Software Language Engineering with XMF and XModeler

XMF and XModeler are presented as technologies that have been specifically designed for Software Language Engineering. XMF provides a meta-circular, extensible platform for DSL definition based on syntax-classes that extend object-oriented classes with composable grammars. XModeler is a development environment built on top of XMF that provides an extensible client-based architecture for developing DSL tools.

Inviting Citizen Designers to Design Digital Interface for the Democratization of Web Online Environments

Web online environments are supposed to create unifying spaces where diverse societies, cultures and linguistics as well as literacies and knowledge associated with them merge together as negotiated in neutral space. However, these online environments are not culturally neutral or innocent communication landscapes. They may alienate the users from marginal/periphery social, cultural, and linguistic background and experience because of their disregard to their social, cultural, and linguistics norms and values in the digital contact zone. Acknowledging the social, cultural, and linguistic limitations of these technologies that aim to provide agency to their users in this chapter, this chapter proposes to invite citizen designers to design the interface of web online environment in general and Learning Management Systems (LMS) in particular because this process can transform online environments into democratic platforms. Citizen designers, who have democratic sentiments for the creation of a just society, are composition students in general and students with periphery cultural and linguistic experience in particular. Doing a cultural usability test of Blackboard 8, the author argues that current web interface design is not democratic and inclusive, and proposes to invite citizen designers to re/design interface of online environments for their democratization so that they would include people from different cultural and linguistic backgrounds and enhance writing students' writing powers.

Intelligent Business Decision-Making in Global Organizations via Fuzzy Reasoning Systems

Companies, organizations, governmental departments, and universities need to adopt globalization patterns for their generative survival in dynamic productive outputs. Such outputs are possible only after effective, rational, logical, and systematic treatment of all available input knowledge and information. These inputs mostly have imprecision, uncertainty, vagueness, incompleteness, and missing parts, which together provide a fuzzy arena where an expert is confronted with decision making under a set of conflicting and mutually inclusive vague alternatives. Any uncertain ingredient may be considered as a set of linguistic adjectives attached to the input and output variables so as to refine them into meaningful and less uncertain sub-sets. Logical propositions that combine each sub-set of any input variable to suitable sub-sets of other variables through logical ANDing connectives as precedents are related to a specific sub-set of output as consequent, which constitute fundamental logical rule. These are expert reflections towards management problem solving. The combination of such rules with logical ORing connectives presents linguistically the holistic decision structure of any management system. This chapter presents the essential steps required to achieve decision making under uncertainty for effective management via a fuzzy logic inference system. The basis of fuzzy logic modeling is presented which may be used by different business management experts.

Formal Semantics for Metamodel-Based Domain Specific Languages

Domain Specific Languages (DSLs) are often defined in terms of metamodels capturing the abstract syntax of the language. For a complete definition of a DSL, both syntactic and semantic aspects of the language have to be specified. Metamodeling environments support syntactic definition issues, but they do not provide any help in defining the semantics of metamodels, which is usually given in natural language. In this chapter, the authors present an approach to formally define the semantics of metamodel-based languages. It is based on a translational technique that hooks to the language metamodel its precise and executable semantics expressed in terms of the Abstract State Machine formal method. The chapter also shows how different techniques can be used for formal analysis of models (i.e., instance of the language metamodel). The authors exemplify the use of their approach on a language for Petri nets.

A Customizable Language Learning Support System Using Ontology-Driven Engine

This article proposes a framework for web-based language learning support systems designed to provide customizable pedagogical procedures based on the analysis of characteristics of both learner and course. This framework employs a course-centered ontology and a teaching method ontology as the foundation for the student model, which includes learner knowledge status and learning preferences. A prototype system has been developed based on this framework. The system was evaluated by means of analysis of learner data from the international language department of a Chinese university. The average learning achievement of the students in the experimental group, who studied with the learning support system, was significantly better than that of the control group, who studied with the tradition learning management system while taking the same Japanese course as the experimental group.

