Variability Modeling and Meta-Modeling for Model-Driven Service-Oriented Architectures

Abstract

Service Oriented Architecture (SOA) has emerged as an architectural style for distributed computing that promotes flexible application development and reuse. One of the major benefits claimed for SOA is the flexible building of IT solutions that can react to changing business requirements quickly and economically. Services could be consumed by many applications that have different requirements. In addition, applications usually change by adding new requirements, removing existing requirements, or updating existing requirements. Thus, applications that consume the same service usually exhibit varying requirements. Varying requirements usually necessitate varying software architectures that satisfy the varying requirements of software applications. Thus, both requirements and architectures have intrinsic variability characteristics. SOA development practices currently lack a systematic approach for managing variability in service requirements and architectures. This dissertation addresses this gap by applying software product line (SPL) concepts to model SOA systems as service families. The dissertation introduces an approach to model SOA variability with a multiple-view service variability model and a corresponding meta-model. The approach integrates SPL concepts of feature modeling and commonality/variability analysis with multiple service requirements and architectural views by using UML and the Service Oriented Architecture Modeling Language (SoaML). At the heart of this research is a multiple-view meta-model that defines the relationships among variable service views and maps features to variable service models along with a corresponding consistency checking rules that ensure the consistency of the multiple service views as they change. The dissertation describes how to derive family member applications from the SPL and presents a validation of the approach. This dissertation makes the case that the presented multiple-view service variability modeling and meta-modeling approach facilitates variability modeling of service families in a systematic and platform independent way. The key contributions of this research include: Multiple-View Service Variability Meta- Model, Multiple-View Service Variability Model, Consistency Checking and Mapping Rules, Model Driven Framework for Service Oriented SPL Engineering, Service Member Applications Derivation Rules, Explicit Modeling of Service Coordination Variability, and a Proof-of-Concept Tool Prototype.S