Skip to main content

Modified Cognitive Complexity Measure

  • Conference paper
Computer and Information Sciences – ISCIS 2006 (ISCIS 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4263))

Included in the following conference series:

Abstract

In cognitive functional size measure, the functional size is proportional to weighted cognitive complexity of all internal BCS‘s and number of input and output. This paper proposes the modification in cognitive functional size complexity measure. The proposed complexity measure is proportional to total occurrence of operators and operands and all internal BCS´s. The operators and operands are equally important in design consideration. Thus, the contribution of the operators, operands and cognitive aspects complete the definition of a complexity measure in terms of cognitive. Accordingly, a new formula is developed for calculating the modified cognitive complexity measure. An attempt has also been made to evaluate modified cognitive complexity measure in terms of nine Weyuker’s properties, through examples. It has been found that seven of nine Weyuker’s properties have been satisfied by the modified cognitive complexity measure and hence establishes as a well-structured one.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Baker, A.L., Zweben, S.H.: A comparison of Measures of control flow complexity. IEEE Transaction on Software Engineering 6, 506–511 (1980)

    Article  MathSciNet  Google Scholar 

  2. Basili, V.R.: Qualitative software complexity models: A summary in tutorial on models and methods for software management and engineering. IEEE Computer Society Press, Los Alamitos (1980)

    Google Scholar 

  3. Basili, V.R., Selby, R.W., Phillips, T.Y.: Metric analysis and data validation across fortran projection. IEEE Transactions on Software Engineering 9, 652–663 (1983)

    Article  Google Scholar 

  4. Halstead, M.H.: Elements of software science. Elsevier North-Holland, New York (1997)

    Google Scholar 

  5. Harrison, W.: An entropy-based measure of software complexity. IEEE Transactions on Software Engineering 18(11), 1025–1029 (1992)

    Article  Google Scholar 

  6. Kemola, T., Rilling, J.: A Cognitive Complexity Metric Based on Category Learning. In: Proceeding of the 2nd IEEE International Conference on Cognitive Informatics, pp. 1044–1050. IEEE CS Press, Los Alamitos (2003)

    Google Scholar 

  7. Kushwaha, D.S., Misra, A.K.: Robustness Analysis of Cognitive Information Complexity Measure using Weyuker’s Properties. ACM SIGSOFT Software Engineering Notes 31(1), 1–6 (2006)

    Google Scholar 

  8. McCabe, T.H.: A complexity measure. IEEE Transactions Software Engineering SE-2(6), 308–320 (1976)

    Article  MathSciNet  Google Scholar 

  9. Misra, S., Misra, A.K.: Evaluating cognitive complexity measure with Weyuker’s properties. In: Proceedings of third IEEE International Conference on Cognitive Informatics, pp. 103–108. IEEE CS Press, Los Alamitos (2004)

    Chapter  Google Scholar 

  10. Oviedo, E.I.: Control flow, data and program complexity. In: Proc. IEEE COMPSAC, Chicago, IL, pp. 146–152 (1980)

    Google Scholar 

  11. Weyuker, E.J.: Evaluating software complexity measure. IEEE Transaction on Software Complexity Measure 14(9), 1357–1365 (1988)

    Article  MathSciNet  Google Scholar 

  12. Woodward, M.R., Hennel, M., David, A.: A measure of control flow complexity in program text. IEEE Transaction on Software Engineering SE-5(1), 45–50 (1979)

    Article  Google Scholar 

  13. Wang, Y.: Component Based Software Measurement. In: Barbier, F. (ed.) Business Component - Based Software Engineering, pp. 247–262 (2002)

    Google Scholar 

  14. Wang, Y.: The real-time process algebra (RTPA). Annuals of Software Engineering An International Journal 14, 235–274 (2002)

    Article  MATH  Google Scholar 

  15. Wang, Y., Shao, J.: On cognitive informatics, Keynote Lecture. In: Proceeding of the 1st IEEE International Conference on Cognitive Informatics, pp. 34–42 (2002)

    Google Scholar 

  16. Wang, Y., Shao, J.: A new measure of software complexity based on cognitive weight. Can. J. Elect. Comput. Engg., 69–74 (2003)

    Google Scholar 

  17. Wang, Y.: On cognitive informatics: Foundation of Software Engineering. In: Proceeding of the 3rd IEEE International Conference on Cognitive Informatics (ICCI 2004), pp. 22–31. IEEE CS Press, Los Alamitos (2004)

    Chapter  Google Scholar 

  18. Wang, Y.: On the Informatics Laws of Software. In: Proceeding of the 1st IEEE International Conference on Cognitive Informatics (ICCI 2004), pp. 132–141. IEEE CS Press, Los Alamitos (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Misra, S. (2006). Modified Cognitive Complexity Measure. In: Levi, A., Savaş, E., Yenigün, H., Balcısoy, S., Saygın, Y. (eds) Computer and Information Sciences – ISCIS 2006. ISCIS 2006. Lecture Notes in Computer Science, vol 4263. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11902140_109

Download citation

  • DOI: https://doi.org/10.1007/11902140_109

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-47242-1

  • Online ISBN: 978-3-540-47243-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics