Assumption-Based Risk Identification Method (ARM) in Dynamic Service Provisioning

In this paper we consider service-oriented applications composed of component services provided by different, economically independent service providers. As in all composite applications, the component services are composed and configured to meet requirements for the composite application. However, in a field experiment of composite service-oriented applications wef found that, although the services as actually delivered by the service providers meet their requirements, there is still a mismatch across service providers due to unstated assumptions, and that this mismatch causes an incorrect composite application to be delivered to end-users. Identifying and analyzing these initially unstated assumptions turns requirements engineering for service-oriented applications into risk analysis. In this paper, we describe a field experiment with an experimental service-oriented homecare system, in which unexpected behavior of the system turned up unstated assumptions about the contributing service providers. We then present an assumptions-driven risk identification method that can help identifying these risks, and we show how we applied this method in the second iteration of the field experiment. The method adapts some techniques from problem frame diagrams to identify relevant assumptions on service providers. The method is informal, and takes the "view from nowhere" in that it does not result in a specification of the component services, but for every component service delivers a set of assumptions that the service must satisfy in order to contribute to the overall system requirements. We end the paper with a discussion of generalizability of this method.