This paper describes an environment for the architectural recovery of software systems called Architectural Recovery Tool (ART). The environment is based on a hierarchical architectural model that drives the application of a set of recognizers, each producing a different architectural view of a system or of some of its parts. Recognizers embody knowledge about architectural cliches and use flow analysis techniques to make their output more accurate.
To test the accuracy and effectiveness of ART, a suite of public domain applications containing interesting architectural organizations was selected as a benchmark. Results are presented by showing ART performance in terms of precision and recall of the architectural concept retrieval process.
The results obtained show that cliche' based architectural recovery is feasible and the recovered information can be a valuable support in reengineering and maintenance activities.