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2022

Digital Transformation - Towards flexible human-centric enterprises

B. Kehrbusch, G. Engels, in: Digital Transformation: Core Technologies and Emerging Topics from a Computer Science Perspective, Springer-Vieweg, 2022


Decision Support Ecosystems: Definition and Platform Architecture

J. Kirchhoff, C. Weskamp, G. Engels, in: Decision Support Systems XII: Decision Support Addressing Modern Industry, Business, and Societal Needs, Springer, 2022

Decision support systems are crucial in helping decision makers to quickly identify optimal business decisions in increasingly volatile and complex business environments. However, the ideal DSS for one decision maker may not optimally address the requirements for decision support of another decision maker. This is due to differences between decision makers in business goals, regulatory restrictions or availability of resources such as data. By using a suboptimal DSS, decision makers risk implementing suboptimal decision recommendations which endanger the success of their business. This presents DSS developers with the challenge to implement a customizable DSS which can be tailored to the individual requirements for decision support of a single decision maker. In order to address this challenge, we suggest a decision support ecosystem in which DSS developers, decision makers and other domain experts collaborate using a shared platform to provide and combine reusable decision support services into a tailored DSS. The contribution of our paper is twofold: First, we define the concept of a decision support ecosystem with respect to existing digital business ecosystems and discuss expected benefits and challenges. Second, we present a reference architecture for a shared platform supporting the realization of a decision support ecosystem. We demonstrate our contributions in the example application domain of regional energy distribution network planning.


Situational Business Model Developer: A Tool-support for Situation-specific Business Model Development

S. Gottschalk, E. Yigitbas, A. Nowosad, G. Engels, in: Proceedings of the 17th International Conference on Wirtschaftsinformatik, AIS, 2022

The development of business models is a challenging task that can be supported with software tools. Here, existing approaches and tools do not focus on the company’s situation in which the development takes place (e.g., financial resources, product type). To tackle this challenge, we used design science research to develop a situation-specific business model development approach that contains three stages: First, existing knowledge in terms of tasks to do (e.g., analyze competitive advantage), and decisions to be made (e.g., social media marketing) are stored in repositories. Second, the knowledge is used to compose a development method based on the company’s situation. Third, the development method is enacted to develop a business model. This demonstration paper presents a tool-support called Situational Business Model Developer that supports all stages of our approach. We release the tool under open-source and evaluate it with a case study on developing business models for mobile apps.


Development and Evaluation of a Collaborative Stock Trading Environment in Virtual Reality

E. Yigitbas, S. Gottschalk, A. Nowosad, G. Engels, in: Proceedings of the 17th International Conference on Wirtschaftsinformatik, AIS, 2022

Due to the proliferation of Virtual Reality (VR) technology, VR is finding new applications in various domains, such as stock trading. Here, traders invest in stocks intending to increase their profit. For this purpose, in conventional stock trading, traders usually make use of 2D applications on desktop or laptop devices. This leads to many drawbacks such as poor visibility due to limited 2D representation, complex interaction due to indirect interaction via mouse and keyboard, or restricted support for collaboration between traders. To overcome these issues, we have developed a novel collaborative, virtual environment for stock trading, which enables stock traders to view financial information and trade stocks with other collaborators. The main results of a usability study indicate that the VR environment, compared to conventional stock trading, shows no significant advantages concerning efficiency and effectiveness, however, we could observe an increased user satisfaction and better collaboration.


