Model-based System Development Research Articles

Integrating scenario- and contract-based verification for automated vessels

Scenario-based verification defines the current state of the art for examining a vessel’s control systems for reliability and safety. However, software updates after release can only be covered to a limited extent. To take changes to a deployed system into account, the design and test phase must be harmonized with the operational phase. For all phases, regulatory, technical and safety requirements provide the scope to which the development process and the scenario-based tests need to be aligned and whose specifications the System under Test (SuT) must adhere to during operation. For this reason, a procedure is needed that converts the requirements into a format that can be utilized across all phases and measured in a structured manner comparing the original system to the updated version. This work does so by combining scenario-based verification methods with formal composition and monitoring techniques based on contract-based design into an integrated development approach. It is shown how safety requirements can be transferred into a Verification Descriptor that in turn provides the foundation for the division into model-based system development, contract-based virtual integration testing and a scenario-based test environment. For the entire lifecycle of the System under Test (SuT) to be included, the extended scenario and contract descriptors are carried forward up to the operational phase, such that the previously defined properties of the SuT can be monitored and validated during runtime. The approach is designed alongside a minimal-viable system and evaluated on an actual implementation of a safety-critical maritime LiDAR-based positioning system.

Multi-objective model transformation chain exploration with MOMoT

Context:The increasing complexity of modern systems leads to an increasing amount of artifacts that are used along the model-based software and systems development lifecycle. This also includes model transformations, which serve for mapping models between representations, e.g., for verification and validation purposes. Objectives:Model repositories manage this variety of artifacts and promote reusability, but should also enable the bundling of compatible artifacts. Therefore, model transformations should be reused and arranged into transformation chains to support more complex transformation scenarios. The resulting transformation should correspond to the user’s interest in terms of quality criteria such as model coverage, transformation coverage, and number of transformation steps, thus assembling such chains becomes a multi-objective problem. Methods:A novel multi-objective approach for exploring possible transformation chains residing in model repositories is presented. MOMoT, a model-driven optimization framework, is leveraged to explore the transformation space spanned by the repository. For demonstration, three differently populated repositories are considered. Results:We have extended MOMoT with an exhaustive, multi-objective search that explores the entire model transformation space defined by graph transformation rules, allowing all possible transformation chains to be considered as solution. Accordingly, the optimal solutions were identified in the demonstration cases with negligible computation time. Conclusion:The approach assists modelers when there are multiple chains for transforming an input model to a specified output model to consider. Our evaluation shows that the approach elicits all legitimate transformation chains, thus enabling the modelers to consider trade-offs in view of multiple criteria selection.

Early Validation and Verification of System Behaviour in Model-based Systems Engineering: A Systematic Literature Review

In the Systems Engineering (SE) domain there has been a paradigm shift from document-based to model-based system development artefacts; in fact, new methodologies are emerging to meet the increasing complexity of current systems and the corresponding growing need of digital workflows. In this regard, Model-Based Systems Engineering (MBSE) is considered as a key enabler by many central players of the SE community. MBSE has reached an adequate level of maturity, and there exist documented success stories in its adoption in industry. In particular, one significant benefit of utilising MBSE when compared to the traditional manual and document-centric workflows is that models are available from early phases of systems development; these enable a multitude of analyses prior any implementation effort together with other relevant capabilities, like the automation of development tasks. Nonetheless, it is noticeable there is a lack of a common understanding for how formal analyses for the verification and validation (V&V) of systems behaviour, specifically in the early phases of development, could be placed in an MBSE setting. In this article, we report on the planning, execution, and results of a systematic literature review regarding the early V&V of systems behaviour in the context of model-based systems engineering. The review aims to provide a structured representation of the state of the art with respect to motivations, proposed solutions, and limitations. From an initial set of potentially relevant 701 peer-reviewed publications we selected 149 primary studies, which we analysed according to a rigorous data extraction, analysis, and synthesis process. Based on our results, early V&V has usually the goal of checking the quality of a system design to avoid discovering flaws when parts are being concretely realised; SysML is a de facto standard for describing the system under study, while the solutions for the analyses tend to be varied; also V&V analyses tend to target varied properties with a slight predominance of functional concerns, and following the variation mentioned so far the proposed solutions are largely context specific; the proposed approaches are usually presented without explicit limitations, while when limitations are discussed, readiness of the solutions, handling of analyses simplifications/assumptions, and languages/tools integration are among the most frequently mentioned issues. Based on the survey results and the standard SE practices, we discuss how the current state-of-the-art MBSE supports early V&V of systems behaviour with a special focus on industrial adoption and identify relevant challenges to be researched further.

