MODELSWARD 2023 Abstracts

Area 1 - Methodologies, Processes and Platforms

Short Papers

Paper Nr:	18
Title:	Model-Driven Optimisation of Monitoring System Configurations for Batch Production
Authors:	Andreas Margraf, Henning Cui, Simon Heimbach, Jörg Hähner, Steffen Geinitz and Stephan Rudolph
Abstract:	The increasing need to monitor asset health and the deployment of IoT devices have driven the adoption of non-desctructive testing methods in the industry sector. In fact, they constitute a key to production efficiency. However, engineers still struggle to meet requirements sufficiently due to the complexity and cross-dependency of system parameters. In addition, the design and configuration of industrial monitoring systems remains dependent on recurring issues: data collection, algorithm selection, model configuration and objective function modelling. In this paper, we shine a light on impact factors of machine vision and signal processing in industrial monitoring, from sensor configuration to model development. Since system design requires a deep understanding of the physical characteristics, we apply graph-based design languages to improve the decision and configuration process. Our model and architecture design method are adapted for processing image and signal data in highly sensitive installations to increase transparency, shorten time-to-production and enable defect monitoring in environments with varying conditions. We explore the potential of model selection, pipeline generation and data quality assessment and discuss their impact on representative manufacturing processes.
Download

Area 2 - Modeling Languages, Tools and Architectures

Full Papers

Paper Nr:	3
Title:	Lightweight Software Language Processing Using Antlr and CGTL
Authors:	Kevin Lano and Qiaomu Xue
Abstract:	Software complexity has become a significant social problem, which MDE endeavours to alleviate, however MDE approaches and tools often introduce additional complexity which prevents general software practitioners from benefiting from MDE solutions. In this paper we present an alternative approach for MDE in the domain of language processing, using lightweight tools (Antlr and CGTL) suitable for general industrial use. We evaluate the approach on tasks of DSL definition, software abstraction, and program translation, based on our experience with industrial applications of MDE.
Download

Paper Nr:	7
Title:	Mutation of Formally Verified SysML Models
Authors:	Ludovic Apvrille, Bastien Sultan, Oana Hotescu, Pierre de Saqui-Sannes and Sophie Coudert
Abstract:	Model checking of SysML models contributes to detect design errors and to check design decisions against user requirements. Yet, each time a model is modified, formal verification must be performed again, which makes model evolution costly and hampers the use of agile development methods. Based on former contributions on dependency graphs, the paper proposes to facilitate updates (also called mutations) on models: whenever a mutation is performed on a model, the algorithms introduced in this paper can determine which proofs remain valid and which ones must be performed again. The main idea to reduce the proof obligation is to identify new paths that need to be re-verified. Our algorithm reuses the results of previous proofs as much as possible in order to lower the complexity of the proof. The paper focuses on reachability proofs. A real-time communication architecture based on TSN (Time Sensitive Networking) illustrates the approach and performance results are presented.
Download

Paper Nr:	22
Title:	NICE: A Flexible Expression Language
Authors:	Oliver Hacker and Thomas Buchmann
Abstract:	Model-driven development relies on model-transformation languages to describe mappings between different metamodels and as such facilitate a model-first workflow. These languages and accompanying tools have matured a lot over the past years. However, the more recent developments BXtend and BXtendDSL lack some features like an integrated expression language which would greatly improve the usability. In this paper, we present the flexible expression language NICE, which aims to solve the aforementioned problem in a modular, reusable, and adaptable way, while being fast and easy to use.
Download

Paper Nr:	30
Title:	An Integrated Framework for Running Extended Class Models
Authors:	Johannes Schröpfer
Abstract:	Model-driven software engineering often deals with combinations of structural and behavioral models. In this area, class models are common artifacts expressing the structure of software systems. From class models, source code can be generated which captures the structural elements. To be runnable, the generated code usually has to be completed by implementing behavior. The Eclipse Modeling Framework (EMF) is a popular environment for model-driven software development. In this context, class models are specified as instances of the Ecore metamodel. From Ecore models, Java code is generated that lacks in the implementation of method bodies (typically, only method heads are generated). Our approach supports code generation from extended metamodels comprising structural elements, behavior, and constraints. To this end, we build a projectional editor for a textual modeling language based on SOIL, an imperative extension of OCL. The editor allows for specifying extended class models from which Java code can be generated. Our goal is to reuse the standard EMF code generator. The resulting Java source code is fully executable such that after creating the extended class model, no user interaction is required any more. In this paper, we present the idea of our approach and the current state of implementation.
Download

