Call for Paper - October 2021 Edition
IJCA solicits original research papers for the October 2021 Edition. Last date of manuscript submission is September 20, 2021. Read More

Program Complexity Finder: A Tool for Finding Program Complexity in Terms of Cognitive Weight based on Complexity Measurement Algorithm

Print
PDF
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2015
Authors:
Samrat Kumar Dey, Tamim Al Mahmud
10.5120/ijca2015907443

Samrat Kumar Dey and Tamim Al Mahmud. Article: Program Complexity Finder: A Tool for Finding Program Complexity in Terms of Cognitive Weight based on Complexity Measurement Algorithm. International Journal of Computer Applications 131(8):41-47, December 2015. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {Samrat Kumar Dey and Tamim Al Mahmud},
	title = {Article: Program Complexity Finder: A Tool for Finding Program Complexity in Terms of Cognitive Weight based on Complexity Measurement Algorithm},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {131},
	number = {8},
	pages = {41-47},
	month = {December},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

Complexity Measurement of any piece of programming problems is a key issue for Distributing Equivalent Problems among examinees. Basic Control Structure or BCS Plays an Important role to design a program and hence measuring complexity value of any piece of programming problems. Using of Cognitive weight concept of any BCS are purely based on the thinking Capacity of Human Brain. In this Research Basic control structure has been established in such a way to reduce the limitation of existing Measures. According to these cognitive data, a new software tool based on java SE language and MySQL Database has been established by using own developed algorithm. This software is structured and developed based on the outcome of research data which is capable of determining the complexity value of several programming languages. It will facilitate the instructors distributing the programming problems among the students by maintaining equivalent level of difficulty. Thus, the automatic complexity measurement application will ensure the students to obtain programming problems with equal difficulty level for evaluation.

References

  1. Baker, A. L. and Zweben, S. H. 1980. “A comparison of Measures of control flow Complexity,” IEEE Transaction on Software Engineering, No.6, pp506-511.
  2. Barbier F. 2002. “Component-based software measurement,” chap. 14 in Business Component-Based Software Engineering, ed. F. Barbier, Boston: Kluwer Academic Publishers, pp. 247–262.
  3. Bashir, G. M. M. Dey, S. K. Tariq, S. S. M. Islam, M. S. Dec. 2014. “Complexity measurement: A new approach to ensure equal distribution of programming problems for evaluation,” in Proc. IEEE Int. Conf. ICECE, pp. 780 – 783.
  4. Basili, V. R. 1980. “Qualitative Software Complexity Models: A Summary in Tutorial on Models and Methods for Software Management and Engineering,” Los Alamitos, Calif.: IEEE Computer Society Press.
  5. Chhabra, J. K. July 6 - 8, 2011. “Code Cognitive Complexity: A New Measure,” Proceedings of the World Congress on Engineering 2011, Vol II WCE 2011, London, U.K.
  6. Halstead, M. H. 1997. “Elements of Software Science,” New York: Elsevier North-Holland Inc.
  7. Henry, S. and Kafura, D. 1981. “Software structure metrics based on information flow,” IEEE Transactions on Software Engineering, 7(5): 510-518.
  8. Hoare, C. A. R. Hayes, I. He, J. J. Morgan, C.C. Roscoe, A. W. Sanders, J. W. Sorensen, I. H. Spivey, J. M. and Sufrin, B. A. Aug. 1987. “Laws of programming,” Comm. ACM, vol. 30, no. 8, pp. 672–686.
  9. Kan, S. H. 2002. “Metrics and Models in Software Quality Engineering” (2nd Edition). Boston: Addison-Wesley Professional.
  10. Kearney, J. K. Sedlmeyer, R. L. Thompson, W. B. Gary, M. A. and Adler, M. A. 1986. “Software Complexity Measurement,” Vol. 28, New York: ACM Press, pp. 1044–1050.
  11. Kearney, Joseph K. Sedlmeyer, Robert L. Thompson, William B. Gray, Michael A. And Adler, Michael A. November 1986. ” SOFTWARE COMPLEXITY MEASUREMENT”, Communications of the ACM, Volume 29, Number 11.
  12. Klemola, T. and Rilling, J. 2004. “ A Cognitive Complexity Metric based on Category Learning,” IEEE International Conference on Cognitive Informatics.
  13. Kushwaha, D. S. and Misra, A. K. January 2006. “A Modified Cognitive Information Complexity Measure of Software,” ACM SIGSOFT Software Engineering Notes, Vol. 31, No.1.
  14. McCabe, T. H. Dec. 1976. “A Complexity Measure,” IEEE Transaction on Software Engineering, vol. 2, no. 4, pp. 308-320.
  15. McQuaid, P. A. 1997. “The profile metric and software quality,” International Conference on Software Quality, October 6-8 1997, Montgomery, pages 245–252.
  16. Mishra, S. 2006. “ A Complexity Measure based on Cognitive Weights.” International Journal of Theoretical and Applied Computer Science, vol 1, no 1, pp. 1-10.
  17. Roberts, E. S. 1995. “Loop exits and structured programming: reopening the debate,” In SIGCSE ’95:Proceedings of the twenty-sixth SIGCSE technical symposium on Computer science education, pages 268–272, New York, NY, USA, ACM Press.
  18. Shao, J. and Wang, Y. 2003. “ A new measure of software complexity based on cognitive weights,” IEEE Canadian Journal of Electrical and Computer Engineering, 28(2):69–74.
  19. Uddin, Md. R. February 2013. “ Equivalence of Problems in Problem Based e-Learning of Database,” Unpublished.
  20. Wang, Y. 2006. “On the Informatics Laws and Deductive Semantics of Software,” IEEE Trans on Systems, Man, nad Cybernetics (C), 36(2), March, pp. 161-171.
  21. Wang, Y. Aug. 2002. “On cognitive informatics: Keynote lecture,” In Proc. 1st IEEE Int. Conf. Cognitive Informatics (ICCI’02), Calgary, Alta., pp. 34–42.
  22. Wang, Y. Oct. 2002. “The real-time process algebra (RTPA),” Annals of Software Engineering, vol. 14, pp. 235–274.
  23. Weyuker, E. J. September 1988. “Evaluating software complexity measure,” IEEE Transaction on Software Engineering, Vol. 14(9): 1357-1365.
  24. Yanming, CHU. and Shiyi, XU. July 2007. “Exploration of Complexity in Software Reliability” Tsinghua Science And Technology, ISSN 1007-0214 48/49 pp266-269, Volume 12, Number S1.
  25. Yin, M. L. Peterson, J. Arellano, R. R. 2004. “Software Complexity factor in Software reliability assessment,In Reliability and Maintainability,” 2004 Annual Symposium-RAMS, pp190-194.
  26. Yindun, S. and Shiyi, X. July 2007. “A New Method for Measurement and Reduction of Software Complexity,” Tsinghua Science And Technology, 1007-021438/49, Volume 12, Number S1, pp.212-216.
  27. Yindun, S. and Shiyi, X. July 2007. “Exploration of Complexity in Software Reliability,” Tsinghua Science And Technology, Volume 12, Number S1, pp.266-269.

Keywords

complexity measurement; basic control structure; cognitive weight; equal distribution; software complexity;