Predicting Expected Budgets: Integrated Quality and Risk

If you were to ask any software development manager if quality is an essential attribute for delivering a project on time and within budget, they would emphatically answer "yes". If you were to ask these same managers if they incorporated existing quality metrics into their baselining and budgeting processes, few managers would answer in the affirmative. Although mid to large-sized software projects overrun planned budgets at an alarming frequency, most projects fail to include quality data in the estimation process. This study examines some of the most extensively adopted estimation techniques and identifies how these techniques fail to utilize quality measures. In addition, a new model is introduced that incorporates quality metrics, which reduce variance between estimates and project actual expenditures. This research illustrates how the incorporation of quality data into estimation and baseline processes can potentially reduce software project failure rates.

Author

• Duran, Jason P

Language

• en

Keyword

• Prediction
• Bayesian Network
• Quality
• Overrun
• Risk
• Budget

Date created

• 2019

Type of Work

• Dissertation

License

• All rights reserved

Rights statement

• In Copyright

GW Unit

• Engineering Management

Degree

• D.Engr.

Advisor

• Fossaceca, John

Committee Member(s)

• Etemadi, Amir
• Fossaceca, John
• Islam, Muhammed

Persistent URL

•  https://scholarspace.library.gwu.edu/etd/n870zr22b