Developing editing support for L languages in E editors is complex and time-consuming. Some languages do not provide dedicated editors, while others offer a single native editor. The language server protocol (LSP) reduces the language-editor combinations L × E to L + E , where a single language server communicates with editors via LSP plugins. However, overlapping implementations of linguistic components remain an issue. Existing language workbenches struggle with modularity, reusability, and leveraging type systems for language server generation. In this work, we propose: (i) Typelang, a family of domain-specific languages for modular, composable, and reusable type system implementation, (ii) a modular language server generation process, producing servers for languages built in a modular workbench, (iii) the variant-oriented programming paradigm and a cross-artifact coordination layer to manage interdependent software variants, and (iv) an LSP plugin generator, reducing E to 1 by automating plugin creation for multiple editors. To simplify editing support for language families, each language artifact integrates its own Typelang variant, used to generate language servers. This reduces combinations to T × 1 , where T = L represents the number of type systems. Further reuse of language artifacts across languages lowers this to N × 1 , where N < < T , representing unique type systems. We implement Typelang in Neverlang, generating language servers for each artifact and LSP plugins for three editors. Empirical evaluation shows a 93.48% reduction in characters needed for type system implementation and 100% automation of LSP plugin generation, significantly lowering effort for editing support in language families, especially when artifacts are reused.

Compilers pose significant challenges in their development as software products. Language developers face the complexities of ensuring efficiency, adhering to good design practices, and maintaining the overall codebase. These factors make it difficult to predict the unexpected impact of updates on existing software built on the current compiler stack. Furthermore, software created for a specific compiler often lacks reusability for other compiler environments. In this study, we propose a comprehensive framework for the uniform development of compilers that addresses these issues. Our approach involves developing compilers as a collection of small transpilation units, referred to as deltas. The transpilation infrastructure takes source code written in a particular source language and searches for a path of deltas to generate equivalent source code in the target language. By adopting this methodology, language developers can easily update their languages by introducing new deltas into the system. Existing code remains unaffected as old transpilation paths remain available. To support this framework, we have devised a metric space for efficient delta search. This metric space enables us to define a non-overestimating heuristic function, which proves valuable in solving the search problem. Leveraging the A* search algorithm, we can efficiently transpile programs from a source language to the target language. To evaluate the effectiveness of our approach, we conducted a benchmark comparison between the A* search algorithm and the simpler breadth-first search (BFS) algorithm. The benchmark consisted of over 100 transpilation searches, providing valuable insights into the performance and capabilities of this framework.

Legacy software poses a critical challenge for organizations due to the costs of maintaining and modernizing outdated systems, as well as the scarcity of experts in aging programming languages. The issue extends beyond commercial applications, affecting public administration, as exemplified by the urgent need for COBOL programmers during the COVID-19 pandemic. In response, this work introduces a modernization approach based on dynamic language product lines, a subset of dynamic software product lines. This approach leverages open language implementations and dynamically generated micro-languages for the incremental migration of legacy systems to modern technologies. The language can be reconfigured at runtime to adapt to the execution of either legacy or modern code, and to generate a compatibility layer between the data types handled by the two languages. Through this process, the costs of modernizing legacy systems can be spread across several iterations, as developers can replace legacy code incrementally, with legacy and modern code coexisting until a complete refactoring is possible. By moving the overhead of making legacy and modern features work together in a hybrid system from the system implementation to the language implementation, the quality of the system itself does not degrade due to the introduction of glue code. To demonstrate the practical applicability of this approach, we present a case study on a COBOL system migration to Java. Using the Neverlang language workbench to create modular and reconfigurable language implementations, both the COBOL interpreter and the application evolve to spread the development effort across several iterations. Through this study, this work presents a viable solution for organizations dealing with the complexity of modernizing legacy software to contemporary technologies. The contributions of this work are (i) a language-oriented, incremental refactoring process for legacy systems, (ii) a concrete application of open language implementations, and (iii) a general template for the implementation of interoperability between languages in hybrid systems.

Language workbenches are tools that enable the definition, reuse and composition of programming languages and their ecosystem. This breed of frameworks aims to make the development of new languages easier and more affordable. Consequently, the comprehensibility of the language used in a language workbench (i.e., the meta-language) should be an important aspect to consider and evaluate. To the best of our knowledge, although the quantitative aspects of language workbenches are often discussed in the literature, the evaluation of comprehensibility is typically neglected.Neverlang is a language workbench that enables the definition of languages with a modular approach. This paper presents a preliminary study that intends to assess the comprehensibility of Neverlang programs, evaluated in terms of users’ effectiveness and efficiency in a code comprehension task. The study also investigates the relationship between Neverlang comprehensibility and the users’ working memory capacity. Furthermore, we intend to capture the relationship between Neverlang comprehensibility and users’ acceptance, in terms of perceived ease of use, perceived usefulness, and intention to use. Our preliminary results on 10 subjects suggest that the users’ working memory capacity may be related to the ability to comprehend Neverlang programs. On the other hand, effectiveness and efficiency do not appear to be associated with an increase in users’ acceptance variables.

