Skip to main content

Parametric Software Metric

  • Conference paper
Software Engineering and Computer Systems (ICSECS 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 181))

Included in the following conference series:

Abstract

Software metrics make meaningful information such as reliability, maintainability to help developers, architecture and so on. It also decides what kind of information is needed to produce a meaningful result from a preset goal. Software metrics should be customizable according to the needs of different users. Earlier, software metrics were not flexible as they supported results focusing on one particular goal. To resolve these problems, we suggest new software metric named Parametric Software Metric. It can be customized by users and it also supports a formula to make a result. Users will get an appropriate result by customizing and using it.

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
Softcover Book
USD 169.99
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. Scotto, M., Sillitti, A.: A relational approach to software metrics. In: Proc. of the 2004 ACM symposium on Applied computing, pp. 1536–1540 (2004)

    Google Scholar 

  2. Umarji, M., Seaman, C.: Gauging acceptance of software metrics: Comparing perspectives of managers and developers. In: 3rd Int. Symposium on Empirical Software Engineering and Measurement (ESEM 2009), pp. 236–247 (2009)

    Google Scholar 

  3. Fenton, N.: New Directions for Software Metrics. In: Keynote Talk CIO Symposium on Software Best Practices, pp. 1–21 (2006)

    Google Scholar 

  4. Roche, J.M.: Roche.: Software Metrics and Measurement Principles. ACM SIGSOFT Software Engineering Notes 19(1), 77–85 (1994)

    Article  Google Scholar 

  5. Linda, M., Laird, M., Brennan, C.: Software Measurement and Estimations: A Practical Approach. Wiley-IEEE Computer Society Press, Chichester (2006)

    Google Scholar 

  6. Fenton, N.E., pfleeger, S.L.: Software Metrics: A Rigorous and Practical Approach, 2nd edn. PWS Publishing Co (1997)

    Google Scholar 

  7. Quality Assurance and Metrics, http://www.eecs.qmul.ac.kr/~norman/papers/qa_metrics_artical/index_qa_met.htm

  8. Kaur, A., Singh, S.: Empirical Analysis of CK & MOOD Metric Suit. Int. Journal of Innovation, Management and Technology 1(5) (2010)

    Google Scholar 

  9. Kaner, C., Bond, W.: Software engineering metrics: What do they measure and how do we know? In: 10th Int. Software Metrics Symposium(METRICS 2004). IEEE Computer Society Press, Los Alamitos (2004)

    Google Scholar 

  10. Canfora, G., Concas, G.: 2010 ICSE Workshop on Emerging Trends in Software Metrics. ACM SIGSOFT Software Engineering Notes 35(5), 51–53 (2010)

    Article  Google Scholar 

  11. Lincke, R., Lundberg, J.: Comparing software metrics tools. In: Proc. of the 2008 international symposium on Software testing and analysis, pp. 131–142 (2008)

    Google Scholar 

  12. Lisper, B.: Fully automatic, parametric worst-case execution time analysis. In: 3rd International Workshop on Worst-Case Execution Time Analysis, pp. 99–102. Polytechnic Institute of Porto, Portugal (2003)

    Google Scholar 

  13. Vivancos, E., Healy, C., Mueller, F., Whalley, D.: Parametric Timing Analysis. In: Workshop on Language, Compilers, and Tools for Embedded Systems, vol. 36(8), pp. 88–93. ACM Press, New York (2001)

    Chapter  Google Scholar 

  14. Bernat, G., Burns, A.: An Approach To Symbolic Worst-Case Execution Time Analysis. In: Proc. 25th IFAC Workshop on Real-Time Programming (2000)

    Google Scholar 

  15. Coffman, J., Healy, C., Mueller, F., Whalley, D.: Generalizing parametric timing analysis. In: Proc. of the 2007 ACM SIGPLAN/SIGBED Conference on LCTES 2007, vol. 42(7), pp. 152–154 (2007)

    Google Scholar 

  16. WCET project, http://www.mrtc.mdh.se/projects/wcet/benchmarks.html

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

Shin, W., Kim, TW., Kim, DH., Chang, CH. (2011). Parametric Software Metric. In: Zain, J.M., Wan Mohd, W.M.b., El-Qawasmeh, E. (eds) Software Engineering and Computer Systems. ICSECS 2011. Communications in Computer and Information Science, vol 181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22203-0_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-22203-0_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22202-3

  • Online ISBN: 978-3-642-22203-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics