Abstract not found

Domain-specific modeling (DSM) assists subject matter experts in describing the essential characteristics of a problem in their domain. When a metamodel is lost, repositories of domain models can become orphaned from their defining metamodel. Within the purview of model-driven engineering, the ability to recover the design knowledge in a repository of legacy models is needed. In this paper we describe MARS, a semi-automatic grammar-centric system that leverages grammar inference techniques to solve the metamodel recovery problem. The paper also contains an applicative case study, as well as experimental results from the recovery of several metamodels in diverse domains.

{zhangj, gray} @ cis.uab.edu Model-Driven Software Engineering (MDSE) is gaining increased adoption in the development of computer-based systems, especially in the area of distributed real-time and embedded (DRE) domains. There is also potential to apply MDSE to assist in the evolution of large enterprise legacy systems. However, the state-of-the-art MDSE techniques still lack support for advanced processes and constructive methods involved within the context of the development and evolution of software systems. This paper outlines our position on what is needed to provide a generative approach to support legacy system evolution with MDSE. A prototype of the Model-Driven Program Transformation (MDPT) technique has been implemented to perform large scale adaptation of legacy source code from transformation rules that are driven by the evolving features of the corresponding domain models.

{zhangj, gray, liny} @ cis.uab.edu Design by Contract provides an effective principle to enable the construction of robust software by describing properties of a module using logical assertions. This paper presents a modeldriven approach for weaving assertion checking aspects into a large software system. The approach is based on a technique called two-level aspect weaving. At the top level, crosscutting assertions are weaved into a model by use of a model weaver. The second step of the weaving process occurs when the Model-Driven Program Transformation technique is applied to perform large-scale adaptation of the underlying source code from the contracts specified in the high-level models. The paper briefly presents a case study to illustrate the concept.

Abstract. Domain-specific modeling techniques are being adopted with more frequency in the engineering of computer based systems. In the presence of new stakeholder requirements, it is possible that a meta-model undergoes numerous changes during periods of evolution. There is a fundamental problem in maintaining the model interpreters in terms of such metamodel schema changes. This position paper outlines the technical challenges involved in providing evolution of model interpreters. The paper proposes an approach that is based on a mature program transformation engine to automate the evolution of interpreters in the presence of meta-schema changes. 1.

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

{gray, zhangj, roychous} @ cis.uab.edu This demonstration will feature overviews of the C-SAW and GenAWeave projects. The first half of the presentation will introduce the concept of two-level aspect weaving, which unites a model transformation tool with a program transformation engine. From models representing an avionics application, it will be shown how changes to model properties trigger corresponding adaptations to the related source code. The second half of the demonstration is focused on using a program transformation engine to perform the task of aspect weaving. In particular, several crosscutting concerns will be woven into an Object Pascal application.

A common task that is often needed in many software development tools is the capability to search the artifact that is being created in a flexible and efficient manner. However, this capability is typically absent in meta-programmable modeling tools, which can be a serious disadvantage as the size of a model increases. As a remedy, we introduce a method to search domain models using XPath -- a World Wide Web Consortium (W3C) standard that uses logical predicates to search an XML document. In this paper, an XPath search engine is described that traverses the internal representation of a modeling tool (rather than an XML document) and returns those model entities that match the XPath predicate expression.

Evolution of design methodologies follows a common trail: technology scaling leads to growing design complexity and rising abstraction level in the domain. Introduction of new (higher) abstraction levels emphasizes the importance of reuse and transformations. The design process can be seen as a sequence of high-level transformations from the higher-level specification to the lower-level one. We analyze high-level modeling and metaprogramming techniques for

Grammar Inference is the process of learning a grammar from examples, either positive (i.e., the grammar generates the string) and/or negative (i.e., the grammar does not generate the string). Although grammar inference has been successfully applied to many diverse domains such as speech recognition and robotics, its application to software engineering has been limited. This research investigates the applicability of grammar inference to software engineering and programming language development challenge problems, where grammar inference offers an innovative solution to the problem, while remaining tractable and within the scope of that problem. Specifically, the following challenges are addressed in this research: 1. Recovery of a metamodel from instance models: Within the area of domain-specific modeling (DSM), instance models may evolve independently of the original metamodel resulting in metamodel drift, an inconsistency between the instance model and the associated metamodel such that the instance model may no longer be loaded