Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

Towards a constructive quality model. Part 2: Statistical techniques for modelling software quality in the ESPRIT REQUEST project

Towards a constructive quality model. Part 2: Statistical techniques for modelling software quality in the ESPRIT REQUEST project

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Add to cart
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)
Add to cart

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
Software Engineering Journal — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

© The Institution of Electrical Engineers
Published
Errata or comment

This paper discusses the type of statistical techniques that will be required to formulate, evaluate and use the proposed REQUEST constructive quality model (COQUAMO). Statistical techniques are evaluated in terms of the probable nature and mode of use of COQUAMO, the requirements for model and metric validation, and the problems associated with software metrics data. Examples of preliminary evaluation of the proposed statistical techniques are given using genuine software metrics data.

Inspec keywords: statistical analysis; software reliability; research initiatives

Other keywords: REQUEST project; COQUAMO; constructive quality model; statistical techniques; ESPRIT; metric validation; software metrics data; modelling software quality

Subjects: Research and development; Other topics in statistics; Systems analysis and programming

References

    1. 1)
      • Kafura, D., Canning, J.: `A validation of software metrics using many metrics and two resources', Proceedings of Eighth International Conference on Software Engineering, 1985, London, England.
    2. 2)
      • M.H. Halstead . (1977) , Elements of software science.
    3. 3)
      • B.W. Boehm . (1981) , Software engineering economics.
    4. 4)
      • Romeu, J.L., Gloss-Soler, S.A.: `Some measurement problems detected in the analysis of software productivity data and their statistical consequences', Proceedings of IEEE International Conference on Computer Software and Applications (COMPSAC), 1983.
    5. 5)
      • T.J. McCabe . A complexity measure. IEEE Transactions on Software Engineering , 4
    6. 6)
      • F. Mosteller , J.W. Tcikey . (1977) , Data analysis and regression.
    7. 7)
      • Doerflinger, C.W., Basili, V.R.: `Monitoring software development through dynamic variables', Proceedings of IEEE International Conference on Computer Software and Applications (COMPSAC), 1983.
    8. 8)
      • B.A. Kitchenham . Measures of programming complexity. ICL Technical Journal , 3 , 298 - 316
    9. 9)
      • Kitchenham, B.A.: `Metrics in practice', Pergamon Infotech State of the Art Report on Software Reliability, 1986.
    10. 10)
      • D. Gujarati . (1978) , Basic econometrics.
    11. 11)
      • S. Siegal . (1956) , Non-parametric statistics for the behavioural sciences.
    12. 12)
      • P.J. Huber . (1981) , Robust statistics.
    13. 13)
      • Frewin, G.D., Hamer, P., Kitchenham, B.A., Ross, N., Wood, L.M.: `Quality measurement and modelling — state of the art report', R1.1.1, Commission of the European Communities ESPRIT REQUEST Project Report, 1985.
http://iet.metastore.ingenta.com/content/journals/10.1049/sej.1987.0015
Loading

Related content

content/journals/10.1049/sej.1987.0015
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
See Also
This article has the following associated article(s):
Towards a constructive quality model. Part 1: Software quality modelling, measurement and prediction
Print this page
This is a required field
Please enter a valid email address