Model-Driven Program Transformation of a Large Avionics Framework
Model-driven approaches to software development, when coupled with a domain-specific visual language, assist in capturing the essence of a large system in a notation that is familiar to a domain expert. From a high-level domain-specific model, it is possible to describe concisely the configuration features that a system must possess, in addition to checking that the model preserves semantic properties of the domain. With respect to large legacy applications written in disparate programming languages, the primary problem of transformation is the difficulty of adapting the legacy source to match the evolving features specified in the corresponding model. This paper presents an approach for uniting model-driven development with a mature program transformation engine. The paper describes a technique for performing widespread adaptation of source code from transformation rules that are generated from a domain-specific modeling environment for a large avionics framework.

title: Business Process-Oriented Software Architecture for Supporting Business Process Change
abstract: As a business process is essential in running an enterprise, this paper aims toward improving software architecture by extracting business-relevant semantics from business logic and transforming them as important elements that need to be molded and represented in software architecture. This allows for the development of a business process-oriented software architecture (BPOSA) that can support smoother business process change. The paper introduces the structure of BPOSA and its work mode. Then it describes the steps involved in designing a process-oriented software system, and provides analysis and design methods of extending process-relevant attributes for application in business operations.

title: A Composition-Oriented Approach for Business Process Formal Design
abstract: Traditional approaches to designing business processes are often inadequate for complicated, distributed, and collaborated settings. However since network technologies have become widespread, an increasing number of business processes exhibit these properties. Therefore a new approach is needed. To this end, we describe the motivation, conceptualization, and analysis of a composition-oriented business process design method. The key advance of our method is that it uses process algebra pi-calculus as its formal basis and builds a complex process by composing simple structured process control modules to reduce the complexity of business process design as well as let several designers collaborate the design of a complex process. To make business process more clear, we also provide way of separating exception processing logic from normal process control logic and provide scooping mechanisms to minimize the detrimental effects of unplanned contingencies by ways of composition

title: Model replication: transformations to address model scalability
abstract: 2 SUMMARY In Model-Driven Engineering, it is often desirable to evaluate different design alternatives as they relate to scalability issues of the modeled system. A typical approach to address scalability is model replication, which starts by creating base models that capture the key entities as model elements and their relationships as model connections. A collection of base models can be adorned with necessary information to characterize a specific scalability concern as it relates to how the base modeling elements are replicated and connected together. In current modeling practice, such model replication is usually accomplished by scaling the base model manually. This is a time-consuming process that represents a source of error, especially when there are deep interactions between model components. As an alternative to the manual process, this paper presents the idea of automated model replication through a model transformation process that expands the number of elements from the base model and makes the correct connections among the generated modeling elements. The paper motivates the need for model replication through case studies taken from models supporting different domains.

title: Automating change evolution in model-driven engineering
abstract: The escalating complexity of software and system models is making it difficult to rapidly explore the effects of a design decision. Automating such exploration with model transformation and aspect-oriented techniques can improve both productivity and model quality. The combination of model transformation and aspect weaving provides a powerful technology for rapidly transforming legacy systems from the high-level properties that models describe. Further, by applying aspect-oriented techniques and program transformation, small changes at the modeling level can trigger very large transformations at the source code level. Thus, model engineers can explore alternative configurations using an aspect weaver targeted for modeling tools and then use the models to generate program transformation rules for adapting legacy source code on a wide scale.

title: Aspect mining from a modelling perspective
abstract: Aspect mining aims at identifying, analysing, and refactoring crosscutting concerns throughout a legacy system for the purpose of improving software modularisation. This paper presents our investigation into raising the benefits of aspect mining to high level domain-specific models. A key contribution is the capability to identify crosscutting concerns early in development, which will assist in the modularisation of a design through aspects, before proceeding to the implementation level. Furthermore, our experience has led us to believe that aspects are easier to identify at the modelling level, because much of the accidental complexities of implementation concerns are not present in the corresponding modelling abstractions.

title: Transforming Natural Arguments in Araucaria to Formal Arguments in LMA
abstract: Over the last few years, argumentation has been gaining increasing importance in multi-agent systems research. LMA is a Logic of multiple-valued argumentation built on top of EALP (extended annotated logic programming). Araucaria is a software tool for analyzing and diagramming arguments written in natural language. We integrate these two systems involved in argumentation to an easy to use and more user-friendly argumentation system, in which natural arguments can be transformed into formal arguments, in order to lighten users' knowledge burden forced by formal argumentation frameworks, and attain extensive usability of formal argumentation systems. We illustrate the transformation process by translating natural arguments in English to formal arguments in EALP step-by-step, and then how the status of those formal arguments can be determined in LMA, resulting in the status determination of original natural arguments.

title: Image Mining: Issues, Frameworks and Techniques
abstract: Advances in image acquisition and storage technology have led to tremendous growth in significantly large and detailed image databases. These images, if analyzed, can reveal useful information to the human users. Image mining deals with the extraction of implicit knowledge, image data relationship, or other patterns not explicitly stored in the images. Image mining is more than just an extension of data mining to image domain. It is an interdisciplinary endeavor that draws upon expertise in computer vision, image processing, image retrieval, data mining, machine learning, database, and artificial intelligence. Despite the development of many applications and algorithms in the individual research fields cited above, research in image mining is still in its infancy. In this paper, we will examine the research issues in image mining, current developments in image mining, particularly, image mining frameworks, state-of-the-art techniques and systems. We will also identify some future research directions for image mining at the end of this paper.

title: Towards Re-engineering Legacy Systems for Assured Dynamic Adaptation
abstract: Increasingly, software must adapt its behavior in response to changes in the supporting computing, communication infrastructure, and in the surrounding physical environment. Since most existing software was not designed to adapt, research on technique to make legacy software dynamically adaptive has gained increasing interest. Assurance is crucial for adaptive software to fulfill its intended purpose. Correctness is even more critical if it is to be applied in high assurance systems. This paper proposes a model-driven approach to introduce dynamic adaptation to non-adaptive legacy systems while maintaining assurance properties. An aspect-oriented technique is applied to achieve separation of concerns in the implementation.

title: Model-Driven Adaptive Self-healing for Autonomic Computing
abstract: Self-healing is a vital property that an autonomic system must possess in order to provide robust performance and survivability. The promise of self-healing depends on other properties that the system should provide, which include self-monitoring and self-configuring. Autonomic systems further require self-healing behavior to adapt to changes in user needs, business goals, and environmental conditions such that self-healing decisions are made dynamically and adaptively according to the system context. In this paper, we propose a model-driven approach that leverages modeling techniques, reliability engineering methodologies, and aspect-oriented development to realize an adaptive self- healing paradigm for autonomic computing.

title: Service Quality Evaluation for Brand Retailers Based on Fuzzy Comprehensive Appraisal
abstract: Evaluation of service quality is becoming more important in the field of retailers, as in other fields. This pilot study is a preliminary attempt to develop an evaluation model by using Exploratory Factor Analysis (EFA), Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Appraisal (FCA). And then it addresses issues associated with determining the service quality in a retail store environment based on this model. Firstly, by summarizing the dynamic situation of service quality evaluation, a factor structure for Retail Service Quality (RSQ) using EFA is proposed, which consists of prestige, reliability, responsiveness, recovery and tangibles. Secondly, Owing to the characteristic of retail service, this article applies AHP and membership function to determine the weight of criteria and hierarchical structure. And then FCA is used to evaluate the service quality of brand retail stores. Finally, an example is shown to illustrate above method.