Efficient Generation of Graphical Model Views via Lazy Model-to-Text Transformation

Producing graphical views from software and system models is often desirable for communication and comprehension purposes, even when graphical model editing capabilities are not required -- because the preferred editable concrete syntax of the models is text-based, or for models extracted via reverse engineering. To support such scenarios, we present a novel approach for efficient rule-based generation of transient graphical views from models using lazy model-to-text transformation, and an implementation of the proposed approach in the form of an open-source Eclipse plugin named Picto. Picto builds on top of mature visualisation software such as Graphviz and PlantUML and supports, among others, composite views, layers, and multi-model visualisation. We illustrate how Picto can be used to produce various forms of graphical views such as node-edge diagrams, tables and sequence-like diagrams, and we demonstrate the efficiency benefits of lazy view generation approach against batch model-to-text transformation for generating views from large models

Model Transformation Languages with Modular Information Hiding

Model transformations, together with models, form the principal artifacts in model-driven software development. Industrial practitioners report that transformations on larger models quickly get sufficiently large and complex themselves. To alleviate entailed maintenance efforts, this thesis presents a modularity concept with explicit interfaces, complemented by software visualization and clustering techniques. All three approaches are tailored to the specific needs of the transformation domain

Model Transformation Languages with Modular Information Hiding

Model transformations, together with models, form the principal artifacts in model-driven software development. Industrial practitioners report that transformations on larger models quickly get sufficiently large and complex themselves. To alleviate entailed maintenance efforts, this thesis presents a modularity concept with explicit interfaces, complemented by software visualization and clustering techniques. All three approaches are tailored to the specific needs of the transformation domain

Consistency-by-Construction Techniques for Software Models and Model Transformations

A model is consistent with given specifications (specs) if and only if all the specifications are held on the model, i.e., all the specs are true (correct) for the model. Constructing consistent models (e.g., programs or artifacts) is vital during software development, especially in Model-Driven Engineering (MDE), where models are employed throughout the life cycle of software development phases (analysis, design, implementation, and testing). Models are usually written using domain-specific modeling languages (DSMLs) and specified to describe a domain problem or a system from different perspectives and at several levels of abstraction. If a model conforms to the definition of its DSML (denoted usually by a meta-model and integrity constraints), the model is consistent. Model transformations are an essential technology for manipulating models, including, e.g., refactoring and code generation in a (semi)automated way. They are often supposed to have a well-defined behavior in the sense that their resulting models are consistent with regard to a set of constraints. Inconsistent models may affect their applicability and thus the automation becomes untrustworthy and error-prone. The consistency of the models and model transformation results contribute to the quality of the overall modeled system. Although MDE has significantly progressed and become an accepted best practice in many application domains such as automotive and aerospace, there are still several significant challenges that have to be tackled to realize the MDE vision in the industry. Challenges such as handling and resolving inconsistent models (e.g., incomplete models), enabling and enforcing model consistency/correctness during the construction, fostering the trust in and use of model transformations (e.g., by ensuring the resulting models are consistent), developing efficient (automated, standardized and reliable) domain-specific modeling tools, and dealing with large models are continually making the need for more research evident. In this thesis, we contribute four automated interactive techniques for ensuring the consistency of models and model transformation results during the construction process. The first two contributions construct consistent models of a given DSML in an automated and interactive way. The construction can start at a seed model being potentially inconsistent. Since enhancing a set of transformations to satisfy a set of constraints is a tedious and error-prone task and requires high skills related to the theoretical foundation, we present the other contributions. They ensure model consistency by enhancing the behavior of model transformations through automatically constructing application conditions. The resulting application conditions control the applicability of the transformations to respect a set of constraints. Moreover, we provide several optimizing strategies. Specifically, we present the following: First, we present a model repair technique for repairing models in an automated and interactive way. Our approach guides the modeler to repair the whole model by resolving all the cardinalities violations and thereby yields a desired, consistent model. Second, we introduce a model generation technique to efficiently generate large, consistent, and diverse models. Both techniques are DSML-agnostic, i.e., they can deal with any meta-models. We present meta-techniques to instantiate both approaches to a given DSML; namely, we develop meta-tools to generate the corresponding DSML tools (model repair and generation) for a given meta-model automatically. We present the soundness of our techniques and evaluate and discuss their features such as scalability. Third, we develop a tool based on a correct-by-construction technique for translating OCL constraints into semantically equivalent graph constraints and integrating them as guaranteeing application conditions into a transformation rule in a fully automated way. A constraint-guaranteeing application condition ensures that a rule applies successfully to a model if and only if the resulting model after the rule application satisfies the constraint. Fourth, we propose an optimizing-by-construction technique for application conditions for transformation rules that need to be constraint-preserving. A constraint-preserving application condition ensures that a rule applies successfully to a consistent model (w.r.t. the constraint) if and only if the resulting model after the rule application still satisfies the constraint. We show the soundness of our techniques, develop them as ready-to-use tools, evaluate the efficiency (complexity and performance) of both works, and assess the overall approach in general as well. All our four techniques are compliant with the Eclipse Modeling Framework (EMF), which is the realization of the OMG standard specification in practice. Thus, the interoperability and the interchangeability of the techniques are ensured. Our techniques not only improve the quality of the modeled system but also increase software productivity by providing meta-tools for generating the DSML tool supports and automating the tasks

