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Although model transformations are considered to be the heart and soul of Model Driven Engineering (MDE), there are still several challenges that need to be addressed to unleash their full potential in industrial settings. Among other shortcomings, their performance and scalability remain unsatisfactory for dealing with large models, making their wide adoption difficult in practice. This paper presents A2L, a compiler for the parallel execution of ATL model transformations, which produces efficient code that can use existing multicore computer architectures, and applies effective optimizations at the transformation level using static analysis. We have evaluated its performance in both sequential and multi-threaded modes obtaining significant speedups with respect to current ATL implementations. In particular, we obtain speedups between 2.32x and 38.28x for the A2L sequential version, and between 2.40x and 245.83x when A2L is executed in parallel, with expected average speedups of 8.59x and 22.42x, respectively. Spanish Research Projects PGC2018-094905-B-I00, TIN2015-73968-JIN (AEI/FEDER/UE), Ramón y Cajal 2017 research grant, TIN2016-75944-R. Austrian Federal Ministry for Digital and Economic Affairs, the National Foundation for Research, Technology and Development, and by the FWF under the Grant Numbers P28519-N31 and P30525-N31.

The motivation behind 15 years of continuous development within the topic of the Tensor Product (TP) model transformation is that the greater the number of parameters or components of the Takagi Sugeno (TS) fuzzy model one can manipulate, the larger the complexity reduction or control optimization one can achieve. The paper proposes a radically new type of extension to the TP model transformation: while earlier variants of the TP model transformation focused on how the antecedent - consequent fuzzy set system of a given TS fuzzy model could be varied, the present work, in contrast, focuses on how the number of inputs to a given TS fuzzy model can be manipulated. The proposed extension is capable of changing the number of inputs or transforming the non-linearity between the fuzzy rules and the input dimensions. These new features considerably increase the modeling power of the TP model transformation, allowing for further complexity reduction and more powerful control optimisation to be achieved. The paper provides two examples to show how the proposed extension can be used in a routine-like fashion.

This article investigates the velocity and input constrained tracking control problem of discrete-time high-speed train systems. A distributed cooperative tracking control algorithm is proposed for each train using the local information from its adjacent trains. Based on model transformation and the convex analysis approach, it is shown that all trains eventually cooperative run in a stable mode while tracking the desired speed. Finally, a simulation example is given to demonstrate the obtained theoretical results.

In this article, we address how the production of model transformations (MT) can be accelerated by automation of transformation synthesis from requirements, examples, and metamodels. We introduce a synthesis process based on metamodel matching, correspondence patterns between metamodels, and completeness and consistency analysis of matches. We describe how the limitations of metamodel matching can be addressed by combining matching with automated requirements analysis and model transformation by example (MTBE) techniques. We show that in practical examples a large percentage of required transformation functionality can usually be constructed automatically, thus potentially reducing development effort. We also evaluate the efficiency of synthesised transformations. Our novel contributions are: The concept of correspondence patterns between metamodels of a transformation. Requirements analysis of transformations using natural language processing (NLP) and machine learning (ML). Symbolic MTBE using “predictive specification” to infer transformations from examples. Transformation generation in multiple MT languages and in Java, from an abstract intermediate language.

Enterprise architecture has become an important driver to facilitate digital transformation in companies, since it allows to manage IT and business in a holistic and integrated manner by establishing connections among technology concerns and strategical/motivational ones. Enterprise architecture modelling is critical to accurately represent business and their IT assets in combination. This modelling is important when companies start to manage their enterprise architecture, but also when it is remodelled so that the enterprise architecture is realigned in a changing world. Enterprise architecture is commonly modelled by few experts in a manual way, which is error-prone and time-consuming and makes continuous realignment difficult. In contrast, other enterprise architecture modelling proposal automatically analyses some artefacts like source code, databases, services, etc. Previous automated modelling proposals focus on the analysis of individual artefacts with isolated transformations toward ArchiMate or other enterprise architecture notations and/or frameworks. We propose the usage of Knowledge Discovery Metamodel (KDM) to represent all the intermediate information retrieved from information systems’ artefacts, which is then transformed into ArchiMate models. Thus, the core contribution of this paper is the model transformation between KDM and ArchiMate metamodels. The main implication of this proposal is that ArchiMate models are automatically generated from a common knowledge repository. Thereby, the relationships between different-nature artefacts can be exploited to get more complete and accurate enterprise architecture representations.

With the increasing demand to deploy convolutional neural networks (CNNs) on 5G mobile platforms, architecture designs with efficient sparse kernels (SKs) were proposed, which can save more parameters than the standard convolution while maintaining the high accuracy. Despite the great potential, neural network designs with SKs still require a lot of expert knowledge and take ample time. In this paper, we first propose a search scheme that effectively reduces the SK design space based on three aspects: composition , performance , and efficiency . Meanwhile, we completely eliminate the model training from our search scheme. Instead, an easily measurable quantity, the information field , is identified and used to predict the model accuracy in the searching process. Additionally, we provide a detailed efficiency analysis on the final designs found by our scheme. Second, based on the analysis we propose a model transformation scheme to better utilize the SK designs on existing models to either reduce the number of parameters or increase the accuracy. Last, considering the extra programming overhead and the expert knowledge required by the model transformation scheme, we develop a compiler prototype to automate the entire process, given the source code of an existing model. Experimental results show that models composed of the sparse kernel designs searched by our search scheme can beat state-of-the-art networks such as ResNets in terms of the accuracy and the efficiency. Also by using our model transformation scheme we can easily improve the accuracy (the same number of parameters) or the efficiency (the same accuracy) upon existing state-of-the-art models.