The introduction of better abstractions is at the forefront of research and practice. Among many approaches, domain-specific languages are subject to an increase in popularity due to the need for easier, faster and more reliable application development that involves programmers and domain experts alike. To smooth the adoption of such a language-driven development process, researchers must create new engineering techniques for the development of programming languages and their ecosystems. Traditionally, programming languages are implemented from scratch and in a monolithic way. Conversely, modular and reusable language development solutions would improve maintainability, reusability and extensibility. Many programming languages share similarities that can be leveraged to reuse the same language feature implementations across several programming languages; recent language workbenches strive to achieve this goal by solving the language composition and language extension problems. Yet, some features are inherently complex and affect the behavior of several language features. Most notably, the exception handling mechanism involves varied aspects, such as the memory layout, variables, their scope, up to the execution of each statement that may cause an exceptional event—e.g., a division by zero. In this paper, we propose an approach to untangle the exception handling mechanism dubbed the exception handling layer: its components are modular and fully independent from one another, as well as from other language features. The exception handling layer is language-independent, customizable with regards to the memory layout and supports unconventional exception handling language features. To avoid any assumptions with regards to the host language, the exception handling layer is a stand-alone framework, decoupled from the exception handling mechanism offered by the back-end. Then, we present a full-fledged, generic Java implementation of the exception handling layer. The applicability of this approach is presented through a language evolution scenario based on a Neverlang implementation of JavaScript and LogLang, that we extend with conventional and unconventional exception handling language features using the exception handling layer, with limited impact on their original implementation.

Programming languages are complex software systems integrated across an ecosystem of different applications such as language compilers or interpreters but also an integrated development environment comprehensive of syntax highlighting, code completion, error recovery, and a debugger. The complexity of language ecosystems can be faced using language workbenches—i.e., tools that tackle the development of programming languages, domain specific languages and their ecosystems in a modular way. As with any other software system, one of the priorities that developers struggle to achieve when developing programming languages is reusability. After all, the capacity to easily reuse and adapt existing components to new scenarios can dramatically improve development times. Therefore, as programming languages offer features to reuse existing code, language workbenches should offer tools to reuse existing language assets. However, reusability can be achieved in many different ways. In this work, we identify six forms of linguistic reusability, ordered by level of granularity: (i) sub-languages composition, (ii) language features composition, (iii) syntax and semantics assets composition, (iv) semantic assets composition, (v) actions composition, and. (vi) action extension. We use these mechanisms to extend the taxonomy of language composition proposed by Erdweg et al. To show a concrete application of this taxonomy, we evaluate the capabilities provided by the Neverlang language workbench with regards to our taxonomy and extend it by adding explicit support for any granularity level that was originally not supported. This is done by instantiating two levels of reusability as actual operators—desugaring, and delegation. We evaluate these operators against the clone-and-own approach, which was the only form of reuse at that level of granularity prior to the introduction of explicit operators. We show that with the clone-and-own approach the design quality of the source code is negatively affected. We conclude that language workbenches can benefit from the introduction of mechanisms to explicitly support reuse at all granularity levels.

Software product lines (SPL) describe highly-variable software systems as a family of similar products that differ in terms of the features they provide. The promise of SPL engineering is to enable massive software reuse by allowing software features to be reused across a variety of different products made for several customers. However, there are some disadvantages in the extraction of SPLs from standard applications. Most notably, approaches to the development of SPLs are not supported by the base language and use a syntax and composition techniques that require a deep understanding of the tools being used. Therefore, the same features cannot be used in a different application and developers must face a steep learning curve when developing SPLs for the first time or when switching from one approach to a different one. Ultimately, this problem is due to a lack of standards in the area of SPL engineering and in the way SPLs are extracted from variability-unaware applications. In this work, we present a framework based on LSP and dubbed that aims at standardizing such a process by decoupling the refactoring operations made by the user from the effect they have on the source code. This way, the server for a specific SPL development approach can be used across several development environments that provide clients with customized refactoring options. Conversely, the developers can use the same client to refactor SPLs made according to different approaches without needing to learn the syntax of each approach. To showcase the applicability of the approach, we present an evaluation performed by refactoring four SPLs according to two different approaches: the results show that a minimal implementation of the client and server applications can be used to reduce the effort of extracting an SPL up to the 93% and that it can greatly reduce or even completely hide the implementation details from the developer, depending on the chosen approach.

Abstract 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.