Integrated Development Environments (IDEs) are evolving towards cloud-native applications with the aim to relocate the language services provided by an IDE on distant servers. Existing research works focus on the overall migration process to handle more efficiently their specific requirements. However, the microservicization of legacy monolithic applications is still highly dependent on the specific properties of the application of interest. In this paper, we report our experiment on the microservicization process of the Cloud-Based graphical modeling workbench Sirius Web.
To cope with the ever-growing number of programming languages, manufacturers of Integrated Development Environments (IDE) have recently defined protocols as a way to use and share multiple language services (e.g., auto-completion, type checker, language runtime) in language-agnostic environments (i.e., the user interface provided by the IDE): the most notable are the Language Server Protocol (LSP) for textual editors, and the Debug Adapter Protocol (DAP) for debugging facilities. These protocols rely on a proper specification of the services that are commonly found in the tool support of general-purpose languages, and define a fixed set of capabilities to offer in the IDE.
Read-eval-print-loops (REPLs) allow programmers to test out snippets of code, explore APIs, or even incrementally construct code, and get immediate feedback on their actions. However, even though many languages provide a REPL, the relation between the language as is and what is accepted at the REPL prompt is not always well-defined. Furthermore, implementing a REPL for new languages, such as DSLs, may incur significant language engineering cost. In this paper we survey the domain of REPLs and investigate the (formal) principles underlying REPLs.
Modeling is requiring increasingly larger efforts while becoming indispensable given the complexity of the problems we are solving. Modelers face high cognitive load to understand a multitude of complex abstractions and their relationships. There is an urgent need to better support tool builders to ultimately provide modelers with intelligent modeling assistance that learns from previous modeling experiences, automatically derives modeling knowledge, and provides context-aware assistance. However, current Intelligent Modeling Assistants (IMAs) lack adaptability and flexibility for tool builders, and do not facilitate understanding the differences and commonalities of IMAs for modelers.
Runtime monitoring is a fundamental technique used throughout the lifecycle of a system for many purposes, such as debugging, testing, or live analytics. While runtime monitoring for general purpose programming languages has seen a great amount of research, developing such complex facilities for any executable Domain Specific Language (DSL) remains a challenging, reoccurring and error prone task. A generic solution must both support a wide range of executable DSLs (xDSLs) and induce as little execution time overhead as possible.
The adoption of Domain-Specific Languages (DSLs) relies on the capacity of language workbenches to automate the development of advanced and customized environments. While DSLs are usually well tailored for the main scenarios, the cost of developing mature tools prevents the ability to develop additional capabilities for alternative scenarios targeting specific tasks (e.g., API testing) or stakeholders (e.g., education). In this paper, we propose an approach to automatically generate interactive computer programming environments from existing specifications of textual interpreted DSLs.