Paper Nr:	32
Title:	Verifying Static Constraints on Models Using General Formal Verification Methods
Authors:	Norbert Somogyi and Gergely Mezei
Abstract:	Over the years, the field of software modeling has gained significant popularity. By capturing the static aspects of the requirements of the software, model-driven engineering easens the development and maintenance of software. However, additional constraints that the solution must conform to may be too complex to include in the structure of the model itself. For this reason, external solutions are often used to describe static constraints on models, the most prevalent approach being the Object Constraint Language (OCL) and its formal variants. This paper proposes a general approach for verifying static constraints on software models by employing different formal verification methods than previous solutions. The approach defines a general Kripke Structure (KS) that captures the static structure of the model. In the next step, the constraints that the model must conform to are formalized using a first-order branching-time logic, the Computational Tree Logic (CTL). Finally, the NuSMV model checker tool is used to check whether the constraints formalized in CTL hold on the formal Kripke Structure. To demonstrate the feasibility of the approach, the concepts are illustrated on a running UML class diagram.
Download

Short Papers

Paper Nr:	1
Title:	InTra: A Pragmatic Approach of Using Rule-Based Model Transformation to Reduce Complexity of UML and SysML Models
Authors:	Philippe Barbie, Martin Becker and Andreas Schäfer
Abstract:	While UML and SysML are important concepts for digitally representing complex systems, we are still confronted with the problems of comprehensibility and maintainability. Even models with comparatively few elements can quickly become confusing and hard to read, due to their relationship density. This leads to potential errors, both for the initial modelling and the later model evolution and evaluation phase. Driven by the needs of a large-scale modelling project in the field of communication systems, we have researched approaches to cope with the inherent model complexity by following a modelling approach, that is based on interaction patterns. In this paper, we will give an introduction to the challenge of the consistently increasing complexity of system models in the field of model-based systems engineering (MBSE). We will motivate our need for rule-based modelling in order to handle a real industry use case and outline the problems of system modeling, which could be solved by using a new rule-based modelling approach. InTra (Interaction-based Transformation) is an approach to significantly reduce the complexity of a system model, by reducing the number of connectors through the use of interaction rules. By doing so, we were able to create an abstracted variant of the same system model, but with a highly reduced number of connectors used and thus an overall reduced model complexity.
Download

Paper Nr:	10
Title:	A Tool for Supporting Round-Trip Engineering with the Ability to Avoid Unintended Design Changes
Authors:	Takahiro Yamazaki, Takafumi Tanaka, Atsuo Hazeyama and Hiroaki Hashiura
Abstract:	It is difficult to maintain consistency between artifacts in a round-trip engineering project, such as an agile development method. In such software development projects, there is a method using traceability links as a method for maintaining consistency between artifacts. A method for creating traceability links from design artifacts to programs has been proposed in the past. However, few studies have proposed traceability links from source code to UML artifacts. Round-trip engineering could involve the developer making changes to the source code and applying those changes to the UML artifacts. The larger the system, the more difficult it becomes to apply changes to the UML artifact. We believe that traceability from the program to UML artifacts effectively addresses this problem. In this paper, we propose a traceability link method for programs to design artifacts, develop a tool for supporting the method, evaluate its effectiveness, and identify the difficulties for developers in manually modifying class diagrams.
Download

