Automatic Model Transformation Research Articles

Modeling and Verification of Natural Language Requirements based on States and Modes

The relationship between states (status of a system) and modes (capabilities of a system) used to describe system requirements is often poorly defined. The unclear relationship could make systems of interest out of control because of the out of boundaries of the systems caused by the newly added modes. Formally modeling and verifying requirements can clarify the relationship, making the system safer. To this end, an innovative approach to analyzing requirements is proposed. The MoSt language (a Domain Specific Language implemented on the Xtext framework) is firstly designed for requirements modeling and a model validator is realized to check requirements statically. A code generator is then provided to realize the automatic model transformation from the MoSt model to a NuSMV model, laying the foundation for the dynamic checks of requirements through symbolic model checking. Next, a NuSMV runner is designed to connect the NuSMV with the validator to automate the whole dynamic checks. The grammar, the model validator, the code generator, and the NuSMV runner are finally integrated into a publicly available Eclipse-based tool. Two case studies have been employed to illustrate the feasibility of our approach. For each case study, we injected 14 errors. The results show that the static and dynamic checks can successfully detect all the errors.

DBSCAN-based line density clustering algorithm for CAD architectural drawings

In the traditional architecture industry, architects often need to convert CAD drawings into BIM in order to express the final effect of the building more concretely and to understand whether the design of each profession is reasonable after the drawings are completed. The whole modeling process is boring and tedious, and due to human fatigue, the final result is prone to problems, which eventually leads to failure to meet expectations. In order to free architects from the tedious task of model transformation, companies have designed software for automatic model transformation using computers. The core of the software design is related to computational geometry. Line segment clustering is one of the elements of computational geometry and a frequent problem in programming. Appropriate clustering of line segments can often bring convenience to the problem. This paper combines the basic idea of the DBSCAN algorithm, improves the shortcomings of DBSCAN algorithm in dealing with line segment clustering, and proposes a density-based line clustering algorithm with shapely library as a tool. The algorithm is highly interpretable, and the method performs well and efficiently in the test of actual drawings, whether to group the line segments or to find the target line segments that meet the conditions, which provides convenience for the subsequent calculation.

MoTrans-BDI: Leveraging the Beliefs-Desires-Intentions agent architecture for collaborative model transformation by example

Due to the growing interest in model-driven system development techniques, the efficient design of automated model transformations between heterogeneous models has become a major challenge in software development. While a number of specialized languages have been proposed, aiming at specifying model transformations, there is currently no matured foundation for specifying transformations between such models that are based on designers/experts collaboration in order to propose a solution that satisfies users’ requirements and application constraints. This transformation process is a complex task and must emulate how designers and experts with different perspectives behave and reflect about model transformations. In this paper, we propose a framework based on a novel approach for the specification and design of model transformations called MoTrans-BDI, which leverages Evolutionary Multi-Agent System (EMAS) to simulate designers’ expertise for the transformation of models. Our approach is based on the Belief-Desire-Intention (BDI) agent model and the Contract Net Protocol where agents’ beliefs feed from a series of transformation examples. The emphasis of using the specific model is the opportunity to produce a target model that may be composed of parts from different experts’ designs. We first experimentally evaluate MoTrans-BDI on twelve handmade UML2REL model transformation problems. All types of agents are able to produce perfect target models compared to human experts’ collaboratively-produced target models. Second, we empirically evaluate MoTrans-BDI’s proposal in terms of response time on Star Schema Benchmark (SSB) queries. An application of MoTrans-BDI in the case of UML2REL transformation is performed to stress and highlight the transformation process steps.

Automatic model transformation on multi-platform system development with model driven architecture approach

Several difficulties commonly arise during the software development process. Among them are the lengthy technical process of developing a system, the limited number and technical capabilities of human resources, the possibility of bugs and errors during the testing and implementation phase, dynamic and frequently changing user requirements, and the need for a system that supports multi-platforms. Rapid application development (RAD) is the software development life cycle (SDLC) that emphasizes the production of a prototype in a short amount of time (30-90 days). This study discovered that implementing a model-driven architecture (MDA) approach into the RAD method can accelerate the model design and prototyping stages. The goal is to accelerate the SDLC process. It took roughly five weeks to construct the system by applying all of the RAD stages. This time frame does not include iteration and the cutover procedure. During the prototype test, there were no errors with the create, read, update, and delete (CRUD) procedure. It was demonstrated that automatic transformation in MDA can shorten the RAD phases for designing the model and developing an early prototype, reduce code errors in standard processes like CRUD, and construct a system that supports multi-platform.