We address the state estimation problem for a class of genetic regulatory networks (GRNs) with leakage and discrete heterogeneous delays in this paper. In order to simplify the complexity of designing the state estimator for nonlinear delayed model of GRNs, a state estimate algorithm based on a model transformation method is presented, which goal is to get the entire system state. First, in light of the Lagrange’s mean-value theorem, the nonlinear model transformation method is applied to describe the nonlinear error system as a linear time-varying model. Second, by constructing the Lyapunov–Krasovskii functional dependent on the composite function variables of state estimate errors, a new technique lemma is provided and applied to the stability analysis. Third, the sufficient condition of state estimator design is obtained in term linear matrix inequalities, under which, the certification of the uniform asymptotic stability for state estimate error system is derived. Finally, a simulation example illustrates the rationality and effectiveness of the proposed theoretical results.

In the past few years, software development has seen rapid growth, and developers have adopted different methods to provide efficient procedures in software development, thus reducing the overall bug counts and time delay. Bidirectional model transformation is one such technique that encompasses the development of the object code in both directions enabling an abstract view of the software to the developer; over the year’s researchers, have been able to produce many approaches in bidirectional model transformations (bx), but the cost and best fir for effective model transformation, in particular, a quantities survey will be designed which will discuss the best possible apron in the bx. The methodology for this survey shall be made through SLR to identify around 20 different approaches proposed for bidirectional model transformation; these studies range from the year 2010 till date and are thus, rendered latest in the respective fields of our survey. The gathered results have been calculated on the specific set of parameters that are cost and time of usage time are the main aspects of these approaches, and that is the predicament that has made us produce a systematic literature review (SLR) on this very topic. Thus, this paper investigates different approaches based on their implementation cost and time delay and discusses their limitations, and the approach is implemented. Those approaches have been selected, which culminate in both of these respective parameters. The main objective of this SLR is to provide an insight into the different approaches and establish a well-balanced approach that can be used in bidirectional model transformation in software development.

The final executable code should no longer be considered as a central element in a software development process but rather a naturally important component that results from a model transformation. The objective of the MDA (Model Driven Architecture) approach is to lift the lock of software development automation from the CIM (Computation Independent Model) requirements until the code of an application is obtained. Therefore, we have proposed in the framework of MDA an approach that consists of automatically generating object-oriented code from the CIM model represented by ReLEL (Restructuring extended Lexical Elaborate Language). ReLEL is a natural language-oriented model that represents both the client requirements and the conceptual level of a system. However, the MDA framework does not recommend the type of UML model that corresponds to each business activity. Consequently, automating the software development process from the CIM model specified by ReLEL becomes a complex task. Our strategy in this paper includes the instantiation of the ReLEL model in the Praxeme methodology, which models each of the company's concerns, grouped in a homogeneous whole, using the UML (Unified Modeling Language) and which considers the articulation of these aspects by adopting the MDA principle. To do this, we propose to automate the articulation that covers the intentional, semantic, logical, and software aspects of Praxeme. To validate our approach, we measure the coupling and cohesion of the UML class diagram obtained from the Java code generated from this article using the slicing technique. The results show that the coupling is weak, and the cohesion is strong. It can be deduced that the method proposed in this paper can produce a more reliable and efficient system.

In this study, a robust decentralized stochastic $H_{\infty }$ tracking control design is proposed to deal with the team formation tracking problem for a large-scale biped robot team system with external disturbance and communication requirement on biped robots and leader. Under the concept of virtual leader and the decentralized control approach, biped robots walking in a large-scale team formation are controlled to track their own reference paths with the robust stochastic $H_{\infty }$ tracking performance. Consequently, the original robust decentralized stochastic $H_{\infty }$ large-scale biped robot team formation tracking control design problem can be transformed to a set of independent Hamilton–Jacobi inequality (HJI)-constrained optimization problems for each biped robot. To cope with the difficulties in solving the HJIs for the robust decentralized stochastic $H_{\infty }$ team formation tracking control design, a numerical framework is introduced to approximate the walking biped robot systems. Based on the tensor-product model transformation technique, the set of independent HJI-constrained optimization problems for the robust decentralized stochastic $H_{\infty }$ team formation tracking control design is converted into a set of independent linear-matrix-inequality-constrained optimization problems, which can be solved efficiently by the convex optimization methods. Since the robust decentralized stochastic $H_{\infty }$ team formation tracking control can be designed individually, the magnitude of a biped robot team can be easily increased to a very large scale. Finally, a simulation example of decentralized $H_{\infty }$ formation tracking control design for a 30-scale biped robot team is given to validate the effectiveness of the proposed scheme.

Systems Modeling Language (SysML) is an object management group standard for systems-of-systems engineering. It enables the description of complex system models; however, it cannot effectively support all system engineering activities. For instance, system performance evaluation is usually performed via simulation. In this case, the transformation of SysML system models to executable simulation models for specific simulation methodologies and tools is required. Model transformation is a key component for addressing the challenges of seamless integration of SysML model simulation in model-based system engineering. In this paper, we explore a declarative approach, based on the query/view/transformation-relations (QVT-R) standard, for the transformation of SysML models to executable simulation models, fully adhering model-driven architecture (MDA) concepts. It is supported by a framework implemented to provide executable simulation model and code generation. Methodological guidelines, for the effective use of a declarative language as QVT-R, for model transformation, are provided, emphasizing the utilization of existing domain-specific SysML profiles, as well as executable simulation library components. The experience obtained from two different domains, namely, enterprise information and railway transportation systems, modeled as systems-of-systems via SysML, is discussed, based on a quantitative analysis of the respective QVT-R transformations.

