Abstract: |
Source code size, in terms of SLOC (Source Lines of Code), is an important parameter of many parametric software development effort estimation methods. Moreover, test code size, in terms of TLOC (Test Lines of Code), has been used in many studies to indicate the effort involved in testing. This paper aims at comparing empirically the Use Case Metrics (UCM) method, a use case model based method that we proposed in previous work, and the Objective Class Points (OCP) method in terms of early prediction of SLOC and TLOC for object-oriented software. We used both simple and multiple linear regression methods to build the prediction models. An empirical comparison, using data collected from four open source Java projects, is reported in the paper. Overall, results provide evidence that the multiple linear regression model, based on the combination of the use case metrics, is more accurate in terms of early prediction of SLOC and TLOC than: (1) the simple linear regression models based on each use case metric, and (2) the simple linear regression model based on the OCP method. |