Domain Specific Languages

NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence

Abstract: The need to handle increasingly larger data volumes is one factor driving the adoption of a new class of nonrelational NoSQL databases. Advocates of NoSQL databases claim they can be used to build systems that are more performant, scale better, and are easier to program. NoSQL Distilled is a concise but thorough introduction to this rapidly emerging technology. Pramod J. Sadalage and Martin Fowler explain how NoSQL databases work and the ways that they may be a superior alternative to a traditional RDBMS. The authors provide a fast-paced guide to the concepts you need to know in order to evaluate whether NoSQL databases are right for your needs and, if so, which technologies you should explore further. The first part of the book concentrates on core concepts, including schemaless data models, aggregates, new distribution models, the CAP theorem, and map-reduce. In the second part, the authors explore architectural and design issues associated with implementing NoSQL. They also present realistic use cases that demonstrate NoSQL databases at work and feature representative examples using Riak, MongoDB, Cassandra, and Neo4j. In addition, by drawing on Pramod Sadalages pioneering work, NoSQL Distilled shows how to implement evolutionary design with schema migration: an essential technique for applying NoSQL databases. The book concludes by describing how NoSQL is ushering in a new age of Polyglot Persistence, where multiple data-storage worlds coexist, and architects can choose the technology best optimized for each type of data access.

Xtext: implement your language faster than the quick and dirty way

Abstract: Whether there is an (emerging or legacy) Domain-Specific Language to increase the expressiveness of your coworkers or whether you are about to invent a new General Purpose Prgramming Language: Tool support that goes beyond a parser/compiler is essential to make other people adopt your language and to be more productive. Xtext is an award- winning framework to build such tooling.In this tutorial we explain how to define a language and a statically typed, EMF-based Abstract Syntax Tree using only a grammar. We then generate a parser, a serializer and a smart editor from it. The editor provides many features out-of-the-box, such as syntax highlighting, content-assist, folding, jump-to-declaration and reverse-reference lookup across multiple files. Then, it is shown how literally every as- pects of the language and its complementary tool support can be customized using Dependency Injection, especially how this can be done for linking, formatting and validation. As an outlook, we will demonstrate how to integrate a custom language with Java, how Xtext maintains a workspace-wide index of named elements and how to implement incremental code generation or attach an interpreter.

Plenary talk III Domain-specific languages

Abstract: Computer science is undergoing a revolution today, in which language designers are shifting attention from general purpose programming languages to so-called domain-specific languages (DSLs). General-purpose languages like Java, C#, C++, and C have long been the primary focus of language research. The idea was to create one language that would be better suited for programming than any other language. Ironically, we now have so many different general purpose languages that it is hard to imagine how this goal could be attained. Instead of aiming to be the best for solving any kind of computing problem, DSLs aim to be particularly good for solving a specific class of problems, and in doing so they are often much more accessible to the general public than traditional programming languages.

FAMILIAR: A domain-specific language for large scale management of feature models

Abstract: The feature model formalism has become the de facto standard for managing variability in software product lines (SPLs). In practice, developing an SPL can involve modeling a large number of features representing different viewpoints, sub-systems or concerns of the software system. This activity is generally tedious and error-prone. In this article, we present FAMILIAR a Domain-Specific Language (DSL) that is dedicated to the large scale management of feature models and that complements existing tool support. The language provides a powerful support for separating concerns in feature modeling, through the provision of composition and decomposition operators, reasoning facilities and scripting capabilities with modularization mechanisms. We illustrate how an SPL consisting of medical imaging services can be practically managed using reusable FAMILIAR scripts that implement reasoning mechanisms. We also report on various usages and applications of FAMILIAR and its operators, to demonstrate their applicability to different domains and use for different purposes.

Domain-specific languages: an annotated bibliography

Abstract: We survey the literature available on the topic of domain-specific languages as used for the construction and maintenance of software systems. We list a selection of 75 key publications in the area, and provide a summary for each of the papers. Moreover, we discuss terminology, risks and benefits, example domain-specific languages, design methodologies, and implementation techniques.

Domain-specific languages

Abstract: Designed as a wide-ranging guide to Domain Specific Languages (DSLs) and how to approach building them, this book covers a variety of different techniques available for DSLs. The goal is to provide readers with enough information to make an informed choice about whether or not to use a DSL and what kinds of DSL techniques to employ. Part I is a 150-page narrative overview that gives you a broad understanding of general principles. The reference material in Parts II through VI provides the details and examples you willneed to get started using the various techniques discussed. Both internal and external DSL topics are covered, in addition to alternative computational models and code generation. Although the general principles and patterns presented can be used with whatever programming language you happen to be using, most of the examples are in Java or C#.