Model transformations play an essential role in most model-driven software projects. As the size and complexity of model transformations increase, their reuse, evolution and maintenance become a challenge. This work further details the Model Transformation TEst Specification (MoTES) approach, which leverages contract-based model testing techniques to assist engineers in model transformation evolution and repairing. The main novelty of our approach is to use contract-based model transformation testing as a foundation to derive suggestions of concrete adaptation actions. MoTES uses contracts to specify the expected behaviour of the model transformation under test. These contracts are transformed into model transformations which act as oracles on input–output model pairs, previously generated by executing the transformation under test on provided input models. By further processing, the oracles’ output model, precision and recall metrics are calculated for every output pattern (testing results). These metrics are then categorised to increase the user’s ability to interpret and act on them. The MoTES approach defines 8 cases for precision and recall values classification (test result cases). As traceability information is retained from transformation rules to each output pattern, it is possible to classify each transformation rule involved according to its impact on the metrics, e.g. the number of true positives generated. The MoTES approach defines 37 cases for these classifications, with each one linked to a particular (abstract) action suggested on a rule, such as relaxation of the rules. A comprehensive evaluation of this approach is also presented, consisting of three case studies. Two previous case studies performed over two model transformations (UML2ER and E2M) are replicated to contrast MoTES with an existing model transformation fault localisation approach. An additional case study presents how MoTES helps with the evolution of an existing model transformation in the context of a reverse engineering project. Main evaluation results show that our approach can not only detect the errors introduced in the transformations but also localise the faulty rule and suggest the proper repair actions, which significantly reduce testers’ effort. From a quantitative perspective, in the third case study, MoTES was able to indicate one faulty rule from 19 possibilities for each result case and suggest one or two repair actions from 6 possibilities for each faulty rule.

This paper is concerned with the problem of fault detection and consensus control via event-triggered scheme for a class of linear multi-agent systems subject to external disturbances. For the network of multi-agent systems with unknown faults and disturbances, the event-triggered consensus protocol and observer-based fault detection filter are designed simultaneously. Through the model transformation and decomposition, the specific design problem can be transformed into a multi-objective optimization problem by using a mixed H ∞ / H − method. Based on the Lyapunov-Krasovskii Theory and Projection Lemma, some sufficient conditions, which ensure the decomposed system is not only asymptotically stable, but also satisfies the prescribed optimization performance constraints, are derived in the form of linear matrix inequalities. Finally, two simulation examples are provided to verify the practicality and validity of the theoretical results.

This paper presents the application of the tensor product (TP)‐based model transformation approach to produce Tower CRrane (TCR) systems models. The modeling approach starts with a nonline...

Model transformation is an effective technique to produce target models from source models. Most transformation approaches focus on generating a single target model from a given source model. However, there are situations where a collection of possible target models is preferred over a single one. Such situations arise when some choices cannot be encoded in the transformation. Then, search techniques can be used to help find a target model having specific properties. In this paper, we present an approach that combines model transformation and constraint programming to generate explorable sets of models. We extend previous work by adding support for multiple solvers, as well as extending ATL, a declarative transformation language used to write such transformations. We evaluate our approach and language on a task scheduling case study including both scheduling constraints and schedule visualization.

As the next step in the development of intelligent computing systems is the addition of human expertise and knowledge, it is a priority to build strong computable and well-documented knowledge bases. Ontologies partially respond to this challenge by providing formalisms for knowledge representation. However, one major remaining task is the population of these ontologies with concrete application. Based on Model-Driven Engineering principles, a generic metamodel for the extraction of heterogeneous data is presented in this article. The metamodel has been designed with two objectives, namely (1) the need of genericity regarding the source of collected pieces of knowledge and (2) the intent to stick to a structure close to an ontological structure. As well, an example of instantiation of the metamodel for textual data in chemistry domain and an insight of how this metamodel could be integrated in a larger automated domain independent ontology population framework are given.

Virtualization technology allows service providers to operate data centers in a cost-effective and scalable manner. The data center network (substrate network) and the applications executed in the data center (virtual networks) are often modeled as graphs. The nodes of the graphs represent (physical or virtual) servers and switches, and the edges represent communication links. Nodes and links are annotated with the provided and required resources (e.g., memory and bandwidth). The NP-hard virtual network embedding (VNE) problem deals with the embedding of a set of virtual networks to the substrate network such that (i) all (resource) constraints of the substrate network are fulfilled, and (ii) an objective is optimized (e.g., minimizing the communication costs). The existing two-step highly customizable model-driven virtual network embedding (MdVNE) approach combines model transformation (MT) and integer linear programming (ILP) techniques to solve the VNE problem based on a declarative specification. MdVNE generates element mapping candidates from an MT specification and identifies an optimal and correct embeddings using an ILP solver. In the past, developers created the MT and ILP specifications manually and needed to ensure carefully that both are compatible and respect the problem description. In this article, we present a novel construction methodology for synthesizing the MT and ILP specification from a given declarative model-based VNE problem description. This problem description consists of a metamodel for substrate and virtual networks, additional OCL constraints, and an objective function that assigns costs to a given model. This methodology ensures that the derived embeddings are correct w.r.t. the metamodel and the OCL constraints, and optimal w.r.t. the optimization goal. The novel model-based VNE specification is applicable to different network domains, environments, and constraints. Thus, the construction methodology allows to automate most of the steps to realize a correct and optimal VNE algorithm compared to a hand-crafted VNE implementation. Furthermore, the simulative evaluation confirms that using MT techniques reduces the time for solving the VNE problem considerably in comparison with a purely ILP-based approach.

