An evaluation method which allows existing reliability growth models to provide better predictions of software behavior is presented. The method is primarily based on the analysis of the trend exhibited by the data collected on the program (which is determined by reliability growth tests). Reliability data are then partitioned according to the trend, and two types of reliability growth models can be applied: when the data exhibit reliability decrease followed by reliability growth, an S-shaped model can be applied, and in case of reliability growth, most of the other existing reliability growth models can be applied. The hyperexponential model is shown to allow prediction of the software residual failure rate in operation, and this failure rate is used as a qualification index for the software product. The method is illustrated through its application to the Brazilian electronic switching system TROPICO-R.>