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Definition and validation of requirements management measures
Umeå University, Faculty of Science and Technology, Computing Science.
2007 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The quality of software systems depends on early activities in the software development process, of which the management of requirements is one. When requirements are not managed well, a project can fail or become more costly than intended, and the quality of the software developed can decrease. Among the requirements management practices, it is particularly important to quantify and predict requirements volatility, i.e., how much the requirements are likely to change over time. Software measures can help in quantifying and predicting requirements attributes like volatility. However, few measures have yet been defined, due to the fact that the early phases are hard to formalise. Furthermore, very few requirements measures have been validated, which would be needed in order to demonstrate that they are useful. The approach to requirements management in this thesis is quantitative, i.e. to monitor the requirements management activities and requirements volatility through software measurement. In this thesis, a set of 45 requirements management measures is presented. The measures were defined using the goal question metrics framework for the two predefined goals of the requirements management key process area of the capability maturity model for software. A subset of these measures was validated theoretically and empirically in four case studies. Furthermore, an analysis of validated measures in the literature was performed, showing that there is a lack of validated process, project, and requirements measures in software engineering. The studies presented in this thesis show that size measures are good estimators of requirements volatility. The important result is that size is relevant: increasing the size of a requirements document implies that the number of changes to requirements increases as well. Furthermore, subjective estimations of volatility were found to be inaccurate assessors of requirements volatility. These results suggest that practitioners should complement the subjective estimations for assessing volatility with the objective ones. Requirements engineers and project managers will benefit from the research presented in this thesis because the measures defined, proved to be predictors of volatility, can help in understanding how much requirements will change. By deploying the measures, the practitioners would be prepared for possible changes in the schedule and cost of a project, giving them the possibility of creating alternative plans, new cost estimates, and new software development schedules.

Place, publisher, year, edition, pages
Umeå: Datavetenskap , 2007. , 106 p.
Series
Report / UMINF, ISSN 0348-0542 ; 07.22
Keyword [en]
Requirement, Measures, Volatility, Theoretical Validation, Empirical Validation, Prediction Model, Correlational Study, Subjective Estimation.
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:umu:diva-1467ISBN: 978-91-7264-468-7 (print)OAI: oai:DiVA.org:umu-1467DiVA: diva2:141153
Public defence
2008-01-25, MA121, MIT, Umeå University SE90187, Umeå, 13:15
Opponent
Supervisors
Available from: 2007-12-20 Created: 2007-12-20Bibliographically approved
List of papers
1. Measuring the Requirements Management Key Process Area: Application of the Goal Question Metric to the Requirements Management Key Process Area of the Capability Maturity Model
Open this publication in new window or tab >>Measuring the Requirements Management Key Process Area: Application of the Goal Question Metric to the Requirements Management Key Process Area of the Capability Maturity Model
2001 In: Proceedings of ESCOM: European Software Control and Metrics Conference, 2001, 67–76- p.Chapter in book (Other academic) Published
Identifiers
urn:nbn:se:umu:diva-2842 (URN)
Available from: 2007-12-20 Created: 2007-12-20Bibliographically approved
2. Theoretical Validation and Case Study of Requirements Management Measures
Open this publication in new window or tab >>Theoretical Validation and Case Study of Requirements Management Measures
(English)Manuscript (Other academic)
Identifiers
urn:nbn:se:umu:diva-2843 (URN)
Available from: 2007-12-20 Created: 2007-12-20 Last updated: 2015-09-25Bibliographically approved
3. A Comparison of two Academic Case Studies on Cost Estimation of Changes to Requirements: Preliminary Results
Open this publication in new window or tab >>A Comparison of two Academic Case Studies on Cost Estimation of Changes to Requirements: Preliminary Results
2004 (English)In: Proceeding of SMEF: Software Measurement European Forum, 2004, 226–236- p.Chapter in book (Other academic)
Identifiers
urn:nbn:se:umu:diva-2844 (URN)
Available from: 2007-12-20 Created: 2007-12-20 Last updated: 2015-09-25Bibliographically approved
4. An Industrial Case Study on Requirements Volatility Measures
Open this publication in new window or tab >>An Industrial Case Study on Requirements Volatility Measures
2005 (English)In: Proceeding of APSEC: 12th IEEE Asia Pacific Software Engineering Conference, 2005, 249–256- p.Chapter in book (Other academic)
Identifiers
urn:nbn:se:umu:diva-2845 (URN)
Available from: 2007-12-20 Created: 2007-12-20 Last updated: 2015-09-25Bibliographically approved
5. Construction and Validation of Prediction Models for Changes to Requirements
Open this publication in new window or tab >>Construction and Validation of Prediction Models for Changes to Requirements
(English)Manuscript (Other academic)
Identifiers
urn:nbn:se:umu:diva-2846 (URN)
Available from: 2007-12-20 Created: 2007-12-20 Last updated: 2015-09-25Bibliographically approved
6. A Correlational Study on Four Size Measures as Predictors of Requirements Volatility
Open this publication in new window or tab >>A Correlational Study on Four Size Measures as Predictors of Requirements Volatility
(English)Manuscript (Other academic)
Identifiers
urn:nbn:se:umu:diva-2847 (URN)
Available from: 2007-12-20 Created: 2007-12-20 Last updated: 2015-09-25Bibliographically approved
7. Are Size Measures Better than Expert Opinion? An Industrial Case Study on Requirements Volatility
Open this publication in new window or tab >>Are Size Measures Better than Expert Opinion? An Industrial Case Study on Requirements Volatility
2007 (English)In: Proceeding of APSEC: 14th IEEE Asia Pacific Conference on Software Engineering, 2007, 238–245- p.Chapter in book (Other academic)
Identifiers
urn:nbn:se:umu:diva-2848 (URN)
Available from: 2007-12-20 Created: 2007-12-20 Last updated: 2015-09-25Bibliographically approved

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Citation style
  • apa
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