A MDA Approach to Model & Implement Transformations

Only in software and in linguistics a model has the same nature as the thing it models. In software at least, this opens the possibility to automatically derive software from its model. This property is well known from any compiler writer (and others), but it was recently be made quite popular with an OMG initiative called the Model Driven Architecture (MDA). The model transformations allowing the engineers to more or less automatically go from platform-independent models (PIM) to platform-specific models (PSM) are increasingly seen as vital assets that must be managed with sound software engineering principles. We believe that transformations should be first-class models in the MDA world; we propose to adopt the object-oriented approach and to leverage the expressive power of UML as a metamodel defining the transformation language

Modeling of Secure and Dependable Applications Based on a Repository of Patterns: The SEMCO Approach

International audienceThe requirement for higher quality and seamless development of systems is continuously increasing, even in domains traditionally not deeply involved in such issues. Security and Dependability (S&D) requirements are incorporated to an increasing number of systems. These newer restrictions make the development of those systems more complicated than conventional systems. In our work, we promote a new approach called SEMCO (System and software Engineering with Multi-COncerns) combining Model-Driven Engineering (MDE) with a model-based repository of S&D patterns to support the design and the analysis of pattern-based secure and dependable system and software architectures. The modeling framework to support the approach is based on a set of modeling languages, to specify security and dependability patterns, resources and a set of property models, and a set of model transformation rules to specify some of the analysis activities. As part of the assistance for the development of S&D applications, we have implemented a tool-chain based on the Eclipse platform to support the different activities around the repository, including the analysis activities. The proposed approach was evaluated through a case study from the railway domain

Termination Criteria for Model Transformation

Nowadays the usage of model transformations in software engineering has become widespread. Considering current trends in software development such as model driven development (MDD), there is an emerging need to develop model manipulations such as model evolution and optimisation, semantics definition, etc. If a model transformation is described in a precise way, it can be analysed lateron. Models, especially visual models, can be described best by graphs, due to their multi-dimensional extension. Graphs can be manipulated by graph transformation in a rule-based manner. Thus, we specify model transformation by graph transformation. This approach offers visual and formal techniques in such a way that model transformations can be subjects to analysis. Various results on graph transformation can be used to prove important properties of model transformations such as its functional behaviour, a basic property for computations. Moreover, certain kinds of syntactical and semantical consistency properties can be shown on this formal basis

Supporting the migration towards model-driven robotic systems

Robots are increasingly deployed to perform every-day tasks. It is crucial to implement reliable and reusable systems to reduce development effort. The complexity of robotic systems requires the collaboration of experts from different backgrounds. Therefore, clear and communicatable abstraction of components is essential for successful development process. There has been a demand in the community for increased adoption of software engineering approaches to support better robotic systems. Adopting model-driven approaches has been proved successful in supporting this movement. We aim to support the adaptation of model-driven approaches in robotic domain in three interest areas: behavior models, structural models and guaranteeing confidence in system behavior.The overall goal is to support the creation of reusable, verifiable and easy to communicate robotic missions and systems. To achieve that, we conducted a mix of knowledge-seeking and solution-seeking studies. We started with behavior models. We wanted to build knowledge about used behavior models in practice. We investigated the state-of-practice of an emerging behavior model, behavior trees, in comparison to two standardized UML models and a traditional roboticists choice. Moving to the second interest area, we wanted to support the creation of light-weight tools for building an understanding of system structure using feature models. We conducted a pilot evaluation of an already light-weight tool, called FeatureVista. The final interest area was guaranteeing confidence in system behavior. The usual engineering process of self-adaptive controllers in robotic involves different model-based approaches. We wanted to investigate an approach that reaffirm, at code-level, control properties while keeping the usual engineering process. We investigated an approach for mapping control properties to software ones using an appropriate input format for software model-based checking.Our investigations in the different interest areas have built knowledge and shed light on opportunities. We provided characteristics of behavior models, behavior trees and state machines, in popular robotic implementations and highlighted opportunities for improvements. We also provided usage trend for studied implementations in open-source projects. In addition, we provided corestructural characteristic and code-reuse patterns for studied behavior models in open-source projects. For feature models, our results showed promising results for using an interactive tool that provides an easy and initiative navigation between feature models and software components. Improvement aspects were also highlighted for developing similar tools. Finally, our work for the confidence of system behavior showed promising results in reaffirming the correctness of a control property at code-level using appropriate software notation, specification patterns. Also, our approach allowed keeping the current practices of using model-based approaches in self-adaptive robotic systems

A Language-centered Approach to support environmental modeling with Cellular Automata