A Functional, Comprehensive and Extensible Multi-Platform Querying and Transformation Approach

This thesis is about a new model querying and transformation approach called FunnyQT which is realized as a set of APIs and embedded domain-specific languages (DSLs) in the JVM-based functional Lisp-dialect Clojure. Founded on a powerful model management API, FunnyQT provides querying services such as comprehensions, quantified expressions, regular path expressions, logic-based, relational model querying, and pattern matching. On the transformation side, it supports the definition of unidirectional model-to-model transformations, of in-place transformations, it supports defining bidirectional transformations, and it supports a new kind of co-evolution transformations that allow for evolving a model together with its metamodel simultaneously. Several properties make FunnyQT unique. Foremost, it is just a Clojure library, thus, FunnyQT queries and transformations are Clojure programs. However, most higher-level services are provided as task-oriented embedded DSLs which use Clojure's powerful macro-system to support the user with tailor-made language constructs important for the task at hand. Since queries and transformations are just Clojure programs, they may use any Clojure or Java library for their own purpose, e.g., they may use some templating library for defining model-to-text transformations. Conversely, like every Clojure program, FunnyQT queries and transformations compile to normal JVM byte-code and can easily be called from other JVM languages. Furthermore, FunnyQT is platform-independent and designed with extensibility in mind. By default, it supports the Eclipse Modeling Framework and JGraLab, and support for other modeling frameworks can be added with minimal effort and without having to modify the respective framework's classes or FunnyQT itself. Lastly, because FunnyQT is embedded in a functional language, it has a functional emphasis itself. Every query and every transformation compiles to a function which can be passed around, given to higher-order functions, or be parametrized with other functions

Automated reasoning for attributed graph properties

Graphs are ubiquitous in computer science. Moreover, in various application fields, graphs are equipped with attributes to express additional information such as names of entities or weights of relationships. Due to the pervasiveness of attributed graphs, it is highly important to have the means to express properties on attributed graphs to strengthen modeling capabilities and to enable analysis. Firstly, we introduce a new logic of attributed graph properties, where the graph part and attribution part are neatly separated. The graph part is equivalent to first-order logic on graphs as introduced by Courcelle. It employs graph morphisms to allow the specification of complex graph patterns. The attribution part is added to this graph part by reverting to the symbolic approach to graph attribution, where attributes are represented symbolically by variables whose possible values are specified by a set of constraints making use of algebraic specifications. Secondly, we extend our refutationally complete tableau-based reasoning method as well as our symbolic model generation approach for graph properties to attributed graph properties. Due to the new logic mentioned above, neatly separating the graph and attribution parts, and the categorical constructions employed only on a more abstract level, we can leave the graph part of the algorithms seemingly unchanged. For the integration of the attribution part into the algorithms, we use an oracle, allowing for flexible adoption of different available SMT solvers in the actual implementation. Finally, our automated reasoning approach for attributed graph properties is implemented in the tool AutoGraph integrating in particular the SMT solver Z3 for the attribute part of the properties. We motivate and illustrate our work with a particular application scenario on graph database query validation.Peer ReviewedPostprint (author's final draft

