Title :
Reconstructing Architectural Views from Legacy Systems
Author :
Boussaidi, G.E. ; Belle, Alvine Boaye ; Vaucher, Stéphane ; Mili, Hafedh
Author_Institution :
Dept. of Software & IT Eng., Ecole de Technol. Super., Montreal, QC, Canada
Abstract :
Modernizing a large legacy system is a demanding and costly process which requires a deep understanding of the system´s architecture and its components. However legacy systems are poorly documented and they have often undergone many changes that make them deviate from their initial architectural design. Approaches for reconstructing architectural views from legacy systems and re-documenting the resulting components are of great value in the context of a modernization process. In this paper, we propose an approach that helps constructing distinct architectural views from legacy systems. To do so, we propose various clustering algorithms which are driven by common architectural views and styles. Our approach makes use of the knowledge discovery model which provides a standard machine-independent representation of legacy systems. We implemented and applied the approach in an industrial setting. The preliminary experimentations have shown that the algorithms perform well and produce comprehensive views.
Keywords :
data mining; pattern clustering; software architecture; software maintenance; architectural design; architectural view reconstruction; clustering algorithms; component redocumentation; knowledge discovery model; legacy systems; standard machine-independent representation; Aging; Clustering algorithms; Computer architecture; Partitioning algorithms; Software; Software algorithms; Standards; architectural views; architecture reconstruction; legacy system modernization; software clustering;
Conference_Titel :
Reverse Engineering (WCRE), 2012 19th Working Conference on
Conference_Location :
Kingston, ON
Print_ISBN :
978-1-4673-4536-1
DOI :
10.1109/WCRE.2012.44