Graph-based implicit knowledge discovery from architecture change logs
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Service architectures continuously evolve as a consequence of frequent business and technical change cycles. Architecture change log data represents a source of evolution-centric information in terms of intent, scope and operationalisation to accommodate changing requirements in existing architecture. We investigate change logs in order to analyse operational representation of architecture change instances to discover an implicit evolution-centric knowledge that have been aggregating over time. Change instances from the log are formalised as a typed attributed graph with its node and edge attribution capturing change representation on architecture elements. We exploit graph matching as a knowledge discovery technique in order to i) analyse change operationalisation and its dependencies for ii) discovering recurrent change sequences in the log. We identify potentially reusable, usage-determined change patterns.