On the Quality Properties of Model Transformations: Performance and Correctness

The increasing complexity of software due to continuous technological advances has motivated the use of models in the software development process. Initially, models were mainly used as drafts to help developers understand their programs. Later they were used extensively and a new discipline called Model-Driven Engineering (MDE) was born. In the MDE paradigm, aside from the models themselves, model transformations (MT) are garnering interest as they allow the analysis and manipulation of models. Therefore, the performance, scalability and correctness of model transformations have become critical issues and thus they deserve a thorough study. Existing model transformation engines are principally based on sequential and in-memory execution strategies, and hence their capabilities to transform very large models in parallel and in distributed environments are limited. Current tools and languages are not able to cope with models that are not located in a single machine and, even worse, most of them require the model to be in a single file. Moreover, once a model transformation has been written and executed-either sequentially or in parallel-it is necessary to rely on methods, mechanisms, and tools for checking its correctness. In this dissertation, our contribution is twofold. Firstly, we introduce a novel execution platform that permits the parallel execution of both out-place and in-place model transformations, regardless of whether the models fit into a single machine memory or not. This platform can be used as a target for high-level transformation language compilers, so that existing model transformations do not need to be rewritten in another language but only have to be executed more efficiently. Another advantage is that a developer who is familiar with an existing model transformation language does not need to learn a new one. In addition to performance, the correctness of model transformations is an essential aspect that needs to be addressed if MTs are going to be used in realistic industrial settings. Due to the fact that the most popular model transformation languages are rule-based, i.e., the transformations written in those languages comprise rules that define how the model elements are transformed, the second contribution of this thesis is a static approach for locating faulty rules in model transformations. Current approaches able to fully prove correctness-such as model checking techniques-require an unacceptable amount of time and memory. Our approach cannot fully prove correctness but can be very useful for identifying bugs at an early development stage, quickly and cost effectively

Migrating software to mobile technology: a model driven engineering approach

Nowadays, organizations are facing the problematic of having to modernize or replace their legacy software. This software has involved the investment of money, time and other resources through the ages and there is a high risk in replacing it. The purpose of reengineering is to adapt software in a disciplined way in order to improve its quality in aspects such as operability, functionality or performance. The focus of reengineering is on improving an existing system with a higher return on investment than would be achieved by developing a new system. In the context of reengineering, the term legacy was associated with software that survived several generations of developers, administrators and users. The entry into the market of new technologies or paradigms is increasingly occurring and, motivates the growing demand for the adaptation of systems developed more recently. Mobile Computing is crucial to harvesting the potential of these new paradigms. Smartphones are the most used computing platform worldwide. They come with a variety of sensors (GPS, accelerometer, digital compass, microphone and camera) enabling a wide range of applications in Pervasive Computing, Cloud Computing and Internet of Things (IoT)

Model Transformation Testing and Debugging: A Survey

Model transformations are the key technique in Model-Driven Engineering (MDE) to manipulate and construct models. As a consequence, the correctness of software systems built with MDE approaches relies mainly on the correctness of model transformations, and thus, detecting and locating bugs in model transformations have been popular research topics in recent years. This surge of work has led to a vast literature on model transformation testing and debugging, which makes it challenging to gain a comprehensive view of the current state of the art. This is an obstacle for newcomers to this topic and MDE practitioners to apply these approaches. This paper presents a survey on testing and debugging model transformations based on the analysis of \nPapers~papers on the topics. We explore the trends, advances, and evolution over the years, bringing together previously disparate streams of work and providing a comprehensive view of these thriving areas. In addition, we present a conceptual framework to understand and categorise the different proposals. Finally, we identify several open research challenges and propose specific action points for the model transformation community.This work is partially supported by the European Commission (FEDER) and Junta de Andalucia under projects APOLO (US-1264651) and EKIPMENT-PLUS (P18-FR-2895), by the Spanish Government (FEDER/Ministerio de Ciencia e Innovación – Agencia Estatal de Investigación) under projects HORATIO (RTI2018-101204-B-C21), COSCA (PGC2018-094905-B-I00) and LOCOSS (PID2020-114615RB-I00), by the Austrian Science Fund (P 28519-N31, P 30525-N31), and by the Austrian Federal Ministry for Digital and Economic Affairs and the National Foundation for Research, Technology and Development (CDG

Computer-Aided Warehouse Engineering (CAWE): Leveraging MDA and ADM for the Development of Data Warehouses

