A formal approach for change impact analysis of long term composed services using Probabilistic Cellular Automata

Incorporating changes into the logics of composed services dynamically and successfully is a challenge for sustaining a business’ image and profit in the society, especially when the change is expected to be made immediately at low cost. In this paper, we address this challenge by proposing a change impact analysis framework for long term composed services (LCS) which: (i) enables the business people to implement the changes by themselves through their analysts, (ii) reduces cost and time by eliminating the dependence on IT developers once the application services are developed and delivered, (iii) ensures effective incorporation of the changes made by using standard methodologies for evaluation – finite state automaton for verifying the runtime compatibilities and change evaluation and probabilistic cellular automaton for impact analysis and prediction. Through the evaluated probability measures and effective incident matching, the knowledge gained by the analyst over his service logics and the efficiency of incorporating changes are increased.