One of the most important steps towards effective software maintenance of a large complicated system is to understand how program features are spread over the entire system and their interactions with the program components. However, we must first be able to represent an abstract feature in terms of some concrete program components.In this paper, we use an execution slice-based technique to identify the basic blocks which are used to implement a program feature. Three metrics are then defined, based on this identification, to determine quantitatively, the disparity between a program component and a feature, the concentration of a feature in a program component, and the dedication of a program component to a feature. The computations of these metrics are automated by incorporating them in a tool (chi-Suds), which makes the use of our metrics immediately applicable in real-life contexts. We demonstrate the effectiveness of our technique by experimenting with a reliability and performance evaluator.Results of our study suggest that these metrics can provide an indication of the closeness between a feature and a program component which is very useful for software programmers and maintainers to better understand the system at hand.