DC4MT : uma abordagem orientada a dados para transformação de modelos

Orientador: Marcos Didonet Del FabroTese (doutorado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Informática. Defesa : Curitiba, 25/08/2020Inclui referências: p. 95-106Área de concentração: Ciência da ComputaçãoResumo: Transformações de Modelos são operações que recebem um conjunto de modelos como entrada e produzem um conjunto de modelos como saída, seguindo uma especificação. Há uma coleção diversificada de abordagens e ferramentas utilizadas para a especificação de diferentes tipos de transformações de modelos. A maioria dessas abordagens adota como estratégia a execução local e sequencial. No entanto, essas abordagens não estão totalmente aptas para processar modelos com grandes quantidades de elementos. VLMs (Very Large Models) são modelos que possuem milhões de elementos. Esses modelos estão presentes em domínios de aplicações como na indústria automotiva, modernização de sistemas legados, internet das coisas, redes sociais, entre outros domínios. Essas abordagens possuem lacunas para suportar o processamento desses VLMs. Por exemplo, para possibilitar a execução das transformações de modelos, considerando a escala do problema ou para melhoria de desempenho. Nesta tese é proposta a Dc4MT, uma abordagem para suportar transformações de VLMs com a aplicação e adaptação de técnicas relacionadas à distribuição de dados. A Dc4MT é uma abordagem Orientada a Dados (Dc - Data-centric) para ser aplicada no domínio da Engenharia Dirigida por Modelos (MDE - Model Driven Engineering). A abordagem é especificada, utilizando um framework de processamento distribuído, e define um conjunto de operações para a fragmentação, extração e transformação de modelos. A fragmentação é uma operação que divide os modelos de entrada (em formatos XMI ou JSON) em fragmentos, de modo que esses fragmentos possam ser distribuídos e processados de maneira paralela/distribuída. A extração é uma operação que processa os fragmentos do modelo de entrada e os traduz em um grafo acíclico, atribuindo um novo domínio de modelagem a esses fragmentos. A transformação de modelos na abordagem Dc4MT é uma operação que transforma modelos de entrada em modelos de saída (M2M) a partir do resultado da extração. As execuções de transformação podem ser em modo paralelo ou distribuído, com ou sem a intervenção no método de particionamento do framework disponível para melhorar o desempenho. Um conjunto de modelos de entrada (datasets) e os ambientes local (transformações paralelas) e distribuído (transformações distribuídas) são utilizados nos experimentos para validar a abordagem Dc4MT, sob os aspectos de factibilidade, desempenho e de escalabilidade. Os resultados desses experimentos, mostram que as operações de fragmentação e extração de modelos favorecem a transformação escalável de VLMs, reconstruindo a estrutura dos fragmentos em um grafo. A operação de extração é executada em modo paralelo/distribuído. Além disso, os aspectos como a imutabilidade, lazy-evaluate e o paralelismo implícito presentes na Dc4MT, permitem o processamento paralelo/distribuído de regras de transformação em uma plataforma escalável. Palavras-chave: Abordagem Orientada a Dados. Engenharia Dirigida por Modelos. Transformação Paralela de Modelos. Transformação Distribuída de Modelos.Abstract: Model Transformations are operations that receive a set of source models as input and produce a set of target models as output, following a specification. There is a variety of approaches and tools used for the specification of different types of model transformation. Most of these approaches adopt for model transformation the local and sequential execution strategy. However, these approaches not fully adapted for processing models with large amounts of elements. VLMs (Very Large Models) are models with millions of elements. These models are present in application domains such as the automotive industry, modernization of legacy systems, internet of things, social networks, among others. These approaches have gaps to support the processing of these increasingly larger models. For example, to enable model transformations, considering the scale of the problem or to improve performance. In this thesis, the Dc4MT is proposed such as an approach to support transformation of VLMs, applying and adapting distribution techniques of data. The Dc4MT is a Data-centric (Dc) approach for applying in Model Driven Engineering (MDE). The approach will be specified using a distributed processing framework, and defines a set of operations for fragmentation, extraction, and transformation of models. The fragmentation is an operation that splits the input models (in the XMI or JSON formats) in a way that the fragments can be processed in parallel/distributed. The extraction is an operation that processes the fragments of the input model in parallel and translates them to an acyclic graph, assigning a new modeling domain to these fragments. The model transformation in Dc4MT is an operation that transforms input models in output models (M2M) from the results of the extraction. The transformation executions can be parallel or distributed with ou without the intervention in the framework partitioning method to improve the performance. A set of input models (datasets) and the local (parallel transformations) and distributed (distributed transformations) environments are used in the experiments to validate the Dc4MT approach, in terms of feasibility, performance, and scalability. The results of the experiments show that the model fragmentation and extraction operations favor the scalable transformation of models, reconstructing the structure of the fragments in a graph. The extraction operation is executed on parallel/distributed way. Moreover, aspects such as immutability, lazy-evaluation, and implicit parallelism present in Dc4MT, allowing the parallel/distributed processing of transformation rules on a scalable platform. Keywords: Data-centric Approach. Model Driven Engineering. Parallel Model Transformation. Distributed Model Transformation