Title :
Supporting Feature-Level Software Maintenance
Author_Institution :
Comput. Sci. Dept., Coll. of William & Mary, Williamsburg, VA, USA
Abstract :
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.
Keywords :
software maintenance; software metrics; dynamic source; evaluation strategies; feature coupling metrics; feature-level impact analysis; feature-level software maintenance; source code; static source; textual source; Area measurement; Computer bugs; Computer science; Educational institutions; Information analysis; Information resources; Performance analysis; Reverse engineering; Scattering; Software maintenance; data fusion; feature coupling; feature location;
Conference_Titel :
Reverse Engineering, 2009. WCRE '09. 16th Working Conference on
Conference_Location :
Lille
Print_ISBN :
978-0-7695-3867-9
DOI :
10.1109/WCRE.2009.43