Evaluating virtualization for fog monitoring of real-time applications in mixed-criticality systems

Technological advances in embedded systems and the advent of fog computing led to improved quality of service of applications of cyber-physical systems. In fact, the deployment of such applications on powerful and heterogeneous embedded systems, such as multiprocessors system-on-chips (MPSoCs), allows them to meet latency requirements and real-time operation. Highly relevant to the industry and our reference case-study, the challenging field of nuclear fusion deploys the aforementioned applications, involving high-frequency control with hard real-time and safety constraints. The use of fog computing and MPSoCs is promising to achieve safety, low latency, and timeliness of such control. Indeed, on one hand, applications designed according to fog computing distribute computation across hierarchically organized and geographically distributed edge devices, enabling timely anomaly detection during high-frequency sampling of time series, and, on the other hand, MPSoCs allow leveraging fog computing and integrating monitoring by deploying tasks on a flexible platform suited for mixed-criticality software, leading to so-called mixed criticality systems (MCSs). However, the integration of such software on the same MPSoC opens challenges related to predictability and reliability guarantees, as tasks interfering with each other when accessing the same shared MPSoC resources may introduce non-deterministic latency, possibly leading to failures on account of deadline overruns. Addressing the design, deployment, and evaluation of MCSs on MPSoCs, we propose a model-based system development process that facilitates the integration of real-time and monitoring software on the same platform by means of a formal notation for modeling the design and deployment of MPSoCs. The proposed notation allows developers to leverage embedded hypervisors for monitoring real-time applications and guaranteeing predictability by isolation of hardware resources. Providing evidence of the feasibility of our system development process and evaluating the industry-relevant class of nuclear fusion applications, we experiment with a safety-critical case-study in the context of the ITER nuclear fusion reactor. Our experimentation involves the design and evaluation of several prototypes deployed as MCSs on a virtualized MPSoC, showing that deployment choices linked to the monitor placement and virtualization configurations (e.g., resource allocation, partitioning, and scheduling policies) can significantly impact the predictability of MCSs in terms of Worst-Case Execution Times and other related metrics.

An Integrated Mutation Analysis Tool (Imat) For Simulink Models and Their Ideal Implementation

Mutation analysis is proving to be an effective approach in detecting the design flaws for safety system designs such as flight control systems or the stall warning systems. The drawback of these analyses is that they are time-consuming and difficult-to-use. This paper discusses about the mutation tool, IMAT, developed in-house for detecting the design flaws of safety critical systems designed in SIMULINK. The IMAT tool is developed as a plug-in to the SIMULINK tool suite and enhances the performance of the model-based development of safety critical systems. Some of the unique features of the tool are ease-of-use, portable, scalable, userfriendly and easy to analyse the reports.

Customer-centric and function-oriented development of mechatronic systems

Successful products at least precisely meet the customers’ expectations and, in the best case, exceed them. To develop successful products, customer expectations must be translated into requirements. With the increasing functionalities of products in recent years, the customers’ expectations regarding product interaction and its behavior in different environmental conditions have also become more extensive. Current approaches of model-based systems engineering (MBSE) enable developing complex mechatronic products seamlessly from requirements to functions and solutions on a parameter level. However, there is a lack of approaches that systematically translate complex customer expectations into functional and design requirements as a starting point for further development.In this contribution we present a method and a corresponding meta-model that allows to systematically formalize the dependencies of different stakeholders and their expectations as well as different environmental conditions and constraints. From these dependencies, operating states are elicited that represent a set of simultaneously valid stakeholder expectations with their corresponding constraints. From these operating states, functional and design requirements are systematically derived as a basis for the model-based design of the system under development. Our meta-model is compatible to the established modeling language SysML, thus, existing approaches for the function-oriented model-based system development can benefit directly from these formally modeled requirements.Our publication signposts the potential for systematic and formal translation of customer expectations into operating states as well as requirements and thus enables a targeted, customer-centric and function-oriented development of mechatronic systems. We applied our method in an interdisciplinary, industrial project using the example of a thermal management system of a battery electric vehicle.

