A decision model for setting target levels in software quality function deployment to respond to rapidly changing customer needs


CONCURRENT ENGINEERING-RESEARCH AND APPLICATIONS, vol.20, no.1, pp.19-29, 2012 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 20 Issue: 1
  • Publication Date: 2012
  • Doi Number: 10.1177/1063293x11435344
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.19-29
  • Keywords: software quality function deployment, quality function deployment, fuzzy regression, fuzzy optimization, ordered weighted averaging, PRODUCT DEVELOPMENT, FUZZY REGRESSION, DESIGN, REQUIREMENTS, MANAGEMENT
  • Galatasaray University Affiliated: Yes


Responding to the need for enhanced software quality, software manufacturers have recently applied quality improvement techniques to software development process. Software quality function deployment, as a technique for better quality designs that match customer expectations, has been used in software development to maximize customer satisfaction. This article proposes a fuzzy regression-based decision framework that considers future requirements for setting target levels of technical attributes in software quality function deployment. Ordered weighted averaging operators are employed to implement quantifier-guided aggregations that enable to calculate the integrated importance degree for each customer need by combining the current and future voice of customers. Then, a fuzzy optimization model, which considers the integrated importance degrees of customer needs and uses the functional relationships obtained by fuzzy regression, is developed to determine target levels of technical attributes of the new or improved software products that meet customer needs at the time when the product reaches the market. The fuzzy optimization model includes both the center values and the spread values of the parameter estimates and thus circumvents loss of information in determining target levels of technical attributes. A search engine quality improvement problem is presented to illustrate the proposed decision framework.