Zipper-based attribute grammars and their extensions

Lecture Notes in Computer Science Volume 8129, 2013.Attribute grammars are a suitable formalism to express complex software language analysis and manipulation algorithms, which rely on multiple traversals of the underlying syntax tree. Recently, Attribute Grammars have been extended with mechanisms such as references and high-order and circular attributes. Such extensions provide a powerful modular mechanism and allow the specification of complex fix-point computations. This paper defines an elegant and simple, zipper-based embedding of attribute grammars and their extensions as first class citizens. In this setting, language specifications are defined as a set of independent, off-the-shelf components that can easily be composed into a powerful, executable language processor. Several real examples of language specification and processing programs have been implemented in this setting

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

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

Type-Oriented Island Parsing

This thesis addresses the problem of specifying and parsing the syntax of domain-specific languages (DSLs) in a modular, user-friendly way. That is, we want to enable the design of composable DSLs that combine the natural syntax of external DSLs with the easy implementation of internal DSLs. The challenge in parsing composable DSLs is that the composition of several (individually unambiguous) languages is likely to contain ambiguities. In this thesis, we present the design of a system that uses a type-oriented variant of island parsing to efficiently parse the syntax of composable DSLs. In particular, we show that type-oriented island parsing is the first parsing algorithm that is constant time with respect to the number of DSLs imported. We also show how to use our tool to implement DSLs on top of a host language such as Typed Racket

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

Scala-Virtualized: Linguistic Reuse for Deep Embeddings

Scala-Virtualized extends the Scala language to better support hosting embedded DSLs. Scala is an expressive language that provides a flexible syntax, type-level computation using implicits, and other features that facilitate the development of em- bedded DSLs. However, many of these features work well only for shallow embeddings, i.e. DSLs which are implemented as plain libraries. Shallow embeddings automatically profit from features of the host language through linguistic reuse: any DSL expression is just as a regular Scala expression. But in many cases, directly executing DSL programs within the host language is not enough and deep embeddings are needed, which reify DSL programs into a data structure representation that can be analyzed, optimized, or further translated. For deep embeddings, linguistic reuse is no longer automatic. Scala-Virtualized defines many of the language’s built-in constructs as method calls, which enables DSLs to redefine the built-in semantics using familiar language mechanisms like overloading and overriding. This in turn enables an easier progression from shallow to deep embeddings, as core language constructs such as conditionals or pattern matching can be redefined to build a reified representation of the operation itself. While this facility brings shallow, syntactic, reuse to deep embeddings, we also present examples of what we call deep linguistic reuse: combining shallow and deep components in a single DSL in such a way that certain features are fully implemented in the shallow embedding part and do not need to be reified at the deep embedding level

Lightweight Modular Staging and Embedded Compilers:Abstraction without Regret for High-Level High-Performance Programming

Programs expressed in a high-level programming language need to be translated to a low-level machine dialect for execution. This translation is usually accomplished by a compiler, which is able to translate any legal program to equivalent low-level code. But for individual source programs, automatic translation does not always deliver good results: Software engineering practice demands generalization and abstraction, whereas high performance demands specialization and concretization. These goals are at odds, and compilers can only rarely translate expressive high-level programs tomodern hardware platforms in a way that makes best use of the available resources. Explicit program generation is a promising alternative to fully automatic translation. Instead of writing down the program and relying on a compiler for translation, developers write a program generator, which produces a specialized, efficient, low-level program as its output. However, developing high-quality program generators requires a very large effort that is often hard to amortize. In this thesis, we propose a hybrid design: Integrate compilers into programs so that programs can take control of the translation process, but rely on libraries of common compiler functionality for help. We present Lightweight Modular Staging (LMS), a generative programming approach that lowers the development effort significantly. LMS combines program generator logic with the generated code in a single program, using only types to distinguish the two stages of execution. Through extensive use of component technology, LMS makes a reusable and extensible compiler framework available at the library level, allowing programmers to tightly integrate domain-specific abstractions and optimizations into the generation process, with common generic optimizations provided by the framework. Compared to previous work on programgeneration, a key aspect of our design is the use of staging not only as a front-end, but also as a way to implement internal compiler passes and optimizations, many of which can be combined into powerful joint simplification passes. LMS is well suited to develop embedded domain specific languages (DSLs) and has been used to develop powerful performance-oriented DSLs for demanding domains such as machine learning, with code generation for heterogeneous platforms including GPUs. LMS has also been used to generate SQL for embedded database queries and JavaScript for web applications