A UML/OCL framework for the analysis of fraph transformation rules

In this paper we present an approach for the analysis of graph transformation rules based on an intermediate OCL representation. We translate different rule semantics into OCL, together with the properties of interest (like rule applicability, conflicts or independence). The intermediate representation serves three purposes: (i) it allows the seamless integration of graph transformation rules with the MOF and OCL standards, and enables taking the meta-model and its OCL constraints (i.e. well-formedness rules) into account when verifying the correctness of the rules; (ii) it permits the interoperability of graph transformation concepts with a number of standards-based model-driven development tools; and (iii) it makes available a plethora of OCL tools to actually perform the rule analysis. This approach is especially useful to analyse the operational semantics of Domain Specific Visual Languages. We have automated these ideas by providing designers with tools for the graphical specification and analysis of graph transformation rules, including a backannotation mechanism that presents the analysis results in terms of the original language notation

Modeling and Analysis of Software Product Line Variability in Clafer

Both feature and class modeling are used in Software Product Line (SPL) engineering to model variability. Feature models are used primarily to represent user-visible characteristics (i.e., features) of products; whereas class models are often used to model types of components and connectors in a product-line architecture. Previous works have explored the approach of using a single language to express both configurations of features and components. Their goal was to simplify the definition and analysis of feature-to-component mappings and to allow modeling component options as features. A prominent example of this approach is cardinality-based feature modeling, which extends feature models with multiple instantiation and references to express component-like, replicated features. Another example is to support feature modeling in a class modeling language, such as UML or MOF, using their profiling mechanisms and a stylized use of composition. Both examples have notable drawbacks: cardinality-based feature modeling lacks a constraint language and a well-defined semantics; encoding feature models as class models and their evolution bring extra complexity. This dissertation presents Clafer (class, feature, reference), a class modeling language with first-class support for feature modeling. Clafer can express rich structural models augmented with complex constraints, i.e., domain, variability, component models, and meta-models. Clafer supports: (i) class-based meta-models, (ii) object models (with uncertainty, if needed), (iii) feature models with attributes and multiple instantiation, (iv) configurations of feature models, (v) mixtures of meta- and feature models and model templates, and (vi) first-order logic constraints. Clafer also makes it possible to arrange models into multiple specialization and extension layers via constraints and inheritance. On the other hand, in designing Clafer we wanted to create a language that builds upon as few concepts as possible, and is easy to learn. The language is supported by tools for SPL verification and optimization. We propose to unify basic modeling constructs into a single concept, called clafer. In other words, Clafer is not a hybrid language. We identify several key mechanisms allowing a class modeling language to express feature models concisely. We provide Clafer with a formal semantics built in a novel, structurally explicit way. As Clafer subsumes cardinality-based feature modeling with attributes, references, and constraints, we are the first to precisely define semantics of such models. We also explore the notion of partial instantiation that allows for modeling with uncertainty and variability. We show that Object-Oriented Modeling (OOM) languages with no direct support for partial instances can support them via class modeling, using subclassing and strengthening multiplicity constraints. We make the encoding of partial instances via subclassing precise and general. Clafer uses this encoding and pushes the idea even further: it provides a syntactic unification of types and (partial) instances via subclassing and redefinition. We evaluate Clafer analytically and experimentally. The analytical evaluation shows that Clafer can concisely express feature and meta-models via a uniform syntax and unified semantics. The experimental evaluation shows that: 1) Clafer can express a variety of realistic rich structural models with complex constraints, such as variability models, meta-models, model templates, and domain models; and 2) that useful analyses can be performed within seconds