Asmaul Husna Web-Based System: Acquainting the 99 Names of Allah

Web-based systems have had a significant impact on computer and communication technology advancement. Websites are still prevalent in a variety of practices after a long time. As a result, an Islamic learning-oriented website concentrating on Asmaul Husna was formed. This project was created as the topic still requires an engaging and comprehensive informal learning method to fill the need. The website was designed using a Waterfall model-based system development life-cycle methodology. According to the testing results, this website has aided users in learning their topic more openly and at their leisure. By using this website, more people would be able to profit from learning about the subject in their daily lives.

FEEDBACK AGGREGATION ALGORITHMS

Intelligent information systems as well as artificial intelligence systems have a special place in modern information technologies. These industries put a strong emphasis on the development of autonomous software modules that would be able to perform mental work instead of people or at least possess some features of intelligence. Some typical problems, which can be solved this way, include management of complex processes; search for optimal design solutions; credit and investment risk assessment; assessment of the enterprise efficiency; medical diagnostics, data aggregation systems. Thus, an important element of such systems is the knowledge base, i.e. their “memory” (“experience”). To create a knowledge base, it is necessary to determine in what form it will represent knowledge as well as how it will be accumulated, stored and processed to obtain a certain result. Therefore, the presentation of knowledge plays a very important role for artificial intelligence systems and the science of thinking. The main purpose of this field is to develop methods for formalizing knowledge and finding ways of representation, which will enable an effective process of logic inference. To manipulate a variety of real-world knowledge with a computer, it is necessary to solve the problem of modeling it. There are many models of knowledge representation, modification and aggregation with significant differences in architecture, capabilities and means of adding knowledge (logical forms, semantic networks, production rules, frames, etc.). To compare the efficiency of the model of knowledge representation implemented in this paper with the performance of other forms of knowledge representation, the following criteria were used: the level of complexity of the knowledge element; universality (possibility of application for various subject areas); authenticity and clarity of the model; the effectiveness of building a logical conclusion and obtaining new knowledge; the volume of the model in terms of memory for storing the item; convenience of model-based system development.

Formal testing of timed graph transformation systems using metric temporal graph logic

Embedded real-time systems generate state sequences where time elapses between state changes. Ensuring that such systems adhere to a provided specification of admissible or desired behavior is essential. Formal model-based testing is often a suitable cost-effective approach. We introduce an extended version of the formalism of symbolic graphs, which encompasses types as well as attributes, for representing states of dynamic systems. Relying on this extension of symbolic graphs, we present a novel formalism of timed graph transformation systems (TGTSs) that supports the model-based development of dynamic real-time systems at an abstract level where possible state changes and delays are specified by graph transformation rules. We then introduce an extended form of the metric temporal graph logic (MTGL) with increased expressiveness to improve the applicability of MTGL for the specification of timed graph sequences generated by a TGTS. Based on the metric temporal operators of MTGL and its built-in graph binding mechanics, we express properties on the structure and attributes of graphs as well as on the occurrence of graphs over time that are related by their inner structure. We provide formal support for checking whether a single generated timed graph sequence adheres to a provided MTGL specification. Relying on this logical foundation, we develop a testing framework for TGTSs that are specified using MTGL. Lastly, we apply this testing framework to a running example by using our prototypical implementation in the tool AutoGraph.

Application of Physical Function Model to State Estimations of Nonlinear Mechanical Systems

The physical function model has been effectively used for model-based development (MBD) of automobile systems. This research demonstrates a novel application of this modeling method to the state estimation of nonlinear mechanical systems based on the Kalman filtering theory. The physical function model is a block diagram that describes each engineering field by a common rule, which focuses on the energy flow. Compared to traditional modeling approaches, this model has the flexibility to incorporate a wide range of nonlinear characteristics and the know-how accumulated by the manufacturers. Hence, it has a quite high affinity with the industrial world. The purpose of this research is to pioneer a new application of the physical function model beyond simulation analysis. In particular, physical function modeling offers a model of a system with multiple nonlinearities in the form of a time-varying linear state equation. By focusing on this feature, this study applies it to the Kalman filtering theory. The proposed approach is applicable to a wide range of nonlinearities, reduces the calculation load, and considers the background of the current MBD. Finally, verifications using an experimental apparatus, which simplifies an automotive drivetrain with backlash, demonstrate the effectiveness of the proposed approach.

