Section: New Results

Results on Software Language Engineering

The engineering of systems involves many different stakeholders, each with their own domain of expertise. Hence more and more organizations are adopting Domain Specific Languages (DSLs) to allow domain experts to express solutions directly in terms of relevant domain concepts. This new trend raises new challenges about designing DSLs, evolving a set of DSLs and coordinating the use of multiple DSLs for both DSL designers and DSL users. In [56] we present the overall vision that we develop in the DiverSE team about Software Language Engineering. The main results on this topic are presented below.

Globalization of Domain Specific Languages

In the software and systems modeling community, research on domain-specific modeling languages (DSMLs) focuses on technologies for developing languages and tools to increase the effectiveness of domain experts. Yet, there is a lack of support to explicitly relate concepts expressed in different DSMLs, which prevents software and system engineers to reason about information spread across models describing different system aspects. Supporting coordinated use of DSMLs leads to what we call the globalization of modeling languages [20] . In such a context, we develop a research initiative that broadens the DSML research focus beyond the development of independent DSMLs to one that supports globalized DSMLs, that is, DSMLs that facilitate coordination of work across different domains of expertise. We also provid a formal framework to prove the correctness of model driven engineering composition operators [57] .

Meta-Language for the Concurrency Concern in DSLs

Concurrency is of primary interest in the development of complex software-intensive systems, as well as the deployment on modern platforms. However, reifying the definition of the DSL concurrency remains a challenge. This hinders: a) the development of a complete understanding of the DSL semantics; b) the effectiveness of concurrency-aware analysis techniques; c) the analysis of the deployment on parallel architectures. In this context, we present MoCCML, a dedicated meta-language for formally specifying the concurrency concern within the definition of a DSL [44] . The concurrency constraints can reflect the knowledge in a particular domain, but also the constraints of a particular platform. MoCCML comes with a complete language workbench to help a DSL designer in the definition of the concurrency directly within the concepts of theDSL itself, and a generic workbench to simulate and analyze any model conforming to this DSL. Mo CCML is illustrated on the definition of an lightweight extension of SDF (SynchronousData Flow).

Automating Variability Model Inference for Component-Based Language Implementations

Componentized language frameworks, coupled with variability modeling, have the potential to bring language development to the masses, by simplifying the configuration of a new language from an existing set of reusable components. However, designing variability models for this purpose requires not only a good understanding of these frameworks and the way components interact, but also an adequate familiarity with the problem domain. In [68] we propose an approach to automatically infer a relevant variability model from a collection of already implemented language components, given a structured, but general representation of the domain. We describe techniques to assist users in achieving a better understanding of the relationships between language components, and find out which languages can be derived from them with respect to the given domain.

Metamorphic Domain-Specific Languages

External or internal domain-specific languages (DSLs) or (fluent) APIs? Whoever you are – a developer or a user of a DSL – you usually have to choose side; you should not! What about metamorphic DSLs that change their shape according to your needs? Our 4-years journey of providing the "right" support (in the domain of feature modeling), led us to develop an external DSL, different shapes of an internal API, and maintain all these languages. A key insight is that there is no one-size-fits-all solution or no clear superiority of a solution compared to another. On the contrary, we found that it does make sense to continue the maintenance of an external and internal DSL. Based on our experience and on an analysis of the DSL engineering field, the vision that we foresee for the future of software languages is their ability to be self-adaptable to the most appropriate shape (including the corresponding integrated development environment) according to a particular usage or task. We call metamorphic DSL such a language, able to change from one shape to another shape [27] .

Adapting mutation testing for model transformations

Due to the specificities of models and transformations, classical software testing techniques have to be adapted. Among these techniques, mutation analysis has been ported and a set of mutation operators has been defined. However, mutation analysis currently requires a considerable manual work and is hampered by the test data set improvement activity. This activity is seen by testers as a difficult and time-consuming job, and reduces the benefits of the mutation analysis.

We provide a model transformation traceability mechanism, in conjunction with a model of mutation operators and a dedicated algorithm, to automatically or semi-automatically produce test models that detect new faults [18] .

Efficient model cloning for analysis

We propose an original approach that exploits the fact that operations rarely modify a whole model. Given a set of immutable properties, our cloning approach determines the objects and fields that can be shared between the runtime representations of a model and its clones. Our generic cloning algorithm is parameterized with three strategies that establish a trade-off between memory savings and the ease of clone manipulation. We evaluated memory footprints and computation overheads with 100 randomly generated metamodels and models [40] . We have also drawn the research roadmap to exploit these efficient clone operations to analyze multidimensional execution traces [41] .