Domain-specific language compilers need to close the gap between the domain abstractions of the language and the low-level concepts of the target platform.This can be challenging to achieve for compilers targeting multiple platforms with potentially very different computing paradigms.In this paper, we present a multi-target, multi-paradigm DSL compiler for algorithmic graph processing. Our approach centers around an intermediate representation and reusable, composable transformations to be shared between the different compiler targets. These transformations embrace abstractions that align closely with the concepts of a particular target platform, and disallow abstractions that are semantically more distant. We report on our experience implementing the compiler and highlight some of the challenges and requirements for applying language workbenches in industrial use cases.

In previous work, we introduced scope graphs as a formalism for describing program binding structure and performing name resolution in an AST-independent way. In this paper, we show how to use scope graphs to build static semantic analyzers. We use constraints extracted from the AST to specify facts about binding, typing, and initialization. We treat name and type resolution as separate building blocks, but our approach can handle language constructs---such as record field access---for which binding and typing are mutually dependent. We also refine and extend our previous scope graph theory to address practical concerns including ambiguity checking and support for a wider range of scope relationships. We describe the details of constraint generation for a model language that illustrates many of the interesting static analysis issues associated with modules and records.

Conducting analytics over data generated by Social Web portals such as Twitter is challenging, due to the volume, variety and velocity of the data. Commonly, adhoc pipelines are used that solve a particular use case. In this paper, we generalize across a range of typical Twitter-data use cases and determine a set of common characteristics. Based on this investigation, we present our Twitter Analytical Platform (TAP), a generic platform for conducting analytical tasks with Twitter data. The platform provides a domain-specific Twitter Analysis Language (TAL) as the interface to its functionality stack. TAL includes a set of analysis tools ranging from data collection and semantic enrichment, to machine learning. With these tools, it becomes possible to create and customize analytical workflows in TAL and build applications that make use of the analytics results. We showcase the applicability of our platform by building Twinder-a search engine for Twitter streams.

WebDSL is a domain-specific language for the implementation of dynamic web applications with a rich data model. It provides developers with object-oriented data modeling concepts but abstracts over implementation details for persisting application data in relational databases. When the underlying data model of an application evolves, persisted application data has to be migrated. While implementing migration at the database level breaks the abstractions provided by WebDSL, an implementation at the data model level requires to intermingle migration with application code. In this paper, we present a domain-specific language for the coupled evolution of data models and application data. It allows to specify data model evolution as a separate concern at the data model level and can be compiled to migration code at the database level. Its linguistic integration with WebDSL enables static checks for evolution validity and correctness.

Syntax definitions are pervasive in modern software systems, and serve as the basis for language processing tools like parsers and compilers. Mainstream parser generators pose restrictions on syntax definitions that follow from their implementation algorithm. They hamper evolution, maintainability, and compositionality of syntax definitions. The pureness and declarativity of syntax definitions is lost. We analyze how these problems arise for different aspects of syntax definitions, discuss their consequences for language engineers, and show how the pure and declarative nature of syntax definitions can be regained.