Date of Graduation
1999
Document Type
Dissertation
Degree Type
PhD
College
Statler College of Engineering and Mineral Resources
Department
Lane Department of Computer Science and Electrical Engineering
Committee Chair
Mike Henry
Committee Co-Chair
Jack Callahan
Committee Member
Wills Cooley
Committee Member
James Miller
Committee Member
George Trapp
Abstract
This work describes and presents a process for building a neural network-based reuse economic model. This study adopts a bottom-up perspective where granularity moves from the developer (software program) level to the enterprise level. The goal of the proposed process is to create a model which provides accurate and reliable results which can be applied to various forms of software reuse in various programming paradigms. The current state-of-practice for measuring effort and reuse effort is extended, leading to improvements in accuracy. Furthermore, in order to accomplish this goal, it becomes necessary to address different forms of reuse: black-box and white-box reuse and different perspectives of reuse: design-for-reuse and design-with-reuse. The reuse economic model must operate for both procedural and object-oriented programming paradigms. A more realistic definition of what constitutes reuse is described. This work expands upon the previous works by the author including: [Boetticher 93a] which verifies and validates the use of neural networks for assessing software; [Boetticher 93b] which produces a neural network-based reusability metric; and [Boetticher 95] which describes a process of using neural networks to determine “hot spots†in a software repository.
Recommended Citation
Boetticher, Gary Dawson, "A neural network-based bottom-up approach for building a software reuse economic model." (1999). Graduate Theses, Dissertations, and Problem Reports. 8503.
https://researchrepository.wvu.edu/etd/8503