Design and Practice of a Model-Based Development Education in Hydraulic Systems

This paper proposes educational simulation environment for the model-based development (MBD) of hydraulic systems. In recent years, customer requirements for different products have become more diversified and increasingly complicated. Thus, companies must respond to such demands promptly. Many companies are beginning to adopt an MBD as a solution to this problem because such an approach can reduce the development time and cost. However, most engineers in such companies lack experience with an MBD. Therefore, establishing a training environment that can allow them to learn the MBD process experientially within a short timeframe is an effective approach. Moreover, because hydraulic systems are mainly used in construction machines, this study focuses on educational materials for hydraulic systems through an MBD educational program jointly developed between Hiroshima University and Kobelco Construction Machinery Co., Ltd.

MBSE-integrated Parametric Working Surfaces as part of a PLM Design Approach

AbstractThis paper demonstrates a concept for a cross-domain strategy for the sustainable processing and dissemination of product information. Important functional product features are explicitly mapped as working surface information in different domain tools with the help of the contact channel method and are integrated using a model-based systems development approach. The approach uses established state of the art design tools and can be integrated into existing product development processes, knowledge based engineering concepts and product (system) lifecycle management strategies.

Bridging proprietary modelling and open-source model management tools: the case of PTC Integrity Modeller and Epsilon

While the majority of research on Model-Based Software Engineering revolves around open-source modelling frameworks such as the Eclipse Modelling Framework, the use of commercial and closed-source modelling tools such as RSA, Rhapsody, MagicDraw and Enterprise Architect appears to be the norm in industry at present. This technical gap can prohibit industrial users from reaping the benefits of state-of-the-art research-based tools in their practice. In this paper, we discuss an attempt to bridge a proprietary UML modelling tool (PTC Integrity Modeller), which is used for model-based development of safety-critical systems at Rolls-Royce, with an open-source family of languages for automated model management (Epsilon). We present the architecture of our solution, the challenges we encountered in developing it, and a performance comparison against the tool’s built-in scripting interface. In addition, we use the bridge in a real-world industrial case study that involves the coordination with other bridges between proprietary tools and Epsilon.

Model transformation for analyzing dependability of AADL model by using HiP-HOPS

The Architecture Analysis and Design Language (AADL) has emerged as a potential future standard in aerospace, automobile and avionics industries for model-based development of dependability-critical systems. As AADL is relatively new, some existing analysis methods and tools are not able to accept AADL models. In this paper we show that, by using model transformation techniques, we can automatically transform AADL models into a form that is directly executable by fault-tree-based dependability analysis and optimisation tools. This model transformation opens a path by which AADL models may benefit from automatic synthesis and analysis of fault trees, temporal fault tree analysis, multiple failure mode and effects analysis and model architecture optimisation.In this paper, we present a new model transformation framework. The core of the framework is a novel transformation from a state machine-based error model to a fault-tree model. The framework has been implemented as a plug-in (AADL2HiP-HOPS) for the AADL model development tool OSATE. The plug-in may be used to transform AADL models into a state-of-the-art dependability analysis and optimisation tool: HiP-HOPS. To illustrate the transformation and subsequent HiP-HOPS analysis, an example AADL model is transformed.

Synchronizing Digital Process Twins between virtual products and resources – A virtual design method

Modern technologies, such as cyber-physical systems and the digital twin, are driving current developments in digital production and its virtual planning tools. Thus leads to specific need for consistent methods that can be used across projects, especially on the future production planning’s long term view. Existing approaches deal with the cross-sectoral, virtually supported integration of cyber-physical properties in production structures by using multiple software structures. However, the potential of current production-related simulation tools in the field of systems virtual validation in the planning phase has not yet been exhausted. Based on this, the present work deals with a method for model data enrichment within virtual model-based systems development process that is executed in front of systems’ virtual commissioning. The elaborated method presupposes the successful procurement of the necessary CAD data as geometrical information and is divided into four steps, starting from the analysis of the process parameters on the basis of the product to be produced. In the second step, a property determination of the existing and planned production structure is carried out. In order to transfer the findings to the virtual modeling process, the third step is to determine the modeling needs between the current state of production and the planned cyber-physical production. Finally, a data enrichment of the products and resources behavioral models takes place that causes possibility of the mutual production-technical influence for example, by synchronizing the process structure that is stored in virtual products and resources. The method is to be classified as a total consideration of products, processes and resources in simulation-based functional verification and physical property validation. In addition, the four steps will be verified, by using the automated car-underbody assembly demonstrator for the physical relief of workers in the final assembly area of ​​automobile production, including many variants.

