Advisory Committee Chair
Jeffrey Gray
Advisory Committee Members
Barrett Bryant
Aniruddha Gokhale
Marjan Mernik
Changcui Zhang
Document Type
Dissertation
Date of Award
2007
Degree Name by School
Doctor of Philosophy (PhD) College of Arts and Sciences
Abstract
It is well-known that the inherent complex nature of software systems adds to the challenges of software development. The most notable techniques for addressing the complexity of software development are based on the principles of abstraction, problem decomposition, separation of concerns and automation. As an emerging paradigm for developing complex software, Model-Driven Engineering (MDE) realizes these principles by raising the specification of software to models, which are at a higher level of abstraction than source code. As models are elevated to first-class artifacts within the software development lifecycle, there is an increasing need for frequent model evolution to explore design alternatives and to address system adaptation issues. However, a system model often grows in size when representing a large-scale real-world system, which makes the task of evolving system models a manually intensive effort that can be very time consuming and error prone. Model transformation is a core activity of MDE, which converts one or more source models to one or more target models in order to change model structures or translate models to other software artifacts. The main goal of model transformation is to provide automation in MDE. To reduce the human effort associated with model evolution while minimizing potential errors, the research described in this dissertation has contributed toward a model transformation approach to automated model evolution. iv A pre-existing model transformation language, called the Embedded Constraint Language (ECL), has been evolved to specify tasks of model evolution, and a model transformation engine, called the Constraint-Specification Aspect Weaver (C-SAW), has been developed to perform model evolution tasks in an automated manner. Particularly, the model transformation approach described in this dissertation has been applied to the important issue of model scalability for exploring design alternatives and crosscutting modeling concerns for system adaptation. Another important issue of model evolution is improving the correctness of model transformation. However, there execution-based testing has not been considered for model transformation testing in current modeling practice. As another contribution of this research, a model transformation testing approach has been investigated to assist in determining the correctness of model transformations by providing a testing engine called M2MUnit to facilitate the execution of model transformation tests. The model transformation testing approach requires a new type of test oracle to compare the actual and expected transformed models. To address the model comparison problem, model differentiation algorithms have been designed and implemented in a tool called DSMDiff to compute the differences between models and visualize the detected model differences. The C-SAW transformation engine has been applied to support automated evolution of models on several different experimental platforms that represent various domains such as computational physics, middleware, and mission computing avionics. The research described in this dissertation contributes to the long-term goal of alleviating the increasing complexity of modeling large-scale, complex applications.
Recommended Citation
Lin, Yuehua, "A Model Transformation Approach To Automated Model Evolution" (2007). All ETDs from UAB. 3749.
https://digitalcommons.library.uab.edu/etd-collection/3749
