Discovering Software Process Measures Using Genetic Programming

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CCR-9970893 Khoshgoftaar, Taghi M.Discovering Software Process Measures Using Genetic Programming is a research project that is developing automated methods for finding algorithms that measure novel and useful attributes of software development processes using genetic programming. A cost-effective strategy for assuring high quality software 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. Genetic programming is a promising technology that is well-suited to searching for novel combinations of algorithmic elements that satisfy complex criteria. This project's contributions to the state of the art are empirical exploration of data stored by feature tracking systems and problem reporting systems to discover software process metrics that are useful as independent variables in software quality models, an automated method for goal-driven discovery and measurement of specialized software process metrics using genetic programming, and a demonstration of the application of genetic programming to a new domain, namely, software measurement. This improvement in the state of the art will enable software developers to achieve practical, cost-effective process improvement guided by predictions from software quality models at a new level of accuracy and robustness.