Model transformation plays an important role in developing software systems using the model-driven engineering paradigm. Examples of applications of model transformation include forward engineering, reverse engineering of code into models, and refactoring. Poor-quality model transformation code is costly and hard to maintain. There is a need to develop techniques and tools that can support transformation engineers in designing high-quality model transformations. The goal of this paper is to present a process, called MUPPIT (method for using proper patterns in model transformations), which can be used by transformation engineers to improve the quality of model transformations by detecting anti-patterns in the transformations and automatically applying pattern solutions. MUPPIT consists of four phases: (1) identifying a transformation anti-pattern, (2) proposing a pattern-solution, (3) applying the pattern-solution, and (4) evaluating the transformation model. MUPPIT takes a transformation design model (TDM), which is a representation of the given transformation, to search for the presence of an anti-pattern of interest. If found, MUPPIT proposes a pattern solution from a catalogue of patterns to the transformation engineer. The application of the pattern solution results in the restructuring of the TDM. While MUPPIT, as a process, is independent of any transformation language and transformation engineering framework, we have implemented an instance of it as a tool using transML and MeTAGeM, which support exogenous transformations using rule-based transformation and OCL-based languages such as ATL and ETL. We evaluate MUPPIT through a number of case studies in which we show how MUPPIT can detect four anti-patterns and propose the corresponding pattern solutions. We also evaluate MUPPIT by collecting a number of metrics to assess the quality of the resulting transformations. The results show that MUPPIT optimizes the transformations by improving reusability, modularity, simplicity, and maintainability, as well as decreasing the complexity. MUPPIT can help transformation engineers to produce high-quality transformations using a pattern-based approach. An immediate future direction would be to experiment with more anti-patterns and pattern solutions. Moreover, we need to implement MUPPIT using other transformation engineering frameworks.

Praxeme is an enterprise methodology that combines the two approaches SOA and MDA to build an information system. It is based on the ideology of separating the business concern into a homogeneous set called "aspect" to better control the usual complexity of a system. The instantiation of the ReLEL requirements model in the Praxeme methodology is an interesting approach to improve the quality of the software development process because it not only allows to specify the user requirements but also to represent the very precise conceptual level of the future system to be designed. Therefore, this article deals with the automatic generation of SOAP web services that represent the software aspect of the Praxeme methodology from the intentional aspect specified by the ReLEL requirements model. To achieve this, we proceeded in two steps, namely the proposal of the rules for deriving the Praxeme Logical Factory Model (logical aspect) into a Web Service Description Language model or WSDL (software aspect) classified as Model to Model Transformation (M2M) in the MDA approach and then the proposal of the rules for translating the WSDL model into a WSDL document known as Model to Text Translation (M2T). The result obtained from the approach proposed in this paper is a WSDL file which is an XML language allowing the complete description of a Web service. We used ATL for the implementation of the M2M approach transformation rules and then the Acceleo template engine for the translation of the M2T.

For the control of a quadrotor unmanned aerial vehicle, the strong nonlinearities, coupling, and underactuated problem in both positioning and attitude systems of the quadrotor are major challenging issues to be solved. In this article, a discrete-time adaptive dynamic surface control (DSC) scheme for the quadrotor is proposed to obtain a satisfactory tracking performance. The nonlinearities and couplings are overcome by employing the designed robust adaptive DSC nonlinear control method. The underactuated problem is overcome by solving the designed adaptive neural control equations. Also, different from the continuous-time control scheme, the discrete-time control is more suitable for the computer and network control in practicable cases. Furthermore, the digital first-order low-pass filters are constructed to predict the future virtual control signal in the backstepping method, leading to the avoidance of the model transformation problem in the discrete-time backstepping method.

In the early phases of the software development process, specifications are mostly written in a natural language rather than formal models, which is not supported by the Model Driven Architecture (MDA). For this reason, the Semantic of Business Vocabulary and Rules (SBVR) is proposed by the Object Management Group to represent the textual specifications in a language comprehensible by both of humans and machines, to facilitate its integration in the MDA lifecycle. However, businesspeople are usually not familiar with SBVR standard. In this paper we present an approach to automatically transform textual business rules to an SBVR model, to facilitate its integration in nowadays information technology infrastructures. Our approach is distinguished from existing works in that it uses an in-depth Natural Language Processing to extract a more comprehensible SBVR model that includes the semantic formulation of each business rule statement, coupled with a Terminological Dictionary of extracted concepts, to which we have added further specifications such as definitions and synonyms. The evaluation of our approach shows that for three sets of business rules statements taken from different domains, we could generate the correct meaning with an average of F1-score exceeding 87%.

Interface and interaction design take up most of the times in software creation. Human Computer Interaction (HCI) is mainly the best way to interact with a computer. During software development, class diagram is the only required step and process to design an information system according to UML notation. In addition, creating class diagram is a mandatory activity during the software creation process. The aim of this paper is to automatically generate the HCI mockup from class diagram to make easy and extremely fast software design. For example, the SEF (Schema d’Enchainement de Fenetre), is an interface model allowing to create a new interface mockup. It offers more widgets to design the HCI. And MACAO (Methode d’Analyse et de Conception d’Applications Orientees-objets) is one of the methods which helps computer scientist to easily create software. The model transformation is based on Model Driven Engineering (MDE). We use UML notation to design the class diagrams. We also adopt MDA architecture to create the model-based transformation process. Transformation rules are created using Atlas Transformation Language (ATL) to automatically generate a specific interface from the class diagram.