Paper Nr:	11
Title:	Model-Driven Collaborative Design of Professional Education Programmes with Extended Online Whiteboards
Authors:	Dennis Wolters and Gregor Engels
Abstract:	Designing bespoke professional education programmes with clients and other stakeholders is always challenging. For instance, education providers must understand a client’s environment, including the intended audience, and agree with them on learning goals and the programme’s structure and content. In this paper, we present our extension to the online whiteboard Miro to collaboratively design professional education programmes with stakeholders in remote settings. We developed a lightweight modelling language covering the entire life cycle of professional education programmes and a visual notation to depict such programmes on a high abstraction level in Miro. Our approach allows the use of online whiteboards beyond informal modelling and makes them a primary tool for designing such programmes. It adds features to extract the underlying model, can deal with modelling flexibility of Miro and provides the basis for integrations with other tools. In particular, we describe the integration with a project management tool to assist with the enactment of design and management processes of professional education programmes. Additionally, we show the feasibility and discuss limitations of tool support for visual modelling languages based on the online whiteboard Miro.
Download

Paper Nr:	16
Title:	Towards Specification of Medical Processes According to International Standards and Semantic Interoperability Needs
Authors:	Tanel Sõerd, Kristian Kankainen, Gunnar Piho, Toomas Klementi and Peeter Ross
Abstract:	Models of healthcare processes and workflows to support the continuity of health care are an essential research topic in medical informatics. This research topic is driven by the necessity to enable systems (including semantic) interoperability, to see the consistency of clinical data recorded in electronic health records (EHR) and to understand retrospectively the clinical pathways that led to these data. We propose a process meta-model and evaluate its usability by modelling the healthcare concepts and models from the ISO 13940 (system of concepts to support continuity of care) standard. Our meta-model is developed according to the software design patterns principles, enabling the formal specification of knowledge in a machine-readable format and preserving the history of these specifications. Our work contributes to the federated interoperability of healthcare information systems (healthcare enterprise applications), utilising executable meta-models that can map healthcare data at the semantic (medical knowledge) level, even at run-time.
Download

Paper Nr:	17
Title:	A Proposal Towards Discovering Metamodels from Low-Code Application Platforms
Authors:	Fernando Moreira, Nuno Bettencourt, Alexandre Bragança and Isabel Azevedo
Abstract:	Low-Code platforms enable users to quickly create apps of various types, with little or no coding in general-purpose programming languages. Despite their popularity, these platforms are often closed-source and do not adhere to standards. Users of these platforms face two major issues: the first is the difficulty in the evolution of applications in terms of platform updates, and the second is the inability to migrate the applications to another platform, restraining users to use the original platform. Thus, we investigated the feasibility of discovering these platforms’ meta-models by using some exported models as a starting point. This possibility could enable apps to be migrated, for example, to a new version of the platform or a different one by describing transformations using the discovered meta-models. A proposal for solving this issue is described, also its evaluation. By analysing the obtained test results, the proposal was considered successful.
Download

Paper Nr:	23
Title:	Challenges in Modeling and Unmodeling Emergence, Rule Composition, and Networked Interactions in Complex Reactive Systems
Authors:	Assaf Marron, Irun Cohen, Guy Frankel, David Harel and Smadar Szekely
Abstract:	Models of complex systems, both human-made and natural, assist in making critical decisions with regard to function, safety, economy, the environment and more. In this position paper, we explore the difficulty in modeling several innate properties of such systems, including: (i) the frequent emergence of new entities (like group effects and temporal patterns) and the system’s reaction to such emergence; (ii) the essence of the system’s reactive behavior as a rich composition of stand-alone rules; and (iii) the vast number of internal and external interactions that the system engages in. For each of these challenges we propose some implications to modeling—methodological approaches that can help address it and potential support in modeling languages and tools. We introduce the concept of unmodeling—formally defining model entities and behaviors that are excluded from model execution—and discuss how unmodeling enhances model quality, supports incremental enhancement, and facilitates evaluation. This report emanates from our research and development in modeling languages and methods and our present research in biological evolution. We believe that analysis and implementation of these principles have general applicability in model development and assessment.
Download

