Many domain-specific languages, that try to bring feasible alternatives for existing solutions while simplifying programming work, have come up in recent years. Although, these little languages seem to be easy to use, there is an open issue whether they bring advantages in comparison to the application libraries, which are the most commonly used implementation approach. In this work, we present an experiment, which was carried out to compare such a domain-specific language with a comparable application library. The experiment was conducted with 36 programmers, who have answered a questionnaire on both implementation approaches. The questionnaire is more than 100 pages long. For a domain-specific language and the application library, the same problem domain has been used - construction of graphical user interfaces. In terms of a domain-specific language, XAML has been used and C# Forms for the application library. A cognitive dimension framework has been used for a comparison between XAML and C# Forms.
Domain-specific languages (DSLs) are often argued to have a simpler notation than general-purpose languages (GPLs), since the notation is adapted to the specific problem domain. Consequently, the impact of domain relevance on the creation of the problem representation is believed to improve programmers' efficiency and accuracy when using DSLs compared with using similar solutions like application libraries in GPLs. Most of the common beliefs have been based upon qualitative conclusions drawn by developers. Rather than implementing the same problem in a DSL and in a GPL and comparing the efficiency and accuracy of each approach, developers often compare the implementation of a new program in a DSL to their previous experiences implementing similar programs in GPLs. Such a conclusion may or may not be valid. This paper takes a more skeptical approach to acceptance of those beliefs. By reporting on a family of three empirical studies comparing DSLs and GPLs in different domains. The results of the studies showed that when using a DSL, developers are more accurate and more efficient in program comprehension than when using a GPL. These results validate some of the longThis work was partially sponsored by the bilateral project "Program Comprehension for Domain-Specific Languages" (code BI-PT/08-09-008) between Slovenia and Portugal.Empir Software Eng (2012) 17:276-304 277 held beliefs of the DSL community that until now were only supported by anecdotal evidence.
The study of Multiagent Systems (MASs) focuses on those systems in which many intelligent agents interact with each other. The agents are considered to be autonomous entities which contain intelligence that serves for solving their selfish or common problems, and to achieve certain goals. However, the autonomous, responsive, and proactive natures of agents make the development of agent-based software systems more complex than other software systems. Furthermore, the design and implementation of a MAS may become even more complex and difficult to implement when considering new requirements and interactions for new agent environments like the Semantic Web. We believe that both domain-specific modeling and the use of a domain-specific modeling language (DSML) may provide the required abstraction, and hence support a more fruitful methodology for the development of MASs. In this paper, we first introduce a DSML for MASs with both its syntax and semantics definitions and then show how the language and its graphical tools can be used during model-driven development of real MASs. In addition to the classical viewpoints of a MAS, the proposed DSML includes new viewpoints which specifically support the development of software agents working within the Semantic Web environment. The practical use of the DSML is exemplified with a case study on the development of an agentbased expert finding system.
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