Authors:
Guenter Pirklbauer
1
and
Michael Rappl
2
Affiliations:
1
Software Competence Center Hagenberg, Austria
;
2
Oberoesterreichische Gebietskrankenkasse, Austria
Keyword(s):
Change Coupling Analysis, Change Impact Analysis, Data Warehouse, Dynamic Dependency Analysis, Software Maintenance.
Related
Ontology
Subjects/Areas/Topics:
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Legacy Systems
Abstract:
The costs for enhancing and maintaining software systems are up to 75% of the total development costs. It is therefore important to provide appropriate methods, techniques and tools for supporting the maintenance phase of the software life cycle. One major maintenance task is the analysis and validation of change impacts. Existing approaches address change impact analysis, but using them in practice raises specific problems. Tools for change impact analysis must be able to deal with analysis- and design-models which are not compliant with the released software system. These models are not a good basis to perform change impact analysis. The proposed approach combines methods of dynamic dependency analysis and change coupling analysis to detect physical and logical dependencies between software components. The goal is to detect low-level artefacts and dependencies based on only up-to-date and system-conform data, including logfiles, the service repository, the versioning system databas
e and the change management system database. The implementation of the approach supports both the management and developers.
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