Paper Nr:	25
Title:	Exploiting Meta-Model Structures in the Generation of Xtext Editors
Authors:	Jörg Holtmann, Jan-Philipp Steghöfer and Weixing Zhang
Abstract:	When generating textual editors for large and highly structured meta-models, it is possible to extend Xtext’s generator capabilities and the default implementations it provides. These extensions provide additional features such as formatters and more precise scoping for cross-references. However, for large metamodels in particular, the realization of such extensions typically is a time-consuming, awkward, and repetitive task. For some of these tasks, we motivate, present, and discuss in this position paper automatic solutions that exploit the structure of the underlying metamodel. Furthermore, we demonstrate how we used them in the development of a textual editor for EATXT, a textual concrete syntax for the automotive architecture description language EAST-ADL. This work in progress contributes to our larger goal of building a language workbench for blended modelling.
Download

Paper Nr:	29
Title:	Requirement Formalisation Using Natural Language Processing and Machine Learning: A Systematic Review
Authors:	Shekoufeh Kolahdouz-Rahimi, Kevin Lano and Chenghua Lin
Abstract:	Improvement of software development methodologies attracts developers to automatic Requirement Formalisation (RF) in the Requirement Engineering (RE) field. The potential advantages of applying Natural Language Processing (NLP) and Machine Learning (ML) in reducing the ambiguity and incompleteness of requirements written in natural languages are reported in different studies. The goal of this paper is to survey and classify existing works on NLP and ML for RF, identifying the challenges in this domain and providing promising future research directions. To achieve this, we conducted a systematic literature review to outline the current state-of-the-art of NLP and ML techniques in RF by selecting 257 papers from commonly used libraries. The search result is filtered by defining inclusion and exclusion criteria and 47 relevant studies between 2012 and 2022 are selected. We found that heuristic NLP approaches are the most common NLP techniques used for automatic RF, primarily operating on structured and semi-structured data. This study also revealed that Deep Learning (DL) techniques are not widely used, instead, classical ML techniques are predominant in the surveyed studies. More importantly, we identified the difficulty of comparing the performance of different approaches due to the lack of standard benchmark cases for RF.
Download

Paper Nr:	33
Title:	Enhancing Deep Learning with Scenario-Based Override Rules: A Case Study
Authors:	Adiel Ashrov and Guy Katz
Abstract:	Deep neural networks (DNNs) have become a crucial instrument in the software development toolkit, due to their ability to efficiently solve complex problems. Nevertheless, DNNs are highly opaque, and can behave in an unexpected manner when they encounter unfamiliar input. One promising approach for addressing this challenge is by extending DNN-based systems with hand-crafted override rules, which override the DNN’s output when certain conditions are met. Here, we advocate crafting such override rules using the well-studied scenario-based modeling paradigm, which produces rules that are simple, extensible, and powerful enough to ensure the safety of the DNN, while also rendering the system more translucent. We report on two extensive case studies, which demonstrate the feasibility of the approach; and through them, propose an extension to scenario-based modeling, which facilitates its integration with DNN components. We regard this work as a step towards creating safer and more reliable DNN-based systems and models.
Download

Paper Nr:	39
Title:	Towards Multi-Level Structuring of Goal-Oriented Models for Improved Model-Based Systems Engineering
Authors:	Christophe Ponsard and Robert Darimont
Abstract:	Model-driven methods are gaining momentum in the industry to support the development of software intensive systems. While most methods rely on progressive levels of functional decomposition, the modelling of requirements tends to stay quite monolithic in nature. This position paper analyses how to better structure requirements across multiple levels in the scope of goal-oriented requirements engineering to reconcile it with layered system models and to provide better support for decomposition and analysis of inner sub-components or the outer system of systems. The proposed ideas are discussed based on a classical case study of the meeting scheduler with some early prototyping using a meta-case requirements engineering platform.
Download

Paper Nr:	40
Title:	Toward Automated Modeling of Abstract Concepts and Natural Phenomena: Autoencoding Straight Lines
Authors:	Yuval Bayer, David Harel, Assaf Marron and Smadar Szekely
Abstract:	Modeling complex systems or natural phenomena requires special skills and extensive domain knowledge. This makes automating model development an intriguing challenge. One question is whether a model’s ontology—the essence of its entities—can be learned automatically from observation. We describe work in progress on automating the learning of a basic concept: an image of the straight line segment between two points in a two-dimensional plane. Humans readily encode such images using two endpoints, or a point, an angle, and a length. Furthermore, image recognition algorithms readily detect line segments in images. Here, we employ autoencoders. Autoencoders perform both feature extraction and reconstruction of inputs from their coded representation. It turns out that autoencoding line segments is not trivial. Our interim conclusions include: (1) Developing methods for comparing the performance of different autoencoders in a given task is an essential research challenge. (2) Development of autoencoders manifests supervision of this purportedly unsupervised process; one then asks what knowledge employed in such development can be obtained automatically. (3) Automatic modeling of properties of observed objects requires multiple representations and sensors. This work can eventually benefit broader issues in automated model development.
Download

Paper Nr:	4
Title:	On the Interest of Combining Several Variability Tactics to Design the Implementation of Product Lines
Authors:	Maouaheb Belarbi and Vincent Englebert
Abstract:	In Software Product Line (SPL) field, several variability mechanisms have been proposed to realize system requirements. Despite that each mechanism is relevant to satisfy only specific engineering criteria, it is unable to face several challenges. We believe that using several variability realization techniques allows to get trade-off for all the benefits and strength of the considered realization techniques. In this paper, we provide an answer for the fact that if combining several programming techniques is worth investment which, at the best of our knowledge, was not tackled before in the literature. The current study implements, at first, an open source product line entirely with different variability realization techniques, and secondly, combines these mechanisms in the same product line. An assessment of the obtained product lines is performed according to quality attributes,code quality metrics, and product line concepts. Together, the present findings confirm that combining several variability mechanisms hits the best rates in most quality evaluation metrics and provides a median to achieve most relevant software quality criteria.
Download

Paper Nr:	13
Title:	Visualizing Errors and Inconsistencies in the DSML IEC 61499
Authors:	Michael Oberlehner, Bianca Wiesmayr, Hafiyyan S. Fadhlillah and Alois Zoitl
Abstract:	Errors of textual programming languages are usually detected by the compiler. These errors are then visualized by the IDE and made available to the developer. This paper is intended to show a novel approach to also propagate errors in visual programming languages to the developer. We analyzed the visual block-based language of IEC 61499 and implemented an error visualization mechanism in the Eclipse-based IDE 4diac. As IEC 61499 is a Domain-Specific Modeling Language (DSML) that includes a type system, we also implemented a mechanism for detecting inconsistencies. With this approach, it is possible to work on broken applications, giving developers the opportunity to fix them in a graphical editor. Furthermore, inconsistencies that lead to errors are now displayed rather than being hidden from the developer and hard to detect.
Download

Paper Nr:	20
Title:	Application of a Process-Oriented Build Tool for Verification and Validation of a Battery Slave Controller for a Battery Modular Multilevel Management System Along the DO-178C/DO-331 Process
Authors:	Purav Panchal, Nina Sorokina, Manuel Kuder, Stephan Myschik, Konstantin Dmitriev and Florian Holzapfel
Abstract:	Software development of safety-critical systems is accompanied with strict methodologies, handling of a large number of artifacts, and transparent verification activities. In order to achieve compliance to the DO-178C/DO-331 standard. These requirements reduces the flexibility of the development and demands highly skilled personnel. This increases both money and time requirements. To address this problem, a process-oriented build tool has been developed and applied to safety-critical applications, such as flight control algorithms. Advantages of this build-tool include automatic verification jobs, interlinking of tools, artifact handling, bottom-totop code generation, change impact analysis, handling of multiple modules, etc. In this paper, the build tool is used to develop and verify a battery slave controller for a Battery Modular Multilevel Management (BM3) module. This paper presents the important verification results achieved, including model coverage, code coverage and cyclomatic complexity of the slave controller. These results help in demonstrating the mentioned advantages of the use of the build-tool and provides a practical application point of view.
Download

