Skip to main content

An Improved SRS Document Based Software Complexity Estimation and Its Robustness Analysis

  • Conference paper
Computer Networks and Information Technologies (CNC 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 142))

Abstract

Complexity measures are used to predict critical information about reliability and maintainability of software systems from analysis of the source code. Complexity measures also provide continuous feedback during a software project to help control the development process. During testing and maintenance, it provides detailed information about software modules to help pinpoint areas of potential instability. The various complexity measures established so far are based on code and it is too late to perform this activity because a major part of investment has already taken place. Although it is established that a high quality SRS is pre requisite for high quality software, but software complexity estimation based on SRS document has not been properly researched and we find little proposals. Hence the work presented in this paper attempts to empirically demonstrate that the complexity of the code to be produced can be closely estimated based on IEEE software requirement specification document (IEEE 830-1998). Results obtained shows that the complexity values obtained from improved requirement based complexity (I-RBC) are comparable with other established measures and hence the complexity of the software to be produced could be computed from its SRS document. Its robustness is established by strictly evaluating and comparing proposed measure against Weyuker properties.

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 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

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. IEEE Computer Society. IEEE Recommended Practice for Software Requirement Specifications, New York (1994)

    Google Scholar 

  2. Halstead, M.H.: Elements of Software Science. Elsevier North, New York (1977)

    MATH  Google Scholar 

  3. Mc Cabe, T.H.: A Complexity measure. IEEE Transactions on Software Engineering SE-2(6), 308–320 (1976)

    Article  MathSciNet  Google Scholar 

  4. Kushwaha, D.S., Misra, A.K.: A Modified Cognitive Information Complexity Measure of Software. ACM SIGSOFT Software Engineering Notes 31(1) (January 2006)

    Google Scholar 

  5. Klemola, T., Rilling, J.: A Cognitive Complexity Metric based on Category Learning. In: IEEE International Conference on Cognitive Informatics (ICCI 2004) (2004)

    Google Scholar 

  6. Wang, Y.: Measurement of the Cognitive Functional Complexity of Software. In: IEEE International Conference on Cognitive Informatics (2003)

    Google Scholar 

  7. Ashish, S., Kushwaha, D.S.: A Complexity measure based on requirement engineering document, JCSE UK (May 2010)

    Google Scholar 

  8. Boehm, B.: Cost Models for Future Software Life Cycle Processes. In: Annals of Software Engineering Special Volume on Software Process and Product Measurement, Netherlands (1985)

    Google Scholar 

  9. Lakshmanan, K.B., Jayaprakash, S., Sinha, P.K.: Properties of control flow complexity measures. IEEE Transactions on Software Engineering 17(12), 1289–1295 (1991)

    Article  Google Scholar 

  10. Weyuker, E.J.: Evaluating Software complexity measures. IEEE transactions on software engineering 14(14), 1357–1365 (1988)

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ashish, S., Kushwaha, D.S. (2011). An Improved SRS Document Based Software Complexity Estimation and Its Robustness Analysis. In: Das, V.V., Stephen, J., Chaba, Y. (eds) Computer Networks and Information Technologies. CNC 2011. Communications in Computer and Information Science, vol 142. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19542-6_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-19542-6_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19541-9

  • Online ISBN: 978-3-642-19542-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics