Predicting software errors, during development, using nonlinear regression models: a comparative study

Accurately predicting the number of faults in program modules is a major problem in quality control of a large software system. The authors' technique is to fit a nonlinear regression model to the number of faults in a program module (dependent variable) in terms of appropriate software metrics. Thi... View More