Automatic model transformation on multi-platform system development with model driven architecture approach

Several difficulties commonly arise during the software development process. Among them are the lengthy technical process of developing a system, the limited number and technical capabilities of human resources, the possibility of bugs and errors during the testing and implementation phase, dynamic and frequently changing user requirements, and the need for a system that supports multi-platforms. Rapid application development (RAD) is the software development life cycle (SDLC) that emphasizes the production of a prototype in a short amount of time (30-90 days). This study discovered that implementing a model-driven architecture (MDA) approach into the RAD method can accelerate the model design and prototyping stages. The goal is to accelerate the SDLC process. It took roughly five weeks to construct the system by applying all of the RAD stages. This time frame does not include iteration and the cutover procedure. During the prototype test, there were no errors with the create, read, update, and delete (CRUD) procedure. It was demonstrated that automatic transformation in MDA can shorten the RAD phases for designing the model and developing an early prototype, reduce code errors in standard processes like CRUD, and construct a system that supports multi-platform.

From quantitative SBML models to Boolean networks

Modelling complex biological systems is necessary for their study and understanding. Biomodels is a repository of peer-reviewed models represented in the Systems Biology Markup Language (SBML). Most of these models are quantitative, but in some cases, qualitative models—such as Boolean networks (BNs)—are better suited. This paper focuses on the automatic transformation of quantitative SBML models to Boolean networks. We propose SBML2BN, a pipeline dedicated to this task. Our approach takes advantage of several SBML elements (reactions, rules, events) as well as a numerical simulation of the concentration of the species over time to constrain both the structure and the dynamics of the Boolean networks to synthesise. Finding all the BNs complying with the given structure and dynamics was formalised as an optimisation problem solved in the answer-set programming framework. We run SBML2BN on more than 200 quantitative SBML models, and we provide evidence that one can automatically construct Boolean networks which are compatible with the structure and the dynamics of an SBML model. In case the SBML model includes rules or events, we also show how the evaluation criteria are impacted when taking these elements into account.

Automatic Bridge between BPMN Models and UML Activity Diagrams based on Graph Transformation

Model Driven Engineering (MDE) provides available tools, concepts and languages to create and transform models. One of the most important successes of MDE is model transformation; it permits transforming models used by one community to equivalent models used by another one. Moreover, each community of developers has its own tools for verification, testing and test case generation. Hence, a developer of one community who moves to work with another community needs a transformation process from the second community to (his/her) own community and vice versa. Therefore, the target community can benefit from the expertise of the source one and the developers do not begin from zero.In this context, we propose in this paper an automatic transformation to create a bridge between the BPMN and UML communities. We propose an approach and a visual tool for the automatic transformation of BPMN models to UML Activity Diagrams (UML-AD). The proposed approach is based on Meta-Modeling and Graph Transformation, and uses the AToM3 tool. Indeed, we were inspired by the OMG meta-models of BPMN and UML-AD and implemented versions of both meta-models using AToM3. This last allows generating automatically a visual modeling tool for each proposed meta-model. Based on these two meta-models, we propose a graph grammar composed of sixty rules that perform the transformation process. The proposed approach is illustrated through three case studies.

Transforming BPMN Processes to SBVR Process Rules with Deontic Modalities

The Object Management Group (OMG) has put considerable effort into the standardization of various business modeling aspects within the context of model-driven systems development. Indeed, the Business Process Model and Notation (BPMN) is now arguably the most popular process modeling language. At the same time, the Semantics of Business Vocabulary and Business Rules (SBVR), which is a novel and formally sound standard for the specification of virtually any kind of knowledge using controlled natural language, is also gaining its grounds. Nonetheless, the integration between these two very much related standards remains weak. In this paper, we present one such integration effort, namely an approach for the extraction of SBVR process rules from BPMN processes. To accomplish this, we utilized model-to-model transformation technology, which is one of the core features of Model-Driven Architecture. At the core of the presented solution stands a set of model transformation rules and two algorithms specifying the formation of formally defined process rules from process models. Basic implementation aspects, together with the source code of the solution, are also presented in the paper. The experimental results acquired from the automatic model transformation have shown full compliance with the benchmark results and cover the entirety of the specified flow of work defined in the experimental process models. Following this, it is safe to conclude that the set of specified transformation rules and algorithms was sufficient for the given scope of the experiment, providing a solid background for the practical application and future developments of the solution.