Design Patterns and Design Principles for Internal Domain-Specific Languages

Internal DSLs are a special kind of DSLs that use an existing programming language as their host. To build them successfully, knowledge regarding how to modify the host language is essential. In this chapter, the author contributes six DSL design principles and 21 DSL design patterns. DSL Design principles provide guidelines that identify specific design goals to shape the syntax and semantic of a DSL. DSL design patterns express proven knowledge about recurring DSL design challenges, their solution, and their connection to each other – forming a rich vocabulary that developers can use to explain a DSL design and share their knowledge. The chapter presents design patterns grouped into foundation patterns (which provide the skeleton of the DSL consisting of objects and methods), notation patterns (which address syntactic variations of host language expressions), and abstraction patterns (which provide the domain-specific abstractions as extensions or even modifications of the host language semantics).

Technology-Mediated Tasks in English for Specific Purposes (ESP)

Although many researchers have focused their attention on task-based language teaching (TBLT) in recent years, there is little published research on TBLT in technology-mediated contexts, and on how to design and implement tasks in online settings. In addition, very little can be found in the literature about learner perception of technology-mediated tasks in these new virtual learning environments. The objective of this paper is to bridge these gaps by reporting on the design, implementation and learner perception of English For Biologists (EFB), an online module based on tasks and aimed at French biology students enrolled on a first year Master's degree programme. The principles underlying the design of EFB (a combination of three action-based approaches) as well as its implementation (tutor mediation in particular) are presented in this paper. This article also offers insight in the learners' perception of task-based language learning through the analysis of the answers they gave to a post-course online questionnaire. Overall, technology-mediated task reception was positive but learner feedback enabled to uncover specific problems, notably regarding the type of support provided.

Kansei Evaluation of Product Recommendation Based on a Partial Comparison Process

This paper aims to find a new evaluation method for collecting Kansei and Context data, which is based on a partial comparison process; and a specification method based on customer's target, which is suitable for the special Kansei and Context data obtained from partial comparison process. For collecting Kansei and Context data, we randomly select 5 objects from all objects, and ask people to compare them on each attribute. After many times comparisons, many comparison lists will be obtained. With these lists, we map them into a directed graphic, and with using some graphic processing techniques, we combine all the comparison lists into a whole list without any contradictions, and we map the whole list into a certain range as our evaluated data. To access these special Kansei and Context data, we also discussed two specification methods based on semantic differential method. To test the new method on collecting Kansei data and the specification method, a comparison system and a recommendation system are developed.

Classifying Consumer Comparison Opinions to Uncover Product Strengths and Weaknesses

With the Web 2.0 paradigm, a huge volume of Web content is generated by users at online forums, wikis, blogs, and social networks, among others. These user-contributed contents include numerous user opinions regarding products, services, or political issues. Among these user opinions, certain comparison opinions exist, reflecting customer preferences. Mining comparison opinions is useful as these types of viewpoints can bring more business values than other types of opinion data. Manufacturers can better understand relative product strengths or weaknesses, and accordingly develop better products to meet consumer requirements. Meanwhile, consumers can make purchasing decisions that are more informed by comparing the various features of similar products. In this paper, a novel Support Vector Machine-based method is proposed to automatically identify comparison opinions, extract comparison relations, and display results with the comparison relation maps by mining the volume of consumer opinions posted on the Web. The proposed method is empirically evaluated based on consumer opinions crawled from the Web. The initial experimental results show that the performance of the proposed method is promising and this research opens the door to utilizing these comparison opinions for business intelligence.

Abstraction of Computer Language Patterns

In general, designing a domain-specific language (DSL) is a complicated process, requiring the cooperation of experts from both application domain and computer language development areas. One of the problems that may occur is a communication gap between a domain expert and a language engineer. Since domain experts are usually non-technical people, it might be difficult for them to express requirements on a DSL notation in a technical manner. Another compelling problem is that even though the majority of DSLs share the same notation style for representing the common language constructs, a language engineer has to formulate the specification for these constructs repeatedly for each new DSL being designed. The authors propose an innovative concept of computer language patterns to capture the well-known recurring notation style often seen in many computer languages. To address the communication problem, they aim for the way of proposing a DSL notation by providing program examples as they would have been written in a desired DSL. As a combination of these two ideas, the chapter presents a method for example-driven DSL notation specification (EDNS), which utilizes computer language patterns for semi-automated inference of a DSL notation specification from the provided program examples.