SEIM: Static Inference of Interaction Models

The quality of systems that integrate Web services provided by independent organizations depends on the ways the systems interact with the services, i.e., on their interaction protocols, which are not always easy to deduce by inspecting the code. Accurate models of interaction protocols provide a comprehensive view of the interactions, and support manual and automatic analysis of corner cases that are often difficult to discover, and are responsible from many subtle failures. Models of program behavior can be extracted either statically from the source code or dynamically from execution traces. Dynamic techniques cannot reveal behaviors that have not been executed, and thus dynamic models are partially useful to identify critical corner cases. Static techniques produce models of the whole execution space, and thus static models are more useful to find critical cases. Most static techniques to extract models of the code behavior focus on the usage protocol, i.e., how the services can be used, rather than the interaction protocol, i.e., how applications use services. While usage protocols can help software engineers understanding the service behavior, interaction protocols describe the subset of actual interactions between the system and the integrated services, and provide the information required to understand critical interactions. In this paper, we present SEIM, a technique to extract models of the service interaction protocol. SEIM extracts models statically, and includes a novel refinement strategy to eliminate infeasible behaviors that reduce the usability of statically derived models. This paper describes the technique and provides some empirical data from the early experience of SEIM with an application that interacts with the eBay Web Services. © 2010 ACM.