CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Analysis of Static and Dynamic Metrics for Productivity and Time Complexity

by Manik Sharma, Dr. Gurdev Singh
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 30 - Number 1
Year of Publication: 2011
Authors: Manik Sharma, Dr. Gurdev Singh
10.5120/3609-5017

Manik Sharma, Dr. Gurdev Singh . Analysis of Static and Dynamic Metrics for Productivity and Time Complexity. International Journal of Computer Applications. 30, 1 ( September 2011), 7-13. DOI=10.5120/3609-5017

@article{ 10.5120/3609-5017,
author = { Manik Sharma, Dr. Gurdev Singh },
title = { Analysis of Static and Dynamic Metrics for Productivity and Time Complexity },
journal = { International Journal of Computer Applications },
issue_date = { September 2011 },
volume = { 30 },
number = { 1 },
month = { September },
year = { 2011 },
issn = { 0975-8887 },
pages = { 7-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume30/number1/3609-5017/ },
doi = { 10.5120/3609-5017 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:15:46.504417+05:30
%A Manik Sharma
%A Dr. Gurdev Singh
%T Analysis of Static and Dynamic Metrics for Productivity and Time Complexity
%J International Journal of Computer Applications
%@ 0975-8887
%V 30
%N 1
%P 7-13
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The aspiration of this study is to perform the comparative analysis of static and dynamic metric for structured programming environment. Software metrics is one of the vital tools that can be worn to find significant estimates for software products and directs us in intriguing managerial and technical decisions. Software metrics have become an integral part of software development and are used during every phase of the software development life cycle. Research in the area of software metrics tends to focus predominantly on static metrics that are obtained by static analysis of the software artifact. But software quality attributes such as execution time, performance and reliability depend on the dynamic activities of the software artifact. With the help of conventional static metrics we are not able to analyze various facts of software’s. It is very important to understand the dynamic behaviour of the program or an application in developing new effective strategies in computer science. This becomes the basis for working on dynamic metrics in place of traditional static metrics. Dynamic metrics gives more accurate result than static metrics as they are able to capture the dynamic behaviour of the software system during measurement.

References
  1. H F Li, W K Cheung “An Empirical Study of Software Metrics” Software Engineering IEEE Transactions on (1987) Volume: SE-13, Issue: 6, Pages: 697-708
  2. N E Fenton “Software Metrics” Conference Proceedings of on the future of Software engineering ICSE 00(2000) Volume: 8, Issue: 2, Publisher: ACM Press
  3. Kuljit Kaur Chahal , Hardeep Singh “Metrics to study symptoms of bad software designs” ACM SIGSOFT Software Engineering Notes (2009) Volume: 34, Issue: 1, Pages: 1
  4. 12 Steps to Useful Software Metrics by Linda Westfall,
  5. online www.westfallteam.com/Papers/12_steps_paper.pdf
  6. Manik Sharma , Gurdev Singh “Static and Dynamic metrics- A Comparative Analysis”, Emerging Trends in Computing and Information Technology 2011.
  7. Tu Honglei, Sun wei, Zhang Yanan, “The Research of Software metric and software complexity metrics” International Forum on Computer Science Technology and Applications (2009) Publisher: IEEE, Pages: 131-136
  8. Somerville “Software Engineering” 6th Edition, Editor: Addison Wesley.
  9. Li, H.F., Cheung, W.K. “An Experimental investigation of software metric and their relationship to software development effort”, IEEE Transaction on software engineering 649-653, Piscataway, NJ, USA.
  10. Thomas J McCabe, “A Complexity Measure”, IEEE Transaction on Software Engineering, Vol. SE-2 No. 4
  11. 308-320
  12. Van Doren “Cyclometic Complexity”
  13. Online web publication access in: http://www.sei.cmu.edu/str/decriptions/cyclometic_body.html
  14. Geoffery K. Gill, Chris F. Kemerer, “Cyclomatic Complexity Metrics Reivisted: An empirical Study of Software Development and Maintenance” Center for Information System research.
  15. Norman Fenton and Martin Neil “Software Metrics and Risk” proceeding of FESMA 99 2nd European Software Measurement Conference.
  16. Gurdev Singh, Dilbag Singh et. al “A Study of Software Metrics” International Journal of Computational Engineering and Management. vol. 11. 2230-7893.
  17. Kamaljit Kaur, Kirti Minhas et. al “Static and Dynamic Complexity Analysis of Software Metrics”, World Academy of Science, Engineering and Technology 56 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Software Metric Accuracy Performance

Powered by PhDFocusTM