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
Construction and Validation of Prediction Models for Number of Changes to Requirements
Umeå universitet, Institutionen för datavetenskap.
Umeå universitet, Institutionen för datavetenskap.ORCID iD: 0000-0003-0639-4234
2007 (English)Report (Other academic)
Abstract [en]

In this paper we present a correlational study in which we assess the ability of five size measures to predict the number of changes to requirements for a medium size software project. The study is explorative, i.e. we analyse the data collected for our measures to find out the best predictor of number of changes. To our knowledge, no empirical validation of requirements change measures as predictors has been performed in an industrial setting. Based on the data collected from two industrial projects for five measures of size of requirements (number of actors, use cases, words, lines, and revisions), we have built and evaluated prediction models for number of changes to requirements. These models can help project managers to estimate the volatility of requirements and minimize the risks caused by volatile requirements, like schedule and costs overruns.We performed a cross systems validation. For our best model we calculated a pred(0.25)=0.5, which is better than the accuracy of common effort prediction models like for example COCOMO. Although our models are likely to have only local validity, the general method for constructing the prediction models could be applied in any software development company. In an earlier study, we showed that decisions solely based on developer perception are unreliable. Predictions models, like the one presented here can help to mitigate that risk.

Place, publisher, year, edition, pages
Umeå University , 2007. , 28 p.
Series
UMINF, 107.03
Keyword [en]
Software engineering, Requirements, Prediction Model, Empirical Validation, Correlational Study
National Category
Computer Science Software Engineering
Identifiers
URN: urn:nbn:se:bth-13438OAI: oai:DiVA.org:bth-13438DiVA: diva2:1046540
Available from: 2008-03-03 Created: 2016-11-14 Last updated: 2017-01-16Bibliographically approved

Open Access in DiVA

No full text

Other links

http://www.cs.umu.se/research/reports/show.cgi?year=2007&nr=003

Search in DiVA

By author/editor
Börstler, Jürgen
Computer ScienceSoftware Engineering

Search outside of DiVA

GoogleGoogle Scholar

Total: 6 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