Domain-specific languages as key tools for ULSSIS engineering

We briefly discuss the potential of domain-specific languages and domain-specific modeling languages for ULSSIS engineering, some of the scaling challenges involved, and the possibilities for raising expressiveness beyond current levels

Domain-specific languages in perspective

Domain-specific languages (DSLs) are languages tailored to a specific application domain. They offer substantial gains in expressiveness and ease of use compared with general-purpose languages in their domain of application. Although the use of DSLs is by no means new, it is receiving increased attention in the context of model-driven engineering and development of parallel software for multicore processors. We discuss these trends from the perspective of the roles DSLs have traditionally played

When and how to develop domain-specific languages

Domain-specific languages (DSLs) are languages tailored to a specific application domain. They offer substantial gains in expressiveness and ease of use compared with general purpose programming languages in their domain of application. DSL development is hard, requiring both domain knowledge and language development expertise. Few people have both. Not surprisingly, the decision to develop a DSL is often postponed indefinitely, if considered at all, and most DSLs never get beyond the application library stage. While many articles have been written on the development of particular DSLs, there is very limited literature on DSL development methodologies and many questions remain regarding when and how to develop a DSL. To aid the DSL developer, we identify patterns in the decision, analysis, design, and implementation phases of DSL development. Our patterns try to improve on and extend earlier work on DSL design patterns, in particular by Spinellis (2001). We also discuss domain analysis tools and language development systems that may help to speed up DSL development. Finally, we state a number of open problems

MATURE: A Model Driven bAsed Tool to Automatically Generate a langUage That suppoRts CMMI Process Areas spEcification

Many companies have achieved a higher quality in their processes by using CMMI. Process definition may be efficiently supported by software tools. A higher automation level will make process improvement and assessment activities easier to be adapted to customer needs. At present, automation of CMMI is based on tools that support practice definition in a textual way. These tools are often enhanced spreadsheets. In this paper, following the Model Driven Development paradigm (MDD), a tool that supports automatic generation of a language that can be used to specify process areas practices is presented. The generation is performed from a metamodel that represents CMMI. This tool, differently from others available, can be customized according to user needs. Guidelines to specify the CMMI metamodel are also provided. The paper also shows how this approach can support other assessment method

Domain-specific languages as key tools for ulssis engineering

We briefly discuss the potential of domain-specific languages and domain-specific modeling languages for ULSSIS engineering, some of the scaling challenges involved, and the possibilities for raising expressiveness beyond current levels

SIGMA: Scala Internal Domain-Specific Languages for Model Manipulations

International audienceModel manipulation environments automate model operations such as model consistency checking and model transformation. A number of external model manipulation Domain-Specific Languages (DSL) have been proposed, in particular for the Eclipse Modeling Framework (EMF). While their higher levels of abstraction result in gains in expressiveness over general-purpose languages, their limitations in versatility, performance, and tool support together with the need to learn new languages may significantly contribute to accidental complexities. In this paper, we present Sigma, a family of internal DSLs embedded in Scala for EMF model consistency checking, model-to-model and model-to-text transformations. It combines the benefits of external model manipulation DSLs with general-purpose programming taking full advantage of Scala versatility, performance and tool support. The DSLs are compared to the state-of-the-art Epsilon languages in non-trivial model manipulation tasks that resulted in 20% to 70% reduction in code size and significantly better performance

Engaging End-Users in the Collaborative Development of Domain-Speci c Modelling Languages

International audienceDomain-Speci c Modelling Languages (DSMLs) are high-level languages specially designed to perform tasks in a particular domain. When developing DSMLs, the participation of end-users is normally limited to providing domain knowledge and testing the resulting language prototypes. Language developers, which are perhaps not domain experts, are therefore in control of the language development and evolution. This may cause misinterpretations which hamper the development process and the quality of the DSML. Thus, it would be bene cial to promote a more active participation of end-users in the development process of DSMLs. While current DSML workbenches are mono-user and designed for technical experts, we present a process and tool support for the example-driven, collaborative construction of DSMLs in order to engage end-users in the creation of their own languages

Domain Specific Languages for Managing Feature Models: Advances and Challenges

International audienceManaging multiple and complex feature models is a tedious and error-prone activity in software product line engineering. Despite many advances in formal methods and analysis techniques, the supporting tools and APIs are not easily usable together, nor unified. In this paper, we report on the development and evolution of the Familiar Domain-Specific Language (DSL). Its toolset is dedicated to the large scale management of feature models through a good support for separating concerns, composing feature models and scripting manipulations. We overview various applications of Familiar and discuss both advantages and identified drawbacks. We then devise salient challenges to improve such DSL support in the near future