The ever-increasing number of mobile platforms constitutes a challenge for application developers, who must develop efficient mobile applications for multiple platforms. Recently, a specific interest is being taken in the Model Based User Interface Development (MBUID) by Software Engineering Community. In such paradigm, an application’s user interface is obtained by defining models and transformations of those models. This paper aim at adopting MBUID paradigm to address the problem of mobile application development. As such, we propose a new approach and its support system for the automatic generation of mobile user interfaces. The approach and the system are based on a set of standards and relevant technologies such as EMF, GMF, ATL, and Xpand. A case study is presented, in the paper, with the aim of verifying the usefulness of this approach.

Parallel scheduling of multiple real-time applications onto heterogeneous processors is needed in the emerging embedded systems such as self-driving cars, smart cameras, and smartphones. Assuming that an embedded application is specified as a synchronous dataflow (SDF) graph or its extension, we propose a novel parallel scheduling methodology based on an evolutionary algorithm where the mapping of tasks onto processors is evolved to optimize a given objective function in an iterative fashion. In each iteration, we use an existing worst-case response time (WCRT) analysis tool to check if all applications satisfy their real-time requirements by translating each SDF graph into a directed acyclic graph (DAG) that is assumed in the WCRT analysis tool. Since the WCRT analysis must be performed in each iteration of evolution, we propose a clustering technique to reduce drastically the analysis time that depends on the number of nodes and their dependency. We formally prove that the proposed clustering technique does not change the estimated WCRT of each application. The effectiveness of the proposed scheduling methodology with the clustering technique is verified with extensive experiments using real-life benchmarks, randomly generated graphs, and the comparison with the existing technique.

The wide application of Cyber Physical System (CPS) makes the security of CPS more and more concerned. As the key factors affecting the safety of CPS, space and time have also become the current research hotspot. The space and time safety of CPS requires that CPS arrives at the specified place at the specified time, time and space should meet the safety requirements of the CPS in the current CPS environment. We call the behavior space-time compositions. In order to solve the problem that CPS lacks the method of modeling and verification of space-time compositions, a hybrid Architecture Analysis & Design Language (AADL) modeling and model transformation method for CPS space-time compositions verification is proposed. Firstly, space-time description capability is extended in the AADL behavior annex and Hybrid AADL (HAADL) is proposed. Secondly, differential equations and space-time compositions vector are introduced in Process Algebra to propose Hybrid Space-Time Communication Sequential Processes (HS-TCSP). Furthermore, the Hybrid AADL is transformed to HS-TCSP. Finally, an example of an aircraft collision avoidance system is used to verify the effectiveness of the method.

Customer relationship management - CRM systems aim to increase customer satisfaction and loyalty to the company through actions that can be performed by monitoring and analyzing customer behaviours for companies. In these systems, the data obtained from different sources such as sales process, service, and call center are interpreted by the CRM experts as a whole, and the necessary action is taken for the customer. With the rapid progress in information technologies, the diversity of channels that are used to collect data, the size and dynamism of the data have increased. This situation has made it impossible for experts to wholly interpret big-size data from a wide variety of sources in a short period of time. In the CRM area, there is a need for technologies that automatically integrate the data obtained from several sources and can interpret it semantically. In this study, an ontology-based approach is proposed, which allows automatic semantic interpretations on the data obtained from different sources. Based on the proposed approach, a tool has been developed that can unify data from different CRM systems in a common format and make customer-centric interpretations of this data. The tool continuously monitors the systems it is integrated with, and when it detects the conditions defined by the users on the data, it can automatically perform the actions determined by the users. The tool developed was experienced by integrating a CRM system of a company and the evaluation results obtained in this process were discussed.

By providing a consolidated access point to information of devices and systems, digital twins enable new, data-intensive use cases for the industrial internet of things (IIoT) like predictive plant and product design. A digital twin is a digital representation of an entity, which is sufficient to meet the requirements of a set of use cases. However, the lack of interoperability between the digital twins of different companies hinders use cases that require information exchange between different organizations. Achieving interoperability among digital twins requires transforming the included information to other formats. In this paper, we present requirements as well as a solution to enable interoperable digital twins by flexibly transforming their information models. The solution enables file- and API-based information exchange of comprehensive information models in a bidirectional way. We illustrate how we applied our solution to a real-world application example in an industrial context by transforming ABB Ability™ digital twins to the asset administration shell format. We show that our customizable transformation system paves the way for on-demand interoperability and thereby enables advanced use cases in the IIoT. This includes smart use cases that connect industries as well as artificial intelligence in industry.

This paper considers the design of output tracking and feedback controllers for nonlinear stochastic systems. The system status cannot be measured. The studied system contains nonlinear state functions, noise disturbances and time delays. We use the free weight matrix method to avoid the conservatism caused by the use of model transformation or cross-term bounded techniques. Based on the Lyapunov-Krasovskii functional method, we propose an output tracking and feedback controller design method based on linear matrix inequality (LMI). Numerical examples show the validity of the obtained results.

Cyber-physical systems (CPSs) are becoming increasingly important in safety-critical systems. Particular risk analysis (PRA) is an essential step in the safety assessment process to guarantee the quality of a system in the early phase of system development. Human factors like the physical environment are the most important part of particular risk assessment. Therefore, it is necessary to analyze the safety of the system considering human factor and physical factor. In this paper, we propose a new particular risk model (PRM) to improve the modeling ability of the Architecture Analysis and Design Language (AADL). An architecture-based PRA method is presented to support safety assessment for the AADL model of a cyber-physical system. To simulate the PRM with the proposed PRA method, model transformation from PRM to a deterministic and stochastic Petri net model is implemented. Finally, a case study on the power grid system of CPS is modeled and analyzed using the proposed method.

