Neverlang 2 – Componentised Language Development for the JVM

Cazzola, Walter; Vacchi, Edoardo

doi:10.1007/978-3-642-39614-4_2

Cited by 22 publications

(21 citation statements)

References 21 publications

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“…The Neverlang [2,3] framework for DSL development promotes code reuse and sharing by making language units first-class concepts. In Neverlang, language components are developed as separate units that can be compiled and tested independently, enabling developers to share and reuse the same units across different language implementations.…”

Section: Neverlangmentioning

confidence: 99%

“…Semantic actions are performed with respect to the parse tree of the input program; roles are executed in the order specified in the roles clause of the language descriptor. For lack of space, we cannot not give an in-depth description of Neverlang's syntax; for a more detailed description, see [3].…”

Section: Neverlangmentioning

confidence: 99%

“…Thus, although componentized development is today the norm, even in the case of language development, complete language workbenches such as Xtext [9] or MPS [25] are usually top-down, end-to-end development tools that are meant for programmers, and therefore less suited for programming-illiterate users. Componentized language frameworks such as LISA [19], JastAdd [10], or Neverlang [2,3] support reuse of language components, but each component may have implicit dependencies on other parts, and often these dependencies are not managed automatically by the system, but are delegated to the developer.…”

Section: Introductionmentioning

confidence: 99%

“…The contribution of this work is an approach to apply variability modeling to component-based language development, that focuses on reuse of existing assets. In particular, we describe 1. a method to extract structured information from the set of existing assets in the form of a graph of dependencies, 2. a strategy to construct a variability model using the extracted information, 3. an implementation of a derivation operator to generate the language implementation from the VM automatically, thereby facilitating the collaboration between the language developer and the domain expert, to the extent that the domain expert becomes autonomous in extracting a desired language.…”

Section: Introductionmentioning

confidence: 99%

“…2 we provide some background in terms of a modular language implementation and variability modeling; in Sect. 3 we give an overview of the approach. In Sect 4 we describe the approach in detail starting with a set of components and in Sect.…”

Section: Introductionmentioning

confidence: 99%

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Variability Support in Domain-Specific Language Development

Vacchi¹,

Cazzola²,

Pillay³

et al. 2013

Software Language Engineering

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Abstract. Domain Specific Languages (DSLs) are widely adopted to capitalize on business domain experiences. Consequently, DSL development is becoming a recurring activity. Unfortunately, even though it has its benefits, language development is a complex and time-consuming task. Languages are commonly realized from scratch, even when they share some concepts and even though they could share bits of tool support. This cost can be reduced by employing modern modular programming techniques that foster code reuse. However, selecting and composing these modules is often only within the reach of a skilled DSL developer. In this paper we propose to combine modular language development and variability management, with the objective of capitalizing on existing assets. This approach explicitly models the dependencies between language components, thereby allowing a domain expert to configure a desired DSL, and automatically derive its implementation. The approach is tool supported, using Neverlang to implement language components, and the Common Variability Language (CVL) for managing the variability and automating the configuration. We will further illustrate our approach with the help of a case study, where we will implement a family of DSLs to describe state machines.

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Section: Neverlangmentioning

confidence: 99%

Section: Neverlangmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Variability Support in Domain-Specific Language Development

Vacchi¹,

Cazzola²,

Pillay³

et al. 2013

Software Language Engineering

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On the incremental growth and shrinkage of LR goto-graphs

Cazzola

Vacchi

2014

Acta Informatica

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The LR(0) goto-graph is the basis for the construction of parsers for several interesting grammar classes such as LALR and GLR. Early work has shown that even when a grammar is an extension to another, the goto-graph of the first is not necessarily a subgraph of the second. Some authors presented algorithms to grow and shrink these graphs incrementally, but the formal proof of the existence of a particular relation between a given goto-graph and a grown or shrunk counterpart seems to be still missing in literature as of today. In this paper we use the recursive projection of paths of limited length to prove the existence of one such relation, when the sets of productions are in a subset relation. We also use this relation to present two algorithms (GROW and SHRINK) that transform the goto-graph of a given grammar into the goto-graph of an extension or a restriction to that grammar. We implemented these algorithms in a dynamically updatable LALR parser generator called DEXTER (the Dynamically EXTEnsible Recognizer) that we are now shipping with our current implementation of the Neverlang framework for programming language development.

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Towards a recipe for language decomposition: quality assessment of language product lines

Cazzola

Favalli

2022

Empir Software Eng

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Programming languages are complex systems that are usually implemented as monolithic interpreters and compilers. In recent years, researchers and practitioners gained interest in product line engineering to improve the reusability of language assets and the management of variability-rich systems, introducing the notions of language workbenches and language product lines (LPLs). Nonetheless, language development remains a complex activity and design or implementation flaws can easily waste the efforts of decomposing a language specification into language features. Poorly designed language decompositions result in high inter-dependent components, reducing the variability space of the LPL system and its maintainability. One should detect and fix the design flaws posthaste to prevent these risks while minimizing the development overhead. Therefore, various aspects of the quality of a language decomposition should be quantitatively measurable through adequate metrics. The evaluation, analysis and feedback of these measures should be a primary part of the engineering process of a LPL. In this paper, we present an exploratory study trying to capture these aspects by introducing a design methodology for LPLs; we define the properties of a good language decomposition and adapt a set of metrics from the literature to the framework of language workbenches. Moreover, we leverage the LPL engineering environment to perform an empirical evaluation of 26 -based LPLs based on this design methodology. Our contributions form the foundations of a design methodology for -based LPLs. This methodology is comprised of four different elements: i) an engineering process that defines the order in which decisions are made, ii) an integrated development environment for LPL designers and iii) some best practices in the design of well-structured language decomposition when using , supported by iv) a variety of LPL metrics that can be used to detect errors in design decisions.

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Neverlang 2 – Componentised Language Development for the JVM

Cited by 22 publications

References 21 publications

Variability Support in Domain-Specific Language Development

Variability Support in Domain-Specific Language Development

On the incremental growth and shrinkage of LR goto-graphs

Towards a recipe for language decomposition: quality assessment of language product lines

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