Increased efficiency in virtual commissioning with automated model generation based on component libraries

The use of Virtual Commissioning (VC) is becoming increasingly relevant for the engineering of automation systems. VC allows for validating concepts and design solutions in the early phases of product development, thereby improving communication among disciplines, reducing the costs for bug fixing and accelerating the overall engineering process, in particular the commissioning of plants and machines. However, as an additional software tool in engineering, the introduction of VC causes initial training and more importantly continuous extra modelling efforts. An approach to overcome this flaw is the automated generation of VC models based on existing engineering information from the system or domain level - ideally in tandem with the reuse of solution models from previous project. The latter can prove particularly beneficial in the context of modular building-block systems as often pursued in automation engineering.This paper presents a practical implementation of an automated VC model generation solution based on system structure and layout models combined with an object library containing additional model information of the applied automation components. The presented use case addresses VC simulation models of intralogistics warehousing systems where the layout plans provide information about type, position and dimension of predefined subsystems, modules or components which are then being analyzed and merged with additional model information. By means of a specific exporter the assembled model information is being filtered and transferred into the simulation environment via a standard API. Significant time savings could be demonstrated in this use case. Based on these results a generalized framework for more efficient interdisciplinary engineering processes based on automated data exchange as well as automated model transformation and generation has been derived and will be presented along with an outlook on future research activities.

Extension of the Modeling Tool Suite for Development of Embedded Systems for the Space Domain

As code complexity continues to increase, software development methods must support the handling of this complexity and reduce development failures. Model-based systems engineering (MBSE) is a modeling-centered development method that provides support to maintain consistency of different phases of the life cycle. Automatic code generation tools were created to reuse software solutions and design patterns and reduce development errors in the software development process, based on automatic model transformations and code generators. However, the use of these tools requires their adaptation to specific platforms and domains since tools only support certain functionalities. What determines how to approach the design of the system are the functionalities provided by the tools available rather than the user needs. In this paper, we propose a way to extend the elements supported by modelling tool suites for real-time embedded systems for the space domain. This enables developers to have greater flexibility by allowing them to modify their tool suite to fit their needs.

Transformation From CIM to PIM: a Systematic Mapping

Model Driven Architecture (MDA) is the most prominent and accepted methodology based on the Model Driven Development (MDD) principles. MDA includes three abstraction levels: Computer Independent Models (CIM), Platform Independent models (PIM) and Platform specific models (PSM). MDA encourages the automatic transformation of models as a means to increase the speed of the software development process and to prevent human errors. There are plenty of solutions to transform PIMs to PSMs, however the CIM to PIM transformation does not receive a similar attention. In that sense, this paper aims to describe a systematic mapping to analyze the main characteristics of the approaches that deal with the CIM to PIM transformation as well as to discuss research directions stemming out from our analysis. The results of this mapping study could be a valuable information source for the scientific community in order to know the real advances in this topic and to avoid unnecessary effort dealing with problems that have already been addressed. For example, this study yielded the models at the CIM level that have already been transformed into models at the PIM level. Hence, with this information, the researchers could focus their attention on finding solutions to transform those models at CIM level that have not been transformed into models at PIM level. Likewise, this mapping study provides information regarding the technological support of this type of transformation. This information could be useful for those software projects interested to adopt MDA.

Modeling multiple space views for schematic building design using space ontologies and layout transformation operations

Modeling multiple views of spaces involves mapping or transformation between multiple models. Automated model transformation is challenging as semantic and spatial criteria need to be considered. This paper proposes a novel method and data processing pipeline to define space views and semi-automatically transform room-based building data created in BIM authoring systems into multi-view space models. The method is based on space ontologies and their integration with space layout transformation operations. It is used to define a set of functional views that are relevant to schematic building design. An existing space modeling system is extended with the method and data processing pipeline. Results from a validation study show that the method can cover specific semantic and spatial aspects of space views. Both are relevant for consistent model transformation and accurate analysis. Results further show that it is feasible to fully automate data processing steps, except for space classification, which is semi-automated.

