Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Predicting Software Test Effort in Iterative Development Using a Dynamic Bayesian Network
Responsible organisation
2010 (English)Conference paper, (Refereed) Published
Abstract [en]

Projects following iterative software development methodologies must still be managed in a way as to maximize quality and minimize costs. However, there are indications that predicting test effort in iterative development is challenging and currently there seem to be no models for test effort prediction. This paper introduces and validates a dynamic Bayesian network for predicting test effort in iterative software devel- opment. The proposed model is validated by the use of data from two industrial projects. The accuracy of the results has been verified through different prediction accuracy measurements and statistical tests. The results from the validation confirm that the model has the ability to predict test effort in iterative projects accurately.

Place, publisher, year, edition, pages
San Jose, CA: IEEE , 2010.
Keyword [en]
agile, Bayesian, prediction
National Category
Software Engineering Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:bth-7685Local ID: oai:bth.se:forskinfoA497CC3DD22D5361C12578010070793FOAI: oai:DiVA.org:bth-7685DiVA: diva2:835329
Conference
21st IEEE International Symposium on Software Reliability Engineering
Available from: 2012-09-18 Created: 2010-12-22 Last updated: 2015-06-30Bibliographically approved

Open Access in DiVA

fulltext(774 kB)52 downloads
File information
File name FULLTEXT01.pdfFile size 774 kBChecksum SHA-512
619e4e20f0161d48bd863efe98212c44c982ee0f045e4e9994be1f00a167fd91355ca43f34bfb1ae23c2198cb9b793741056d9454c3f5518bbe6b46bdbdbb60c
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Torkar, Richard
Software EngineeringProbability Theory and Statistics

Search outside of DiVA

GoogleGoogle Scholar
Total: 52 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 326 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf