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A Comparative Performance of Sorting Algorithms: Statistical Investigation

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Soft Computing: Theories and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1154))

Abstract

This paper is aimed at a comparative study of several sorting algorithms with the purpose of evaluating their relative performance when the input array is randomly generated from zero-truncated binomial and poisson distributions. The sorting algorithms to be investigated are quick sort, k-sort, heap sort and merge sort, all having the same average case complexity of O(NlogN). In practical statistical cases, sometimes it is not possible to record or know about the occurrences as they are limited to values which exist above or below a given limit or within a particular range. Such situations result in truncated distributions. The relative performance of the above-mentioned sorting methods was compared on the basis of ‘execution time’ and the ‘number of swapping’ for both the average and worst cases of different algorithms.

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References

  1. Priyadarshini, Kumari, A.: Parameterized complexity analysis of heap sort, K-sort and quick sort for binomial input with varying probability of success. Int. J. Emerg. Technol. Innov. Res. 5(7), 491–495. www.jetir.org. UGC and ISSN Approved, ISSN:2349-5162, July 2018, Available at http://www.jetir.org/papers/JETIR1807424.pdf

  2. Priyadarshini, Chakarborty, S., Kumari, A.: Parameterised complexity of quick sort, heap sort and k-sort algorithms with quasi binomial input. Int. J. Future Revolution Comput. Sci. Commun. Eng. IJFRSCE 4(1), 117–123

    Google Scholar 

  3. Sabharwal, M.: The use of soft computing technique of decision tree in selection of appropriate statistical test for hypothesis testing. In: Pant, M., Ray, K., Sharma, T., Rawat, S., Bandyopadhyay, A. (eds.) Soft computing: theories and applications. Advances in intelligent systems and computing, vol. 583. Springer, Singapore (2018)

    Google Scholar 

  4. Geyer, C.J.: Lower-truncated poisson and negative binomial distributions, 5 July 2018

    Google Scholar 

  5. Kamnthania, D., Kumar, J., Taterh, S.: Study and comparative analysis of various image spamming techniques. Soft Comput. Theor. Appl. 583(1), 351–365 (2017)

    Google Scholar 

  6. Grover, P.S., Kakkar, M., Jain, S., Bansal, A.: Is open-source software valuable for software defect prediction of proprietary software and vice versa? Soft Comput. Theor. Appl. 583(1), 227–236 (2017)

    Google Scholar 

  7. Kumari, A., Singh, N.K., Chakraborty, S.: A statistical comparative study of some sorting algorithms. Int. J. Found. Comput. Sci. Technol. 5, 21–29 (2015). https://doi.org/10.5121/ijfcst.2015.5403

    Article  Google Scholar 

  8. Singh, N.K., Chakarborty, S., Malick, D.K.: A statistical peek into average case complexity. IJEDPO 4(2); Int. J. Recent Trends Eng. Technol. 8(1), 64–67

    Google Scholar 

  9. Kumari, A., Chakraborty, S.: Parameterized complexity, a statistical approach combining factorial experiments with principal component analysis. Int. J. Comput. Sci. Eng. (2013)

    Google Scholar 

  10. Kumari, A., Chakraborty, S.: The middle pivot element algorithm. Int. Sch. Res. Netw. ISRN Comput. Math. 5 (2012)

    Google Scholar 

  11. Prashant, Anchala and Soubhik (2009) parameterised complexity on a new sorting algorithm, a study in simulation. Annals. Comput. Sci. Ser. VII

    Google Scholar 

  12. Kumari, A., Chakraborty, S.: A simulation study on quick sort parameterized complexity using response surface design. Int. J. Math. Model. Simul. Appl. 1(4) (2009)

    Google Scholar 

  13. Kumari, A., Chakraborty, S.: Software complexity: a statistical case study through insertion sort. Appl. Math. Comput. 190(1) (2007)

    Google Scholar 

  14. Geyer, C.J.: The K-truncated poisson distribution, 18 June 2006

    Google Scholar 

  15. Mahmoud, H.: Sorting: a distribution theory. Wiley (2000)

    Google Scholar 

  16. Clifford, C.A.: Truncated and censored samples: theory and applications. CRC Press

    Google Scholar 

  17. Sacks, J., Welch, W.J., Mitchell, T.J., Wynn, H.P.: Design and analysis of computer experiments. Stat. Sci. 4 (1989)

    Google Scholar 

  18. Rider, P.R.: Truncated binomial and negative binomial distributions. J. Am. Stat. Assoc. 50(271), 877–883 (1955)

    Article  MathSciNet  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Statistics, Patna University, Patna, India

    Priyadarshini & Anchala Kumari

Authors
  1. Priyadarshini
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  2. Anchala Kumari
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Corresponding author

Correspondence to Priyadarshini .

Editor information

Editors and Affiliations

  1. Department of Paper Technology, IIT Roorkee, Roorkee, India

    Millie Pant

  2. Graphic Era Hill University, Dehradun, Uttarakhand, India

    Tarun Kumar Sharma

  3. NIT Patna, Patna, India

    Rajeev Arya

  4. NIT Patna, Patna, India

    B.C. Sahana

  5. Ryerson University, Toronto, ON, Canada

    Hossein Zolfagharinia

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Priyadarshini, Kumari, A. (2020). A Comparative Performance of Sorting Algorithms: Statistical Investigation. In: Pant, M., Kumar Sharma, T., Arya, R., Sahana, B., Zolfagharinia, H. (eds) Soft Computing: Theories and Applications. Advances in Intelligent Systems and Computing, vol 1154. Springer, Singapore. https://doi.org/10.1007/978-981-15-4032-5_34

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