The proposed research defines data fusion approaches to support software maintenance tasks at the feature level. Static, dynamic, and textual sources of information are combined to locate the implementation of features in source code. Structural and textual source code information is used to define feature coupling metrics to aid feature-level impact analysis. This paper provides details on the proposed approaches and evaluation strategies as well as some preliminary results.