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This paper proposes a statistical method that can be used to monitor, control, and predict the quality (measured in terms of the failure intensity) of a software system being tested. The method consists of three steps: estimation of the failure intensity (failures per unit of execution time) based on groups of failures, fitting the logarithmic Poisson model to the estimated failure intensity data, and constructing confidence limits for the failure intensity process. The proposed estimation method is validated through a simulation study. A method for predicting the additional execution time required to achieve a failure intensity objective is also discussed. A set of failure data collected from a real-time command and control system is used to demonstrate the proposed method.