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Evaluation of Code and Data Spatial Complexity Measures

  • Jitender Kumar Chhabra
  • Varun Gupta
Part of the Communications in Computer and Information Science book series (CCIS, volume 40)

Abstract

The comprehension of a program is largely dependent on the spatial abilities of the programmers. Some spatial complexity measures have been proposed in the literature to estimate the effort required in the process of software comprehension. Two of the widely discussed and important spatial measures for procedure-oriented software are code spatial complexity and data spatial complexity. This paper evaluates these two measures using Weyuker’s properties. The paper further validates these two measures on the basis of one of the most acceptable framework proposed by Briand et al. The results of this study show that these two spatial metrics satisfy all properties and parameters required by these two formal evaluation frameworks and thus these spatial measures are practical and useful.

Keywords

Spatial complexity software complexity software psychology software metrics 

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References

  1. 1.
    Mayrhauser, A.V., Vans, A.M.: Program Comprehension during Software Maintenance and Evolution. IEEE Computer 3, 44–55 (1995)CrossRefGoogle Scholar
  2. 2.
    Shneiderman, B.: Software Psychology: Human Factors in Computer and Information Systems. Winthrop Publishers Inc. (1980)Google Scholar
  3. 3.
    Baddeley, A.: Human Memory: Theory and Practice- Revised edn. Psychology Press, Hove (1997)Google Scholar
  4. 4.
    Chhabra, J.K., Aggarwal, K.K., Singh, Y.: Code and Data Spatial Complexity: Two Important Software Understandability Measures. Information and Software Technology 45(8), 539–546 (2003)CrossRefGoogle Scholar
  5. 5.
    Chhabra, J.K., Aggarwal, K.K., Singh, Y.: Measurement of Object Oriented Software Spatial Complexity. Information and Software Technology 46(10), 689–699 (2004)CrossRefGoogle Scholar
  6. 6.
    Douce, C.R., Layzell, P.J., Buckley, J.: Spatial Measures of Software Complexity. Technical Report, Information Technology Research Institute, University of Brighton, UK (1999)Google Scholar
  7. 7.
    Weyuker, E.J.: Evaluating Software Complexity Measure. IEEE Transactions on Software Complexity Measure 14(9), 1357–1365 (1988)CrossRefGoogle Scholar
  8. 8.
    Briand, L., Morasca, S., Basili, V.: Property-based Software Engineering Measurement. IEEE Transactions of Software Engineering 22(1), 68–86 (1996)CrossRefGoogle Scholar
  9. 9.
    Chidamber, S., Kemerer, C.: A Metrics Suite for Object-Oriented Design. IEEE Transactions on Software Engineering 20(6), 476–493 (1994)CrossRefGoogle Scholar
  10. 10.
    Tegarden, D.P., Sheetz, S.D., Monarchi, D.E.: The Effectiveness of Traditional Metrics for Object-Oriented Systems. In: Twenty-Fifth Hawaii International Conference on System Sciences, vol. IV. IEEE Computer Society Press, Los Alamitos (1992)Google Scholar
  11. 11.
    Tegarden, D.P., Sheetz, S.D., Monarchi, D.E.: A Software Complexity Model of Object-Oriented Systems. Decision Support Systems: the International Journal 13, 241–262 (1995)CrossRefGoogle Scholar
  12. 12.
    Misra, S., Misra, A.K.: Evaluation and Comparison of Cognitive Complexity Measure. ACM SIGSOFT Software Engineering Notes 32(2), 1–5 (2007)Google Scholar
  13. 13.
    Chhabra, J.K., Aggarwal, K.K., Singh, Y.: A Unified Measure of Complexity of Object-Oriented Software. Journal of the Computer Society of India 34(3), 2–13 (2004)CrossRefGoogle Scholar
  14. 14.
    McCabe, T.J.: A Complexity Measure. IEEE Transactions on Software Engineering 2(4), 308–319 (1976)CrossRefGoogle Scholar
  15. 15.
    Halstead, M.H.: Elements of Software Science. North Holland, New York (1977)Google Scholar
  16. 16.
    Oviedo, E.I.: Control Flow, Data and Program Complexity. In: IEEE COMPSAC, Chicago, IL, pp. 146–152 (1980)Google Scholar
  17. 17.
    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
  18. 18.
    Basili, V.R., Selby, R.W., Phillips, T.Y.: Metric Analysis and Data Validation across FORTRAN Projection. IEEE Transactions on Software Engineering 9(6), 652–663 (1983)CrossRefGoogle Scholar
  19. 19.
    Wang, Y., Shao, J.: Measurement of the Cognitive Functional Complexity of Software, In: IEEE International Conference on Cognitive Informatics, ICCI 2003, pp. 67–71 (2003)Google Scholar
  20. 20.
    Wang, Y., Shao, J.: New Measure of Software Complexity based on Cognitive Weights. Canadian Journal of Electrical & Computer Engineering 28(2), 69–74 (2003)CrossRefGoogle Scholar
  21. 21.
    Misra, S.: Modified Cognitive Complexity Measure. In: Levi, A., Savaş, E., Yenigün, H., Balcısoy, S., Saygın, Y. (eds.) ISCIS 2006. LNCS, vol. 4263, pp. 1050–1059. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  22. 22.
    Misra, S.: A Complexity Measure based on Cognitive Weights. International Journal of Theoretical and Applied Computer Science 1(1), 1–10 (2006)Google Scholar
  23. 23.
    Chhabra, J.K., Gupta, V.: Towards Spatial Complexity Measures for Comprehension of Java Programs. In: International Conference on Advanced Computing and Communications, pp. 430–433 (2006)Google Scholar
  24. 24.
    Lakshmanian, K.B., Jayaprakash, S., Sinha, P.K.: Properties of Control-Flow Complexity Measures. IEEE Trans. Software Eng. 17(2), 1289–1295 (1991)CrossRefGoogle Scholar
  25. 25.
    Tian, J., Zelkowitz, M.V.: A Formal Program Complexity Model and its Application. J. Systems Software 17, 253–266 (1992)CrossRefGoogle Scholar
  26. 26.
    Baker, A.L., Zweben, S.H.: A Comparison of Measures of Control Flow Complexity. IEEE Transaction on Software Engineering 6(6), 506–511 (1980)CrossRefGoogle Scholar
  27. 27.
    Misra, S., Misra, A.K.: Evaluating Cognitive Complexity Measure with Weyuker Properties. In: Third IEEE International Conference on Cognitive Informatics (ICCI 2004), pp. 103–108 (2004)Google Scholar
  28. 28.
    Misra, S.: Validating Modified Cognitive Complexity Measure. ACM SIGSOFT Software Engineering Notes 32(3), 1–5 (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Jitender Kumar Chhabra
    • 1
  • Varun Gupta
    • 1
  1. 1.Department of Computer EngineeringNational Institute of Technology, KurukshetraKurukshetraIndia

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