Improving the reuse possibilities of the behavioral aspects of object-oriented domain models.

Reuse of domain models is often limited to the reuse of the structural aspects of the domain (e.g. by means of generic data models). In object-oriented models, reuse of dynamic aspects is achieved by reusing the methods of domain classes. Because in the object-oriented approach any behavior is attached to a class, it is impossible to reuse behavior without at the same time reusing the class. In addition, because of the message passing paradigm, object interaction must be specified as a method attached to one class which is invoked by another class. In this way object interaction is hidden in the behavioral aspects of classes. This makes object interaction schemas difficult to reuse and customize. The focus of this paper is on improving the reuse of object-oriented domain models. This is achieved by centering the behavioral aspects around the concept of business events.Model; Models;

Business rules based legacy system evolution towards service-oriented architecture.

Enterprises can be empowered to live up to the potential of becoming dynamic, agile and real-time. Service orientation is emerging from the amalgamation of a number of key business, technology and cultural developments. Three essential trends in particular are coming together to create a new revolutionary breed of enterprise, the service-oriented enterprise (SOE): (1) the continuous performance management of the enterprise; (2) the emergence of business process management; and (3) advances in the standards-based service-oriented infrastructures. This thesis focuses on this emerging three-layered architecture that builds on a service-oriented architecture framework, with a process layer that brings technology and business together, and a corporate performance layer that continually monitors and improves the performance indicators of global enterprises provides a novel framework for the business context in which to apply the important technical idea of service orientation and moves it from being an interesting tool for engineers to a vehicle for business managers to fundamentally improve their businesses

Semantic Component Selection Based on Non-Functional Requirements

Reusing existing software components in place of requiring the implementation of new components can reduce the complexity of the software development process. However, for a software component to be effectively identified and selected for reuse, we need a good understanding of both the functional and non-functional requirements of the component needed, and the components available. Functional requirements specify what a software component does and non-functional requirements specify how a software component achieves its goals. Non-functional requirements are typically complex, and difficult to both understand and effectively articulate. Requirements engineering provides a solution to easing this process, and involves performing the following reasoning steps: elicitation, analysis and description. However, the output of these steps is based on reasoning that requires manual, expensive and error-prone techniques. To solve such drawbacks, this thesis describes a framework that provides the necessary tools and techniques for automating reasoning including: an ontology for non-functional requirements as a conceptual model for reasoning; and a search algorithm that matches the best component according to the reasoning process outputs. To validate our framework, we develop an implementation that supports semantic search within a repository to locate matches based on a user query, validated with experimental findings on a repository consisting of 50 individual component descriptions. Our findings demonstrate the benefit obtained from using an ontology, by minimizing the cost and complexity of analysing non-functional requirements. Our algorithm is capable of running a complex query, for example, supporting 5 non-functional requirements with total 16 prerequisites against a repository of 1000 components can run in 1750 second. It would be impossible for a field expert to compute a complex query in this time frame.Thesis (MCompSc) -- University of Adelaide, School of Computer Science, 201