Paper Nr:	24
Title:	Creating Python-Style Domain Specific Languages: A Semi-Automated Approach and Intermediate Results
Authors:	Weixing Zhang, Regina Hebig, Jan-Philipp Steghöfer and Jörg Holtmann
Abstract:	Xtext is a well-known domain-specific language design framework and technology. It automatically generates a textual grammar for a language, given a meta-model specified in Ecore. These generated textual grammars are typically not user-friendly. Python-style languages are popular among developers for their usability and conciseness. We aim to propose a systematic approach to transform a DSL with a generated grammar into a Python-style DSL. To achieve this, we analyze the problems of grammars generated with Xtext, based on a lightweight architecture description language. In response to these problems, we propose a general semi-automated grammar adaptation approach. We apply the approach to two other DSLs to validate the generalization of the approach. We also discuss the limitations of this approach and prospects for the future.
Download

Paper Nr:	31
Title:	Supporting Change Impact Analysis in System Architecture Design: Towards a Domain-Specific Modeling Method
Authors:	Afef Awadid and Remi Boyer
Abstract:	The architecture design update is appraised as a key issue in the domain of cyber-physical systems. One reason for this is its significant cost that can increase up to several folds with each phase of the life cycle, from conceptual design to operation. Therefore, before accepting such update, it is crucial to analyse its impact the so-called "Change Impact Analysis (CIA)". CIA is based on traceability of dependencies between elements in system artefacts. However, in practice, traceability is not sufficient to allow the automated support of CIA, as it lacks the consideration of CIA parameters. A CIA parameter is any information that could be useful for quantitatively or qualitatively assessing change impact. Against this background, this paper proposes a Domain-Specific Modeling Method for assisting CIA in the context of system architecture design. Such method is composed of two parts. First, a traceability language built upon existing traceability patterns and involving a set of CIA parameters. Second, a modeling procedure referring to a change scenario-based approach that describes how to use such language to provide an automated support for CIA. For the sake of validity, the method is applied in the aeronautical field.
Download

Area 3 - Applications and System Development

Full Papers

Paper Nr:	9
Title:	Go Meta of Learned Cost Models: On the Power of Abstraction
Authors:	Abdelkader Ouared, Moussa Amrani and Pierre-Yves Schobbens
Abstract:	Cost-based optimization is a promising paradigm that relies on execution queries to enable fast and efficient execution reached by the database cost model (CM) during query processing/optimization. While a few database management systems (DBMS) already have support for mathematical CMs, developing such a CMs embedded or hard-coded for any DBMS remains a challenging and error-prone task. A generic interface must support a wide range of DBMS independently of the internal structure used for extending and modifying their signature; be efficient for good responsiveness. We propose a solution that provides a common set of parameters and cost primitives allowing intercepting the signature of the internal cost function and changing its internal parameters and configuration options. Therefore, the power of abstraction allows one to capture the designers/developers intent at a higher level of abstraction and encode expert knowledge of domain-specific transformation in order to construct complex CMs, receiving quick feedback as they calibrate and alter the specifications. Our contribution relies on a generic CM interface supported by Model-Driven Engineering paradigm to create cost functions for database operations as intermediate specifications in which more optimization concerning the performance are delegated by our framework and that can be compiled and executed by the target DBMS. A proof-of-concept prototype is implemented by considering the CM that exists in PostgreSQL optimizer.
Download

Paper Nr:	19
Title:	Modeling Machine Learning Concerns in Collective Adaptive Systems
Authors:	Petr Hnětynka, Martin Kruliš, Michal Töpfer and Tomáš Bureš
Abstract:	Collective adaptive systems (CAS) are systems composed of a large number of heterogeneous entities without central control that adapt their behavior to reach a common goal. Adaptation and collaboration in such systems are traditionally specified via a set of logical rules. Nevertheless, such rules are often too rigid and do not allow for the evolution of a system. Thus, recent approaches started with the introduction of machine learning (ML) methods into CAS. In the is paper, we present a model-driven approach showing how CAS, which employs ML methods for adaptation, can be modeled—on both the platform independent and specific levels. In particular, we define a meta-model for modeling CAS and a mapping of concepts defined in the meta-model to the Python framework.
Download