Increasing Interpretability of Bayesian Probabilistic Programming Models Through Interactive Representations

Bayesian probabilistic modeling is supported by powerful computational tools like probabilistic programming and efficient Markov Chain Monte Carlo (MCMC) sampling. However, the results of Bayesian inference are challenging for users to interpret in tasks like decision-making under uncertainty or model refinement. Decision-makers need simultaneous insight into both the model's structure and its predictions, including uncertainty in inferred parameters. This enables better assessment of the risk overall possible outcomes compatible with observations and thus more informed decisions. To support this, we see a need for visualization tools that make probabilistic programsinterpretableto reveal the interdependencies in probabilistic models and their inherent uncertainty. We propose the automatic transformation of Bayesian probabilistic models, expressed in a probabilistic programming language, into an interactive graphical representation of the model's structure at varying levels of granularity, with seamless integration of uncertainty visualization. This interactive graphical representation supports the exploration of the prior and posterior distribution of MCMC samples. The interpretability of Bayesian probabilistic programming models is enhanced through the interactive graphical representations, which provide human users with moreinformative, transparent, andexplainableprobabilistic models. We present a concrete implementation that translates probabilistic programs to interactive graphical representations and show illustrative examples for a variety of Bayesian probabilistic models.

Toward Dependable Model-Driven Design of Low-Level Industrial Automation Control Systems

Recent technological advances and manufacturing paradigm evolutions in industrial settings will dramatically increase the complexity of automation control systems. Traditional solutions to the software development of low-level control kernels (e.g., numerical control kernel, motion control kernel, and real-time communication tasks) are unable to cope effectively with such complexity due to an inadequate level of abstraction and challenges for dependability. This article presents a formal semantics integrated model-driven design approach as a holistic solution. A domain-specific modeling language (DSML) is specified based on the adaption of IEC 61 499 architecture, along with the extensions of task model, task-to-resource allocation, and nonfunctional specification. Both formal structural and behavioral semantics of the proposed DSML are then explicitly defined. Design-time formal verification is also achieved by automated model transformations. A metaprogrammable environment is adopted to facilitate flexible modeling, verification, and code generation. A case study is demonstrated on implementing a prototype computer numerical control (CNC) system using the proposed solution. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The low-level automation control system in the modern manufacturing scenarios require more agility while respecting strict timing constraints. Handling such complexity with manual coding is getting harder and less efficient. The DSML and the supporting development environment presented in this article aim to enhance the level of automation, flexibility, and dependability of the whole design process. For the proposed DSML, its syntax is formalized and defined as metamodels, while the semantics is integrated through model annotation and transformation. These definitions are implemented as external rules for a metaprogrammable environment to establish our proposed development tool. The finding and insight from this article can enhance efficiency and dependability during the development of common control kernels, such as CNC kernel and motion controller.

A Configurable Semantic-Based Transformation Method towards Conceptual Models

Conceptual models are built to depict and analyze complex systems. They are made of concepts and relationships among these concepts. In a particular domain, conceptual models are helpful for different stakeholders to reach a clear and unified view of domain problems. However, the process of building conceptual models is time-consuming, tedious, and expertise required. To improve the efficiency of the building process, this paper proposes a configurable semantic-based (semi-) automatic conceptual model transformation methodology (SbACMT) that tries to reuse existing conceptual models to generate new models. SbACMT contains three parts: (i) a configurable semantic relatedness computing method building on the structured linguistic knowledge base “ConceptNet” (SRCM-CNet), (ii) a specific meta-model, which follows the Ecore standard, defines the rules of applying SRCM-CNet to different conceptual models to automatically detect transformation mappings, and (iii) a multistep matching and transformation process that employs SRCM-CNet. A case study is carried out to detail the working mechanism of SbACMT. Furthermore, through a systematically analysis of this case study, we validate the performance of SbACMT. We prove that SbACMT can support the automatic transformation process of conceptual models (e.g., class diagrams). The scalability of SbACMT can be improved by adapting the meta-model and predefined syntax transformation rules.

MSL: A pattern language for engineering self-adaptive systems

In architecture-based self-adaptation of decentralized systems, design patterns have been introduced to ease the design of complex adaptation solutions that usually require the interaction of different MAPE-K (Monitor-Analyze-Plan-Execute over a shared Knowledge) control loops, each dealing with an adaptation concern of the managed system. Such MAPE patterns have been proposed by means of a graphical notation, but without a well-defined way to document them and to express the semantics of components interactions.In this paper, we propose an approach to overcome these limitations. We present a domain-specific language, called MSL for MAPE Specification Language, to define and instantiate MAPE patterns and to give semantics to some semantic variation points of the equivalent graphical notation for MAPE pattern. We also provide a formal semantics of the language by means of self-adaptive Abstract State Machines, an extension of the Abstract State Machines (ASMs) formalism to model self-adaptation. Such semantics definition comes with an automatic transformation of MSL models into formal executable models, and opens to the possibility of performing rigorous analysis (validation w.r.t. the adaptation requirements and verification of adaptation properties) of MSL models. Moreover, we present our current results toward a (long-term) realization of an MSL-centric framework, where MSL is the notation of a modeling front-end, on top of richer and more specific modeling, analysis, and implementation back-end frameworks.As proof of concept of our approach, we show the application of MSL and its formal support to a running case study in the field of home automation, by modeling an adaptive control of a virtual smart home developed with the OpenHAB runtime platform.

