Predicting good requirements for in-house development projects

  • Authors:

  • June Verner;Karl Cox;Steven J. Bleistein

  • Affiliations:

  • National ICT Australia, Sydney, Australia;National ICT Australia, Sydney, Australia;National ICT Australia, Sydney, Australia

  • Venue:
  • Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering
  • Year:
  • 2006

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Abstract

We surveyed software practitioners regarding software development practices used during recent projects. Five categories of questions broadly related to requirements were asked: the sponsor, customer/users, requirements issues, the project manager and project management, and the development process. Relationships between project factors and good requirements were investigated. We developed requirements prediction equations by dividing our response data into two data sets. Using binary logistic regression on each set we tested the equations developed. Such analysis provides us with insight into which variables are significant predictors of good requirements. The best predictors were 1) the customers/users had a high level of confidence in the development team, with 2) risks were controlled and managed by the project manager.