Agile model-based system development

Agile model-based system development

Coordinated actor model of self-adaptive track-based traffic control systems

Self-adaptation is a well-known technique to handle growing complexities of software systems, where a system autonomously adapts itself in response to changes in a dynamic and unpredictable environment. With the increasing need for developing self-adaptive systems, providing a model and an implementation platform to facilitate integration of adaptation mechanisms into the systems and assuring their safety and quality is crucial. In this paper, we target Track-based Traffic Control Systems (TTCSs) in which the traffic flows through pre-specified sub-tracks and is coordinated by a traffic controller. We introduce a coordinated actor model to design self-adaptive TTCSs and provide a general mapping between various TTCSs and the coordinated actor model. The coordinated actor model is extended to build large-scale self-adaptive TTCSs in a decentralized setting. We also discuss the benefits of using Ptolemy II as a framework for model-based development of large-scale self-adaptive systems that supports designing multiple hierarchical MAPE-K feedback loops interacting with each other. We propose a template based on the coordinated actor model to design a self-adaptive TTCS in Ptolemy II that can be instantiated for various TTCSs. We enhance the proposed template with a predictive adaptation feature. We illustrate applicability of the coordinated actor model and consequently the proposed template by designing two real-life case studies in the domains of air traffic control systems and railway traffic control systems in Ptolemy II.

Learning probabilistic models for model checking: an evolutionary approach and an empirical study

Many automated system analysis techniques (e.g., model checking, model-based testing) rely on first obtaining a model of the system under analysis. System modeling is often done manually, which is often considered as a hindrance to adopt model-based system analysis and development techniques. To overcome this problem, researchers have proposed to automatically “learn” models based on sample system executions and shown that the learned models can be useful sometimes. There are however many questions to be answered. For instance, how much shall we generalize from the observed samples and how fast would learning converge? Or, would the analysis result based on the learned model be more accurate than the estimation we could have obtained by sampling many system executions within the same amount of time? Moreover, how well does learning scale to real-world applications? If the answer is negative, what are the potential methods to improve the efficiency of learning? In this work, we first investigate existing algorithms for learning probabilistic models for model checking and propose an evolution-based approach for better controlling the degree of generalization. Then, we present existing approaches to learn abstract models to improve the efficiency of learning for scalability reasons. Lastly, we conduct an empirical study in order to answer the above questions. Our findings include that the effectiveness of learning may sometimes be limited and it is worth investigating how abstraction should be done properly in order to learn abstract models.

Model-based collaborative development of manufacturing and control systems

Model-based collaborative development of manufacturing and control systems

Natural Model based Design in Context: an Effective Method for Environmental Problems

Analyzing complex problem domains is not easy. Simulation tools support decision makers to find the best policies. Model-based system development is an approach where a model of the application domain is the central driving force when designing simulation tools. State-of-the-art techniques however still require both expert knowledge of the application domain and the implementation techniques as provided by ICT (such as multilevel agent technology). Domain experts, however, usually do not master ICT sufficiently. Modeling is more insightful for the domain expert when its goal is to formalize the language being used in that domain as a semi-natural language. At the meta level, this language describes the main concepts of the type of application domain. The model then is a concretization of this meta model. The main focus of this article is (1) to propose a natural-language-based approach to modeling application domains, (2) to show how these models can be transformed systematically into computational models, and (3) to propose the tool TiC (Tool in Context) that supports the domain expert when developing a model and generating a simulation tool. Our research methodology is based on Design Science. We verify our approach by describing the various transformation steps in detail, and by demonstrating the way of working via a sample session applying a real problem of Laf Forest Reserve deforestation in North Cameroon.