A Formalization Model Transformation Approach on Workflow Automatic Execution from CIM Level to PIM Level

Model transformation is a keystone in carrying out model-driven development. Currently, many studies have focused on model transformation, those researches study the automatic transformation from PIM to PSM and from PSM to code, but only few have dealt with how the CIM-level model is automatically mapped onto the PIM-level model. Even though some studies have proposed the semi-automatic transformation from CIM-level model to PIM-level model, only few mechanisms are discussed to protect the consistency between the CIM-level model and the PIM-level model in these researches because notation specification of these CIM-level model and PIM-level model does not contain precise semantics. Focusing on workflow perspective, this paper proposes an automatic model transformation approach, which applies a formal model to define the automatic mapping of the workflow from CIM-level model to PIM-level model. This proposal extends Petri nets model elements to define a bridge model, then we use this bridge model to link the CIM-level model (BPMN) and PIM-level model (SCM) following model-driven approach. The metamodels, the transformation rule and the transformation plug-ins have been defined in Eclipse Modeling Framework. Meanwhile, the plug-ins have been empirically validated by a Travel Agency case study. This study shows that using extended Petri nets model as a bridge model to define an automatic model transformation between CIM-level model and PIM-level model is feasible. This approach by means of formal model can ensure the correctness and completeness of the target model, and it can also maintain the consistency between the source model and target model.

A formal approach to AADL model-based software engineering

Formal methods have become a recommended practice in safety-critical software engineering. To be formally verified, a system should be specified with a specific formalism such as Petri nets, automata and process algebras, which requires a formal expertise and may become complex especially with large systems. In this paper, we report our experience in the formal verification of safety-critical real-time systems. We propose a formal mapping for a real-time task model using the LNT language, and we describe how it is used for the integration of a formal verification phase in an AADL model-based development process. We focus on real-time systems with event-driven tasks, asynchronous communication and preemptive fixed-priority scheduling. We provide a complete tool-chain for the automatic model transformation and formal verification of AADL models. Experimentation illustrates our results with the Flight control system and Line follower robot case studies.

Automatic transformation tools of UML design models from virtual prototypes of multi-jointed robots

Most of robotic companies develop a control programming of multi-jointed robots, which spend too much time to manually adjust the moving functions of the robots. To solve this problem, we adapt the virtual prototyping (VP) to develop the control program of the robotic behaviors. For software engineers, in order for them to easily program this robot, we also apply metamodel mechanism to convert UML models with virtual prototyping model. We propose the automatic model transformation from the virtual prototyping model to UML models, which will then develop coding based on UML models. To prove our mechanism’s efficiency, we implement Robot to UML Translator (RUT) as our transformation rules with ATLAS transformational language. Lastly, we show experimental validation about the consistency of our proposed technique with an example of multi-joined robot prototype models.

An Automated Functional Testing Framework for Context-Aware Applications

In the modern era of mobile computing, context-aware computing is an emerging paradigm due to its widespread applications. Context-aware applications are gaining increasing popularity in our daily lives since these applications can determine and react according to the situational context and help users to enhance usability experience. However, testing these applications is not straightforward since it poses several challenges, such as generating test data, designing context-coupled test cases, and so on. However, the testing process can be automated to a greater extent by employing model-based testing technique for context-aware applications. To achieve this goal, it is necessary to automate model transformation, test data generation, and test case execution processes. In this paper, we propose an approach for behavior modeling of context-aware application by extending the UML activity diagram. We also propose an automated model transformation approach to transform the development model, i.e., extended UML activity diagram into the testing model in the form of function nets. The objective of this paper is to automate the context-coupled test case generation and execution. We propose a functional testing framework for automated execution of keyword-based test cases. Our functional testing framework can reduce the testing time and cost, thus enabling the test engineers to execute more testing cycles to attain a higher degree of test coverage.