Compilation of Heterogeneous Models: Motivations and Challenges

International audienceThe widespread use of model driven engineering in the development of software-intensive systems, including high-integrity embedded systems, gave rise to a "Tower of Babel" of modeling languages. System architects may use languages such as OMG SysML and MARTE, SAE AADL or EAST-ADL; control and command engineers tend to use graphical tools such as MathWorks Simulink/Stateflow or Esterel Technologies SCADE, or textual languages such as MathWorks Embedded Matlab; software engineers usually rely on OMG UML; and, of course, many in-house domain specific languages are equally used at any step of the development process. This heterogeneity of modeling formalisms raises several questions on the verification and code generation for systems described using heterogeneous models: How can we ensure consistency across multiple modeling views? How can we generate code, which is optimized with respect to multiple modeling views? How can we ensure model-level verification is consistent with the run-time behavior of the generated executable application?In this position paper we describe the motivations and challenges of analysis and code generation from heterogeneous models when intra-view consistency, optimization and safety are major concerns. We will then introduce Project P 2 and Hi-MoCo 3-respectively FUI and Eurostars-funded collaborative projects tackling the challenges above. This work continues and extends, in a wider context, the work carried out by the Gene-Auto 4 project [1], [2]. Hereby we will present the key elements of Project P and Hi-MoCo, in particular: (i) the philosophy for the identification of safe and minimal practical subsets of input modeling languages; (ii) the overall architecture of the toolsets, the supported analysis techniques and the target languages for code generation; and finally, (iii) the approach to cross-domain qualification for an open-source, community-driven toolset

Mapping UML models incorporating OCL constraints into object-Z

Focusing on object-oriented designs, this paper proposes a mapping for translating systems modelled in the Unified Modelling Language (UML) incorporating Object Constraint Language (OCL) constraints into formal software specifications in Object-Z. Joint treatment of semi-formal model constructs and constraints within a single translation framework and conversion tool is novel, and leads to the generation of much richer formal specifications than is otherwise possible. This paper complements previous analyses by paying particular attention to the generation of complete Object-Z structures. Integration of proposals to extend the OCL to include action constraints also boosts the expressivity of the translated specifications. The main features of a tool support are described

A Systematic Approach to Constructing Incremental Topology Control Algorithms Using Graph Transformation

Communication networks form the backbone of our society. Topology control algorithms optimize the topology of such communication networks. Due to the importance of communication networks, a topology control algorithm should guarantee certain required consistency properties (e.g., connectivity of the topology), while achieving desired optimization properties (e.g., a bounded number of neighbors). Real-world topologies are dynamic (e.g., because nodes join, leave, or move within the network), which requires topology control algorithms to operate in an incremental way, i.e., based on the recently introduced modifications of a topology. Visual programming and specification languages are a proven means for specifying the structure as well as consistency and optimization properties of topologies. In this paper, we present a novel methodology, based on a visual graph transformation and graph constraint language, for developing incremental topology control algorithms that are guaranteed to fulfill a set of specified consistency and optimization constraints. More specifically, we model the possible modifications of a topology control algorithm and the environment using graph transformation rules, and we describe consistency and optimization properties using graph constraints. On this basis, we apply and extend a well-known constructive approach to derive refined graph transformation rules that preserve these graph constraints. We apply our methodology to re-engineer an established topology control algorithm, kTC, and evaluate it in a network simulation study to show the practical applicability of our approachComment: This document corresponds to the accepted manuscript of the referenced journal articl

An invariant-based method for the analysis of declarative model-to-model transformations

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-540-87875-9_3Proceedings of 11th International Conference, MoDELS 2008, Toulouse, France, September 28 - October 3, 2008In this paper we propose a method to derive OCL invariants from declarative specifications of model-to-model transformations. In particular we consider two of the most prominent approaches for specifying such transformations: Triple Graph Grammars and QVT. Once the specification is expressed in the form of invariants, the transformation developer can use such description to verify properties of the original transformation (e.g. whether it defines a total, surjective or injective function), and to validate the transformation by the automatic generation of valid pairs of source and target models.Work supported by the Spanish Ministry of Education and Science, projects MOSAIC (TSI2005-08225-C07-06), MODUWEB (TIN2006-09678) and TIN2005-06053, and an UOC-IN3 research gran