During the last decade, data warehousing has reached a high maturity and is a well-accepted technology in decision support systems. Nevertheless, development and maintenance are still tedious tasks since the systems grow over time and complex architectures have been established. The paper at hand adopts the concepts of Model Driven Architecture (MDA) and Architecture Driven Modernization (ADM) taken from the software engineering discipline to the data warehousing discipline. We show the works already available, outline further research directions and give hints for implementation of Computer-Aided Warehouse Engineering systems

Migrating Traditional Web Applications to CMS-based Web Applications

AbstractIn recent years, Content Management Systems (CMS) have proven to be the best platforms for maintaining the large amount of digital content managed by Web applications. Thus, many organizations have experienced the necessity to base its Web applications on these CMS platforms. To do this, they start a migration process which is complex and error prone. To support this process, we propose a method based on the principles of Architecture-Driven Modernization (ADM) which automates the migration of Web applications to CMS-based Web applications. This article focuses on the implementation of two artifacts of this method: 1) the DSL ASTM_PHP, a modeling language for defining a model from PHP code (ASTM_PHP model) and 2) the model-to-model transformation rules which generate automatically a KDM model from a ASTM_PHP model. To show the feasibility of this implementation, we use a case study based on a widget implemented in PHP which lists the online users of a Web application

A modular metamodel and refactoring rules to achieve software product line interoperability.

Emergent application domains, such as cyber–physical systems, edge computing or industry 4.0. present a high variability in software and hardware infrastructures. However, no single variability modeling language supports all language extensions required by these application domains (i.e., attributes, group cardinalities, clonables, complex constraints). This limitation is an open challenge that should be tackled by the software engineering field, and specifically by the software product line (SPL) community. A possible solution could be to define a completely new language, but this has a high cost in terms of adoption time and development of new tools. A more viable alternative is the definition of refactoring and specialization rules that allow interoperability between existing variability languages. However, with this approach, these rules cannot be reused across languages because each language uses a different set of modeling concepts and a different concrete syntax. Our approach relies on a modular and extensible metamodel that defines a common abstract syntax for existing variability modeling extensions. We map existing feature modeling languages in the SPL community to our common abstract syntax. Using our abstract syntax, we define refactoring rules at the language construct level that help to achieve interoperability between variability modeling languages.Work supported by the projects MEDEA RTI2018-099213-B-I00, IRIS PID2021-122812OB-I00 (co-financed by FEDER funds), Rhea P18-FR-1081 (MCI/AEI/FEDER, UE), LEIA UMA18-FEDERIA-157, and DAEMON H2020-101017109. // Funding for open access: Universidad de Málaga / CBUA

A Method for Developing Model to Text Transformations

In the field of business process development, model transformations play a key role, for example for moving from business process models to either code or inputs for simulation systems, as well as to convert models expressed with notation A into equivalent models expressed with notation B. In the literature, many cases of useful transformations of business process models can be found. However, in general each transformation has been developed in an ad-hoc fashion, at a quite low-level, and its quality is often neglected. To ensure the quality of the transformations is important to apply to them all the well-known software engineering principles and practices, from the requirements definition to the testing activities. For this reason, we propose a method, MeDMoT, for developing non-trivial Model to Text Transformations, which prescribes how to: (1) capture and specify the transformation requirements; (2) design the transformation, (3) implement the transformation and (4) test the transformation. The method has been applied in several case studies, including a transformation of UML business processes into inputs for an agent-based simulator

Simulation of Road Traffic Applying Model-Driven Engineering

Road traffic is an important phenomenon in modern societies. The study of its different aspects in the multiple scenarios where it happens is relevant for a huge number of problems. At the same time, its scale and complexity make it hard to study. Traffic simulations can alleviate these difficulties, simplifying the scenarios to consider and controlling their variables. However, their development also presents difficulties. The main ones come from the need to integrate the way of working of researchers and developers from multiple fields. Model-Driven Engineering (MDE) addresses these problems using Modelling Languages (MLs) and semi-automatic transformations to organise and describe the development, from requirements to code. This paper presents a domain-specific MDE framework for simulations of road traffic. It comprises an extensible ML, support tools, and development guidelines. The ML adopts an agent-based approach, which is focused on the roles of individuals in road traffic and their decision-making. A case study shows the process to model a traffic theory with the ML, and how to specialise that specification for an existing target platform and its simulations. The results are the basis for comparison with related work