Background: In model-driven development, model transformation transforms one model to another between different phases of software engineering. In model transformation, metamodel plays a vital role which defines the abstract syntax of models and the interrelationship between their elements. A unified metamodel defines an abstract syntax for both source and target models when they share core elements. Theoretical approaches define language and platform independent representation of models in software engineering. This paper investigates the theoretical foundation to this unified meta-modelling for their consistent transformation. Objective: This paper aims to define the formal foundations to the unified metamodel for generating implementation from design specifications and model reusability. Method: In this paper, the study considers transformation from design to implementation and vice versa using theoretical foundations to build a verified software system. Results: The related tools provide a formal representation of the design phase for verification purpose. Our approach provides a set-theoretical foundation to the unified metamodel for model transformation from USE (UML/OCL) to Spec#. In other words, our approach defines the formal foundation to define a model which consists of all the required properties for verification at the design and implementation phase. Conclusion: This paper introduced a new set of the theoretical framework which acts as an interface between the design and implementation to generate verified software systems.

Self-adaptive software (SAS) is gaining popularity as it can reconfigure itself in response to the dynamic changes in the operational context or itself. However, early modeling and formal analysis of SAS systems becomes increasingly difficult, as the system scale and complexity is rapidly increasing. To tackle the modeling difficulty of SAS systems, we present a refinement-based modeling and verification approach called EasyModel. EasyModel integrates the intuitive Unified Modeling Language (UML) model with the stepwise refinement Event-B model. Concretely, EasyModel: 1) creates a UML profile called AdaptML that provides an explicit description of SAS characteristics, 2) proposes a refinement modeling mechanism for SAS systems that can deal with system modeling complexity, 3) offers a model transformation approach and bridges the gap between the design model and the formal model of SAS systems, and 4) provides an efficient way to verify and guarantee the correct behaviour of SAS systems. To validate EasyModel, we present an example application and a subject-based experiment. The results demonstrate that EasyModel can effectively reduce the modeling and formal verification difficulty of SAS systems, and can incorporate the intuitive merit of UML and the correct-by-construction merit of Event-B.

The QVT-Relations (QVT-R) model transformation language is an OMG standard notation for model transformation specification. It is highly declarative and supports (in principle) bidirectional (bx) transformation specification. However, there are many unclear or unsatisfactory aspects to its semantics, which is not precisely defined in the standard. UML-RSDS is an executable subset of UML and OCL. It has a precise mathematical semantics and criteria for ensuring correctness of applications (including model transformations) by construction. There is extensive tool support for verification and for production of 3GL code in multiple languages (Java, C#, C++, C, Swift and Python). In this paper, we define a translation from QVT-R into UML-RSDS, which provides a logically oriented semantics for QVT-R, aligned with the RelToCore mapping semantics in the QVT standard. The translation includes variation points to enable specialised semantics to be selected in particular transformation cases. The translation provides a basis for verification and static analysis of QVT-R specifications and also enables the production of efficient code implementations of QVT-R specifications. We evaluate the approach by applying it to solve benchmark examples of bx.

When model transformations are used to implement consistency relations between very large models, incrementality plays a cornerstone role in detecting and resolving inconsistencies efficiently when models are updated. Given a directed consistency relation between two models, the problem studied in this work consists in propagating model changes from a source model to a target model in order to ensure consistency while minimizing computational costs. The mechanism that enforces such consistency is called consistency maintainer and, in this context, its scalability is a required non-functional requirement. State-of-the-art model transformation engines with support for incrementality normally rely on an observer pattern for linking model changes, also known as deltas, to the application of model transformation rules, in so-called dependencies, at run time. These model changes can then be propagated along an already executed model transformation. Only a few approaches to model transformation provide domain-specific languages for representing and storing model changes in order to enable their use in asynchronous, event-based execution environments. The principal contribution of this work is the design of a forward change propagation mechanism for incremental execution of model transformations, which decouples dependency tracking from change propagation using two innovations. First, the observer pattern-based model is replaced with dependency injection, decoupling domain models from consistency maintainers. Second, a standardized representation of model changes is reused, enabling interoperability with EMF-compliant tools, both for defining model changes and for processing them asynchronously. This procedure has been implemented in a model transformation engine, whose performance has been evaluated experimentally using the VIATRA CPS benchmark. In the experiments performed, the new transformation engine shows gains in the form of several orders of magnitude in the initial phase of the incremental execution of the benchmark model transformation and change propagation is performed in real time for those model sizes that are processable by other tools and, in addition, is able to process much larger models.

UML profiles offer an intuitive way for developers to build domain-specific modelling languages by reusing and extending UML concepts. Eclipse Papyrus is a powerful open-source UML modelling tool which supports UML profiling. However, with power comes complexity, implementing non-trivial UML profiles and their supporting editors in Papyrus typically requires the developers to handcraft and maintain a number of interconnected models through a loosely guided, labour-intensive and error-prone process. We demonstrate how metamodel annotations and model transformation techniques can help manage the complexity of Papyrus in the creation of UML profiles and their supporting editors. We presentJorvik, an open-source tool that implements the proposed approach. We illustrate its functionality with examples, and we evaluate our approach by comparing it against manual UML profile specification and editor implementation using a non-trivial enterprise modelling language (Archimate) as a case study. We also perform a user study in which developers are asked to produce identical editors using both Papyrus andJorvikdemonstrating the substantial productivity and maintainability benefits thatJorvikdelivers.