Die Anwendung von Methodiken und Technologien aus dem Bereich der Softwaretechnik auf den Bereich der Umweltmodellierung ist eine gemeinhin akzeptierte Vorgehensweise. Im Rahmen der "modellgetriebenen Entwicklung"(MDE, model-driven engineering) werden Technologien entwickelt, die darauf abzielen, Softwaresysteme vorwiegend auf Basis von im Vergleich zu Programmquelltexten relativ abstrakten Modellen zu entwickeln. Ein wesentlicher Bestandteil von MDE sind Techniken zur effizienten Entwicklung von "domänenspezifischen Sprachen"( DSL, domain-specific language), die auf Sprachmetamodellen beruhen. Die vorliegende Arbeit zeigt, wie modellgetriebene Entwicklung, und insbesondere die metamodellbasierte Beschreibung von DSLs, darüber hinaus Aspekte der Pragmatik unterstützen kann, deren Relevanz im erkenntnistheoretischen und kognitiven Hintergrund wissenschaftlichen Forschens begründet wird. Hierzu wird vor dem Hintergrund der Erkenntnisse des "modellbasierten Forschens"(model-based science und model-based reasoning) gezeigt, wie insbesondere durch Metamodelle beschriebene DSLs Möglichkeiten bieten, entsprechende pragmatische Aspekte besonders zu berücksichtigen, indem sie als Werkzeug zur Erkenntnisgewinnung aufgefasst werden. Dies ist v.a. im Kontext großer Unsicherheiten, wie sie für weite Teile der Umweltmodellierung charakterisierend sind, von grundsätzlicher Bedeutung. Die Formulierung eines sprachzentrierten Ansatzes (LCA, language-centered approach) für die Werkzeugunterstützung konkretisiert die genannten Aspekte und bildet die Basis für eine beispielhafte Implementierung eines Werkzeuges mit einer DSL für die Beschreibung von Zellulären Automaten (ZA) für die Umweltmodellierung. Anwendungsfälle belegen die Verwendbarkeit von ECAL und der entsprechenden metamodellbasierten Werkzeugimplementierung.The application of methods and technologies of software engineering to environmental modeling and simulation (EMS) is common, since both areas share basic issues of software development and digital simulation. Recent developments within the context of "Model-driven Engineering" (MDE) aim at supporting the development of software systems at the base of relatively abstract models as opposed to programming language code. A basic ingredient of MDE is the development of methods that allow the efficient development of "domain-specific languages" (DSL), in particular at the base of language metamodels. This thesis shows how MDE and language metamodeling in particular, may support pragmatic aspects that reflect epistemic and cognitive aspects of scientific investigations. For this, DSLs and language metamodeling in particular are set into the context of "model-based science" and "model-based reasoning". It is shown that the specific properties of metamodel-based DSLs may be used to support those properties, in particular transparency, which are of particular relevance against the background of uncertainty, that is a characterizing property of EMS. The findings are the base for the formulation of an corresponding specific metamodel- based approach for the provision of modeling tools for EMS (Language-centered Approach, LCA), which has been implemented (modeling tool ECA-EMS), including a new DSL for CA modeling for EMS (ECAL). At the base of this implementation, the applicability of this approach is shown

A quality management based on the Quality Model life cycle

Managing quality is a hard and expensive task that involves the execution and control of processes and techniques. For a good quality management, it is important to know the current state and the objective to be achieved. It is essential to take into account with a Quality Model that specifies the purposes of managing quality. QuEF (Quality Evaluation Framework) is a framework to manage quality in MDWE (Model-driven Web Engineering). This paper suggests managing quality but pointing out the Quality Model life cycle. The purpose is to converge toward a quality continuous improvement by means of reducing effort and time.Ministerio de Ciencia e Innovación TIN2010-20057-C03-02Ministerio de Ciencia e Innovación TIN 2010-12312-EJunta de Andalucía TIC-578

From napkin sketches to reliable software

In the past few years, model-driven software engineering (MDSE) and domain-specific modeling languages (DSMLs) have received a lot of attention from both research and industry. The main goal of MDSE is generating software from models that describe systems on a high level of abstraction. DSMLs are languages specifically designed to create such models. High-level models are refined into models on lower levels of abstraction by means of model transformations. The ability to model systems on a high level of abstraction using graphical diagrams partially explains the popularity of the informal modeling language UML. However, even designing simple software systems using such graphical diagrams can lead to large models that are cumbersome to create. To deal with this problem, we investigated the integration of textual languages into large, existing modeling languages by comparing two approaches and designed a DSML with a concrete syntax consisting of both graphical and textual elements. The DSML, called the Simple Language of Communicating Objects (SLCO), is aimed at modeling the structure and behavior of concurrent, communicating objects and is used as a case study throughout this thesis. During the design of this language, we also designed and implemented a number of transformations to various other modeling languages, leading to an iterative evolution of the DSML, which was influenced by the problem domain, the target platforms, model quality, and model transformation quality. Traditionally, the state-space explosion problem in model checking is handled by applying abstractions and simplifications to the model that needs to be verified. As an alternative, we demonstrate a model-driven engineering approach that works the other way around using SLCO. Instead of making a concrete model more abstract, we refine abstract models by transformation to make them more concrete, aiming at the verification of models that are as close to the implementation as possible. The results show that it is possible to validate more concrete models when fine-grained transformations are applied instead of coarse-grained transformations. Semantics are a crucial part of the definition of a language, and to verify the correctness of model transformations, the semantics of both the input and the output language must be formalized. For these reasons, we implemented an executable prototype of the semantics of SLCO that can be used to transform SLCO models to labeled transition systems (LTSs), allowing us to apply existing tools for visualization and verification of LTSs to SLCO models. For given input models, we can use the prototype in combination with these tools to show, for each transformation that refines SLCO models, that the input and output models exhibit the same observable behavior. This, however, does not prove the correctness of these transformations in general. To prove this, we first formalized the semantics of SLCO in the form of structural operational semantics (SOS), based on the aforementioned prototype. Then, equivalence relations between LTSs were defined based on each transformation, and finally, these relations were shown to be either strong bisimulations or branching bisimulations. In addition to this approach, we studied property preservation of model transformations without restricting ourselves to a fixed set of transformations. Our technique takes a property and a transformation, and checks whether the transformation preserves the property. If a property holds for the initial model, which is often small and easy to analyze, and the property is preserved, then the refined model does not need to be analyzed too. Combining the MDSE techniques discussed in this thesis enables generating reliable and correct software by means of refining model transformations from concise, formal models specified on a high level of abstraction using DSMLs