Evaluating software development effort model-building techniques for application in a real-time telecommunications environment

This paper describes the comparative evaluation of four methods of building software development effort models based on least squares regression, artificial neural networks, case-based reasoning and rule induction. Some deficiencies are identified in the main measurement of estimating effectiveness currently used in comparative evaluations, `mean magnitude of relative error´ (MMRE), and a complementary measurement, `mean variation from estimate´ (MVFE) is suggested as more accurately reflecting the practitioner´s viewpoint. Given the current state of development of the techniques, the parallel use of least squares regression and case-based reasoning is recommended as appearing to give the most reliable results in the studied environment