Typing in Model Management

International audienceModel management is essential for coping with the complexity introduced by the increasing number and varied nature of artifacts involved in MDE-based projects. Global Model Management (GMM) addresses this issue enabling the representation of artifacts, particularly transformation composition and execution, by a model called a megamodel. Typing information about artifacts can be used for preventing type errors during execution. In this work, we present a type system for GMM that improves its current typing approach and enables formal reasoning about the type of artifacts within a megamodel. This type system is able to capture non-trivial situations such as the use of higher order transformations

Using Model Types to Support Contract-Aware Model Substitutability

International audienceModel typing brings the benefit associated with well-defined type systems to model-driven development (MDD) through the assignment of specific types to models. In particular, model type systems enable reuse of model manipulation operations (e.g., model transformations), where manipulations defined for models of a supertype can be used to manipulate models of subtypes. Existing model typing approaches are limited to structural typing defined in terms of object-oriented metamodels (e.g., MOF) in which the only structural (well-formedness) constraints are those that can be expressed directly in metamodeling notations (e.g., multiplicity and element containment constraints). In this paper we describe an extension to model typing that takes into consideration structural invariants, other than those that can be expressed directly in metamodeling notation, and specifications of behaviors associated with model types. The approach supports contract-aware substitutability, where contracts are defined in terms of invariants and pre-/postconditions expressed using OCL. Support for behavioral typing paves the way for behavioral substitutability. We also describe a technique to rigorously reason about model type substitutability as supported by contracts and apply the technique in use cases from the optimizing compiler community

Generator-Composition for Aspect-Oriented Domain-Specific Languages

Software systems are complex, as they must cover a diverse set of requirements describing functionality and the environment. Software engineering addresses this complexity with Model-Driven Engineering ( MDE ). MDE utilizes different models and metamodels to specify views and aspects of a software system. Subsequently, these models must be transformed into code and other artifacts, which is performed by generators. Information systems and embedded systems are often used over decades. Over time, they must be modified and extended to fulfill new and changed requirements. These alterations can be triggered by the modeling domain and by technology changes in both the platform and programming languages. In MDE these alterations result in changes of syntax and semantics of metamodels, and subsequently of generator implementations. In MDE, generators can become complex software applications. Their complexity depends on the semantics of source and target metamodels, and the number of involved metamodels. Changes to metamodels and their semantics require generator modifications and can cause architecture and code degradation. This can result in errors in the generator, which have a negative effect on development costs and time. Furthermore, these errors can reduce quality and increase costs in projects utilizing the generator. Therefore, we propose the generator construction and evolution approach GECO, which supports decoupling of generator components and their modularization. GECO comprises three contributions: (a) a method for metamodel partitioning into views, aspects, and base models together with partitioning along semantic boundaries, (b) a generator composition approach utilizing megamodel patterns for generator fragments, which are generators depending on only one source and one target metamodel, (c) an approach to modularize fragments along metamodel semantics and fragment functionality. All three contributions together support modularization and evolvability of generators

Towards Language-Oriented Modeling

In this habilitation à diriger des recherches (HDR), I review a decade of research work in the fields of Model-Driven Engineering (MDE) and Software Language Engineering (SLE). I propose contributions to support a language-oriented modeling, with the particular focus on enabling early validation & verification (V&V) of software-intensive systems. I first present foundational concepts and engineering facilities which help to capture the core domain knowledge into the various heterogeneous concerns of DSMLs (aka. metamodeling in the small), with a particular focus on executable DSMLs to automate the development of dynamic V&V tools. Then, I propose structural and behavioral DSML interfaces, and associated composition operators to reuse and integrate multiple DSMLs (aka. metamodeling in the large).In these research activities I explore various breakthroughs in terms of modularity and reusability of DSMLs. I also propose an original approach which bridges the gap between the concurrency theory and the algorithm theory, to integrate a formal concurrency model into the execution semantics of DSMLs. All the contributions have been implemented in software platforms — the language workbench Melange and the GEMOC studio – and experienced in real-world case studies to assess their validity. In this context, I also founded the GEMOC initiative, an attempt to federate the community on the grand challenge of the globalization of modeling languages

Safely Reusing Model Transformations through Family Polymorphism

International audienceThe 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. In this talk we explore various dimensions of these challenges, and outline a possible research roadmap for addressing them. We detail one of these challenges, which is the safe reuse of model transformations.Indeed both DSL definition and tooling (e.g., checkers, document or code generators, model transformations) require significant development efforts, for a limited audience (by definition), because the current state of the art of Model Driven Engineering still makes it hard to reuse and evolve these definitions and tooling across several DSLs, even when these DSLs are conceptually very close to one other. We outline a new extension to the Kermeta language that leverages Family Polymorphism to allow model polymorphism, inheritance among DSLs, as well as evolution and interoperability of DSLs

When Systems Engineering Meets Software Language Engineering

International audienceThe 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. This paper explores various dimensions of these challenges, and outlines a possible research roadmap for addressing them. The message of this paper is also to claim that if language engineering techniques to design any single (disposable) language are mature, the language engineering community needs to fundamentally change its view on software language design. We need to take the next step and adopt the perspective that a software language is, fundamentally, software too and thus the result of a composition of design decisions. These design decisions should be represented as first-class entities in the software languages workbench and it should be possible, during the language lifecycle, to add, remove and change language design decisions with limited effort to go from continuous design to continuous meta-design

Facet-oriented Modelling

© ACM 2021. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Transactions on Software Engineering and Methodology, http://dx.doi.org/10.1145/10.1145/3428076Models are the central assets in model-driven engineering (MDE), as they are actively used in all phases of software development. Models are built using metamodel-based languages, and so objects in models are typed by a metamodel class. This typing is static, established at creation time, and cannot be changed later. Therefore, objects in MDE are closed and fixed with respect to the class they conform to, the fields they have, and the well-formedness constraints they must comply with. This hampers many MDE activities, like the reuse of model-related artefacts such as transformations, the opportunistic or dynamic combination of metamodels, or the dynamic reconfiguration of models. To alleviate this rigidity, we propose making model objects open so that they can acquire or drop so-called facets. These contribute with a type, fields and constraints to the objects holding them. Facets are defined by regular metamodels, hence being a lightweight extension of standard metamodelling. Facet metamodels may declare usage interfaces, as well as laws that govern the assignment of facets to objects (or classes). This article describes our proposal, reporting on a theory, analysis techniques, and an implementation. The benefits of the approach are validated on the basis of five case studies dealing with annotation models, transformation reuse, multi-view modelling, multi-level modelling, and language product linesWork partially funded by the R&D programme of the Madrid Region (project FORTE, S2018/TCS-4314) and the Spanish Ministry of Science (project MASSIVE, RTI2018-095255-B-I00