Short Papers

Paper Nr:	8
Title:	Hierarchical Design of Cyber-Physical Systems
Authors:	Daniela Genius and Ludovic Apvrille
Abstract:	Cyber-physical systems are based upon analog / digital hardware and software components. The splitting into functionalities and interaction between analog and digital parts should be considered as early as possible in the design phase, relying on formal verification or simulation. While many papers pretend to propose a modeling environment supporting them, only a few of them really address the different Models of Computation of these systems because they strongly differ. The paper explains how to generate a combined SystemC/SystemC AMS virtual prototype of the analog and mixed-signal parts of CPS directly from a SysML model featuring whole parts of CPS, thus reconciling near-circuit precision with more abstract analog and digital models.
Download

Paper Nr:	14
Title:	A Modelling Methodology for Developing an Information Model for Cyber-Physical Production Systems using OPC UA
Authors:	Mainak Majumder and Alois Zoitl
Abstract:	The Open Platform Communication Unified Architecture (OPC UA), due to its sophisticated information modelling mechanism, has emerged as one of the principal tools for developing information models of Cyber-Physical Production Systems (CPPS). However, developing information models, especially for legacy brownfield systems, remains a challenging task. This is due to the unavailability of adequate modelling techniques as well as a higher learning curve regarding the OPC UA model. Therefore, the goal of this paper is to analyse the OPC UA information modelling paradigm and propose a generic technology-agnostic modelling methodology that could act as a guideline for OPC UA information model development.
Download

Paper Nr:	21
Title:	Metamodel-Based Multi-View Modeling Framework for Machine Learning Systems
Authors:	Jati H. Husen, Hironori Washizaki, Nobukazu Yoshioka, Hnin T. Tun, Yoshiaki Fukazawa and Hironori Takeuchi
Abstract:	Machine Learning systems provide different challenges for their development. However, machine learning systems also require specific attention toward traditional aspects of software engineering. This situation often leads developers to use different models to cover different views that need to be handled during machine learning system development which often leads to conflicting information between models. In this research, we developed a multi-view modeling framework for machine learning system development by utilizing a metamodel as its backbone for consistency. We have conducted a case study and controlled experiment to evaluate the framework. In conclusion, our framework does help manage the consistency between different views but relies heavily on the quality of available support tools.
Download

Paper Nr:	28
Title:	Experiences and Lessons from Introducing Model-Based Analysis in Brown-Field Product Family Development
Authors:	Jacques Verriet, Bram van der Sanden, Gijs van der Veen, André van Splunter, Sam Lousberg, Martijn Hendriks and Twan Basten
Abstract:	Product family development facilitates reuse across all phases of systems engineering; in case of model-based systems engineering, this reuse involves the models as well. Introducing a model-based way of working is challenging, especially for product family development. This paper describes a case of introducing a modelbased way of working in brown-field product family development. We explain how we developed a master model, i.e. a library of model elements, to predict and optimize the productivity of a family of industrial production systems. Using this master model, we construct models of existing and yet-to-be-developed product family members by configuring and combining the appropriate library elements. We use system and model execution traces to validate the productivity models. For this, we developed a master transformation, i.e. a library of execution trace transformation rules, to unify system and model execution traces. Besides the master model and the master transformation, we present lessons learned regarding the introducing a model-based way of working. This proves both technically and organizationally complex, especially for brown-field product family development, but besides the intended prediction and optimization, it brings benefits with respect to capturing domain knowledge and system validation.
Download

Paper Nr:	41
Title:	ATMO: Autonomous Train Map Ontology
Authors:	Nadia Chouchani and Sana Debbech
Abstract:	Infrastructure is the backbone of the railway industry which is an extensive and particularly complex system. However, the usage of different national and international standards for its design has led to a large number of incompatible systems. In this paper, we present ATMO, Autonomous Train Map Ontology, a modular ontology for modelling an on-board digital map for autonomous trains representing the railway infrastructure, line-side signalling and associated buildings. Semantic web technologies, knowledge and ontology engineering are adopted to integrate information from heterogenous sources and diverse standards such as RailSystemModel, EULYNX and IFC Rail ; to ensure semantic consistency of digital map objects. The development process is based on METHONTOLOGY and produced : (i) UML model as lightweight ontology; and (ii) OWL formal machine-readable specification as heavyweight ontology. The latter was evaluated using a railway use case.
Download