AN EMPIRICAL-MODEL OF ENHANCEMENT-INDUCED DEFECT ACTIVITY IN SOFTWARE

This study exploits the relationship between functional enhancement (F E) activity and defect distribution to produce a model for predicting FE induced defect activity, We achieve this in 2 steps: 1) Apply canon ical correlation analysis to model the relationship between a set of F E activity indicators and a set of defect activity indicators. This an alysis isolates 1 dimension of this relationship having strong correla tion. 2) Model the relationship between the latent variables at this d imension as a simple linear regression. This model demonstrates predic tive quality sufficient for application as a software engineering tool . The predictive model considers FE activity as the sole source of var iation in defect activity. Other sources of variation, such as differe nces: in the product to be enhanced, in programmer skill level, in pro grammer product understanding, and in the software development process , are not modeled, but remained constant throughout the development ef fort that yielded the modeled data. Models developed with this techniq ue are intended for predicting defect activity in the program modules that result from the next iteration of the same development process, i n production Of the next release of the modeled product, with the same key people implementing the software changes that introduce FE. Even in this application, software engineers should understand & control th e impacts of the unmodeled sources of variation, The modeling techniqu e scales to larger development efforts involving several hey people by either developing unique models for each area of responsibility, or a dding independent variables that account for variation introduced by d iffering skill & understanding levels.