In this paper, we introduced a recently developed image-based model alignment technique for 3D reconstruction of large-scale indoor corridors. The proposed participatory model alignment technique enables crowd source single image-based modeling since it allows various participants to incorporate their images taken from different cameras for large-scale indoor mapping. This technique is robust against changes of camera orientation and prevents miss-association of a newly generated 3D model to the previously integrated models. To investigate the possibility of aligning two individual 3D models, their respective corridor topological graphs must match, and they need to geometrically transform into the same object space. Here 3D affine transformation is applied, and the transformation parameters are estimated through corresponding vertices of both 3D models. Having integrated two models in the same 3D space, they will be back projected into the image space for evaluation using Direct Linear Transformation. Note that the proposed method performs layout model matching in image space and considers information including layout topology and geometry as well as image information to address model alignment. The advantages of using layout information in the proposed alignment technique are twofold. First, a metric constraint is imposed to insure topological model consistency and balance 3D models scale issues. Second, it will reduce alignment ambiguity related to indoor corridor scenes, where the scene is enriched with multiple structural elements including various corridors junctions. To evaluate the performance of the proposed method, we have performed the experiments on a data set collected from Ross building corridors at York University. This dataset includes single images captured by a handheld wide-angle camera. The obtained results present the ability of the proposed method in alignment of single image-based 3D models while producing limited geometric errors.

International audience; Model checking is an effective way to verify behaviours of an agent-based simulation system. Three behaviours are analysed: operational, control, and global behaviours. Global behaviours of a system emerge from operational behaviours of local components regulated by control behaviours of the system. The previous works principally focus on verifying the system from the operational point of view (operational behaviour). The satisfaction of the global behaviour of the system conforming to the control behaviour has not been investigated. Thus, in this paper, we propose a more complete approach for verifying global and operational behaviours of systems. To do so, these three behaviours are firstly formalized by automata-based techniques. The meta-transformation between automata theories and Kripke structure is then provided , in order to illustrate the feasibility for the model transformation between the agent-based simulation model and Kripke structure based model. Then, a mapping between the models is proposed. Subsequently, the global behaviour of the system is verified by the properties extracted from the control behaviour and the operational behaviour is checked by general system performance properties (e.g. safety, deadlock freedom). Finally, a case study on the simulation system for aircraft maintenance has been carried out. A counterexample of signals sending between Flight agent and Plane agent has been produced by NuSMV model checker. Modifications for the NuSMV model and agent-based simulation model have been performed. The experiment results show that 9% out of 19% of flights have been changed to be serviceable. behaviours and operational behaviours; Model transformation.

In rule-based approaches, a model transformation definition tells how an instance of a source metamodel should be transformed to an instance of a target metamodel. As these metamodels undergo changes, model transformations defined over these metamodels may get out of sync. Restoring conformance between model transformations and the metamodels is a complex and error-prone task. In this paper, we propose a formal approach to automatically co-evolve model transformations according to the evolution of the metamodels. The approach is based on encoding the model transformation definition as a query-retyping combination and the evolution of the metamodels as applications of graph transformation rules. These rules are used to obtain an evolved query over the evolved metamodel together with a new retyping from the target metamodel. We will identify the criteria which need to be fulfilled in order to make this automatic co-evolution possible. We provide a tool support for this procedure, in which, from a traceability model that represents the original model transformation definition, we derive a co-evolved traceability model that represents the evolved transformation definition. Moreover, we use a case study to evaluate the approach with a set of commonly performed metamodel evolutions.

Model transformations play an important role in the evolution of systems in various fields such as healthcare, automotive and aerospace industry. Thus, it is important to check the correctness of model transformation programs. Several approaches have been proposed to generate test cases for model transformations based on different coverage criteria (e.g., statements, rules, metamodel elements, etc.). However, the execution of a large number of test cases during the evolution of transformation programs is time-consuming and may include a lot of overlap between the test cases. In this paper, we propose a test case selection approach for model transformations based on multi-objective search. We use the non-dominated sorting genetic algorithm (NSGA-II) to find the best trade-offs between two conflicting objectives: (1) maximize the coverage of rules and (2) minimize the execution time of the selected test cases. We validated our approach on several evolution cases of medium and large ATLAS Transformation Language programs.

Software build systems tackle the problem of building software from sources in a way which is sound (when a build completes successfully, the relations between the generated and source files are as specified) and optimal (only genuinely required rebuilding steps are done). In this paper, we explain and exploit the connection between software build and the megamodel consistency problem. The model-driven development of systems involves multiple models, metamodels and transformations. Transformations—which may be bidirectional—specify, and provide means to enforce, desired “consistency” relationships between models. We can describe the whole configuration using a megamodel. As development proceeds, and various models are modified, we need to be able to restore consistency in the megamodel, so that the consequences of decisions first recorded in one model are appropriately reflected in the others. At the same time, we need to minimise the amount of recomputation needed; in particular, we would like to avoid reapplying a transformation when no relevant changes have occurred in the models it relates. The megamodel consistency problem requires flexibility beyond what is found in conventional software build, because different results are obtained depending on which models are allowed to be modified and on the order and direction of transformation application. In this paper, we propose using an orientation model to make important choices explicit. We show how to extend the formalised build system pluto to provide a means of restoring consistency in a megamodel, that is, in appropriate senses, flexible, sound and optimal.

This paper proposes a tensor product (TP) model transformation-based framework requiring minimal human intuition to numerically reconstruct linear time invariant, Takagi–Sugeno (T–S) fuzzy model-based linear parameter varying and quasi-linear parameter varying representations of state-space models. The proposed framework facilitates the manipulation of the structure of the system matrix, the parameter vector—including state elements—and the vertex systems. The motivation behind this capability is that all of these structural components strongly influence the control design and the resulting control performance. An important feature of the framework is that it is agnostic towards the formulation of the state-space model, i.e., whether it is given using soft-computing-based techniques or closed formulae. The proposed approach is an extension of the TP model-based control design framework and inherits all of its advantageous properties, e.g., it can be easily used to find minimal representations, including the higher order singular value-based canonical form, and it supports the clear formulation of complexity/accuracy tradeoffs and allows for conversions to various types of convex representations, making for a flexible way to manipulate the weighting and antecedent functions. This paper gives examples to show how the framework can be used in a routine-like fashion and to highlight how it can be applied to the problem of finding useful T–S fuzzy model variations of a given model.

