirical Analysis on the Running Time of a Searching Algorithm, Chunk Algorithm. EJSDR. 2019;3(1):24-9.