By Topic

On prediction of cost and duration for risky software projects based on risk questionnaire

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Mizuno, O. ; Dept. of Informatics & Math. Sci., Osaka Univ., USA ; Adachi, T. ; Kikuno, T. ; Takagi, Y.

The paper proposes a new approach that can discriminate risky software development projects from smoothly or satisfactorily going projects and give an explanation for the risk. We have already developed a logistic regression model which predicts whether a project becomes risky or not (O. Mizuno et al., 2000). However, the model returned the decision with a calculated probability only. Additionally, a formula was constructed based on the risk questionnaire which includes 23 questions. We therefore try to improve the previous method with respect to accountability and feasibility. In the new approach, we firstly construct a new risk questionnaire including only 9 questions (or risk factors), each of which is concerned with project management. We then apply multiple regression analysis to the actual project data, and clarify a set of factors which contributes essentially to estimate the relative cost error and the relative duration error, respectively. We then apply the constructed formulas to another set of project data. The analysis results show that both the cost and duration of risky projects are estimated fairly well by the formulas. We can thus confirm that our new approach is applicable to software development projects in order to discriminate risky projects from appropriate projects and give reasonable explanations for the risk

Published in:

Quality Software, 2001. Proceedings.Second Asia-Pacific Conference on

Date of Conference:

2001