Engineering design is one of the most in-demand Building Information Modelling (BIM) uses. Due to efforts required for modifying and preparing an imported model for analysis, the difficulty-to-benefit ratio is low in this BIM use. These preparations are more geared toward modifying an imported model based on the designer’s interpretation of the building information model and including additional engineering information. Automating the interpretation and model transformation process can significantly facilitate information exchanges. The Interpreted Information Exchange (IIE) concept is developed in this study for such automation during model exchanges. A platform is developed and presented in this paper for implementation of this concept. The platform contains procedures and functionalities required for inputting, processing, and exporting IFC information models through automated interpretation processes that implement IIE concept. The platform is especially formulated to be schema-independent to make it compatible with any standard or custom-defined version of IFC.

AADL is widely used to depict the architecture and behavior of real-time safety-critical systems such as avionics and aerospace. The development of these systems has strict requirements for building fault-free systems. Formal verification is frequently applied to verify the critical properties of the systems, such as safety and liveness; however, the formal verification is not supported by AADL. Model transformation is commonly applied to provide formal semantics; hence, the AADL model can be verified by a language that supports formal verification in addition to the ability to cover all AADL model behavior. Event-B, with its proof obligation, is increasingly used to model and verify safety-critical systems. This paper presents the transformation of the AADL model into Event-B, which captures most AADL components and behavioral actions to be effective in the verification of current real-time systems models. Then, we define theorems and invariants of safety and liveness properties to be proven by using the RODIN platform. To demonstrate the efficacy of our method, we model the AADL of movement authority (MA) control of the Chinese Train Control System, transform the AADL model to Event-B and verify its crucial properties.

Applying Model Driven Architecture (MDA) concepts and tools to Multi Agent Systems (MAS) is a topic of great interest in recent years. MDA intends to reduce computer code development effort via model transformations and makes complex systems available and more practical for research. In this work, we propose a model transformation process for a widely used agent-based modeling and simulation tool, RePast Simphony. We adopt SysML for the platform-independent specification of an agent. We provide platform-independent and platform-specific models for an agent model, a mapping between them and a meta-model specification for RePast Flowchart Diagrams. We show the process for a SysML to RePast round-trip model transformation. Our work covers transformations to/from SysML Activity Diagram from/to RePast Flowchart Diagram.

A sequence diagram is a modeling approach for visualizing the behavioral execution of a system. The objective of this research is to investigate the problem of security in a behavioral model (sequence diagram) through the application of model refactoring. We propose detection and correction techniques, empirical evaluation of the proposed techniques and assessment of security improvement in sequence diagrams. The detection of security bad smells is achieved through the adaptation of a genetic algorithm, while correction is accomplished by the model transformation approach. The results show significant detection recall and correction efficacy of the proposed detection and correction approaches, respectively. Our results show that the proposed approach is effective in detecting and correcting bad smells and can improve the security of UML Sequence Diagram.

Models transformation is the most important principle in MDA (model driven architecture).Indeed, two transformation kinds are possible in MDA: CIM (computing independent model) to PIM (platform independent model) and PIM to PSM (platform specific model). Most researchers deal with the transformation from PIM to PSM, since several elements are shared between these two levels. However, CIM to PIM transformation is rarely highlighted in research topics since they are two radically different levels. However an approach that ensures a transformation from CIM to PIM up to PSM almost extinct. Indeed, this paper represents a methodology to master model transformation from CIM to PIM up to PSM into MDA. This methodology is instituted on creating a rich CIM, through well-chosen rules, to facilitate transformation to the PIM. However, we establish a good PIM, taking into consideration the three classic modeling views: functional, dynamic and static to expedite transformation to PSM. Our methodology conforms to MDA by respecting the business dimension in CIM, by using BPMN (Business Process Model and Notation) which is the OMG (Object Management Group) standard for modeling business process. Thereby, we used UML (Unified Modeling Language) models in PIM level, because UML is recommended by MDA in this level. Indeed, we use IFML (Interaction Flow Modeling Language) that is OMG standard for representing web interface model in PSM.

Safety analysis is often performed independent of the system design life cycle, leading to inconsistency between the system design and the safety artifact. Additionally, the process of generating safety artifacts is manual, time-consuming, and error-prone. As a result, safety analysis often requires re- work, is expensive, and increases system development time. Several model-based systems engineering (MBSE) approaches have been developed to automatically generate certain safety artifacts. However, these approaches only cover part of the system design and safety life cycle. To truly leverage the benefits of MBSE, system design must be undertaken together with safety analysis for the entire life cycle, and multiple safety artifacts must be generated from the same model. Moreover, MBSE approaches that require a model transformation between the system design and the safety model suffer from the inability to automatically reflect changes made to a safety artifact in the system and the safety model. This paper presents a framework to integrate the entire system design and safety life cycle using an MBSE approach. Both the system design and the safety data are captured in a single SysML model, from which safety artifacts such as failure modes and effects analysis (FMEA) tables and fault trees are automatically generated. This framework ensures consistency between the system design and the safety analysis by requiring no model transformation, thus reducing the resources required for safety analysis. The proposed Integrated System Design and Safety (ISDS) framework comprises three phases that together cover the entire system design and safety life cycle. In this paper, the application of Phase 1 of the framework to a real-world case study is demonstrated.