Graph-based implicit knowledge discovery from architecture change logs

Service architectures continuously evolve as a consequence of frequent business and technical change cycles. Architec- ture change log data represents a source of evolution-centric information in terms of intent, scope and operationalisation to accommodate changing requirements in existing architec- ture. We investigate change logs in order to analyse op- erational 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 archi- tecture elements. We exploit graph matching as a knowl- edge discovery technique in order to i) analyse change op- erationalisation and its dependencies for ii) discovering re- current change sequences in the log. We identify potentially reusable, usage-determined change patterns.