Dr. Taghi M. Khoshgoftaar is the Principal Investigator, Dr. Matthew P. Evett is co-Principal Investigator, and Dr. Edward B. Allen is Senior Research Associate. High quality software is essential for mission-critical systems. One cost-effective strategy is to target enhancement activities to those modules that are most likely to have faults. When the methods being developed by this project are applied to a software development project, the resulting software process metrics will be novel, specialized for the development organization, and useful for predicting software quality. This project is focusing on data stored in both kinds of systems.
Many developers use such systems to manage implementation of requirements and fixing bugs.
Although these kinds of systems appear to be a rich source of information on development process history, this readily available data has been almost completely unused for predicting software quality. Genetic programming is a promising technology that is well-suited to searching for novel combinations of algorithmic elements that satisfy complex criteria. GP is a member of the evolutionary computation family of adaptive search techniques, whose defining characteristic is an adaptation mechanism based upon neo-Darwinian natural selection. GP enables the exploitation of identifiers, categories, dates, and text, as well as counts and quantities. GP makes no prior assumptions about the functional form of relationships among algorithmic elements.