''Neural Network Techniques for Software Quality Evaluation''
Jerry L. Trahan
To appear in 1998 Reliability and Maintainability Symp.
Software quality modeling involves identifying fault-prone modules
and predicting the number of errors in the early stages of the
software development life cycle. This paper investigates the viability
of several neural network techniques for software quality evaluation (SQE).
We have implemented a principal component analysis technique
(used in SQE) with two different neural network training rules, and
have classified software modules as fault-prone or non-fault-prone
using software complexity metric data. Our results reveal that
neural network techniques provide a good management tool in a
software engineering environment.