COVIDPUBGRAPH: A FAIR Knowledge Graph of COVID-19 Publications

S.. Pestryakova, D. Vollmers, M. Sherif, S. Heindorf, M.. Saleem, D. Moussallem, A. Ngonga Ngomo, Scientific Data (2022)


Enhancing Human-in-the-Loop Adaptive Systems through Digital Twins and VR Interfaces

E. Yigitbas, K. Karakaya, I. Jovanovikj, G. Engels, in: Software Engineering 2022, Fachtagung des GI-Fachbereichs Softwaretechnik, 21.-25. Februar 2022, Virtuell, Gesellschaft für Informatik e.V., 2022, pp. 95–96

DOI


Collaborative Software Modeling in Virtual Reality

E. Yigitbas, S. Gorissen, N. Weidmann, G. Engels, in: Software Engineering 2022, Fachtagung des GI-Fachbereichs Softwaretechnik, 21.-25. Februar 2022, Virtuell, Gesellschaft für Informatik e.V., 2022, pp. 93–94

DOI


Design and Evaluation of AR-Assisted End-User Robot Path Planning Strategies

S.C. Krings, E. Yigitbas, K. Biermeier, G. Engels, in: Proceedings of the 14th ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS 2022) (to appear), 2022


Self-Adaptive Digital Assistance Systems for Work 4.0

E. Yigitbas, S. Sauer, G. Engels, in: Digital Transformation: Core Technologies and Emerging Topics from a Computer Science Perspective, Springer-Vieweg, 2022


Automated UX Evaluation for User-Centered Design of VR Interfaces

K. Karakaya, E. Yigitbas, G. Engels, in: Proceedings of the 9th International Working Conference on Human-Centered Software Engineering (HCSE'22) (to appear), Springer, 2022


Human-in-the-Loop Large-Scale Model Transformations with the VICToRy Debugger

N. Weidmann, E. Yigitbas, A. Anjorin, A.. Srivastava, J. Jose, The Journal of Object Technology (to appear) (2022)


Comparative Evaluation of AR-based, VR-based, and Traditional Basic Life Support Training

E. Yigitbas, S. Krois, T. Renzelmann, G. Engels, in: Proceedings of the 10th International Conference on Serious Games and Applications for Health (SeGAH'22) (to appear), IEEE, 2022


Model-driven Continuous Experimentation on Component-based Software Architectures

S. Gottschalk, E. Yigitbas, G. Engels, in: Proceedings of the 18th International Conference on Software Architecture Companion , IEEE, 2022

To build successful software products, developers continuously have to discover what features the users really need. This discovery can be achieved with continuous experimentation, testing different software variants with distinct user groups, and deploying the superior variant for all users. However, existing approaches do not focus on explicit modeling of variants and experiments, which offers advantages such as traceability of decisions and combinability of experiments. Therefore, our vision is the provision of model-driven continuous experimentation, which provides the developer with a framework for structuring the experimentation process. For that, we introduce the overall concept, apply it to the experimentation on component-based software architectures and point out future research questions. In particular, we show the applicability by combining feature models for modeling the software variants, users, and experiments (i.e., model-driven) with MAPE-K for the adaptation (i.e., continuous experimentation) and implementing the concept based on the component-based Angular framework.


Continuous Situation-specific Development of Business Models: Knowledge Provision, Method Composition, Method Enactment

S. Gottschalk, E. Yigitbas, A. Nowosad, G. Engels, International Journal on Software and Systems Modeling (SoSyM) (to appear) (2022)

The development of new business models is essential for startups to become successful, as well as for established companies to explore new business opportunities. However, developing such business models is a continuous challenging activity where different tasks need to be performed, and business decisions need to be made. Both have to fit the constantly changeable situation in which the business model is developed to reduce the risk of developing ineffective business models with low market penetration. Therefore, a method for developing situation-specific business models is needed. As a solution, we refine the concept of situational method engineering (SME) to business model development. SME, in turn, provides means to construct situation-specific development methods out of fragments from a method repository. We develop a concept for the continuous situation-specific development of business models based on design science. The approach uses the roles of a domain expert, a method engineer, and a business developer together with a repository with method fragments for developing business models and a repository with modeling artifacts for supporting the development. Both repositories are filled by utilizing the experience of domain experts. Out of these repositories, situation-specific development methods for developing business models can be continuously composed based on the changeable situation by the method engineer and enacted by the business developer. We implement it as an open-source tool and evaluate its applicability in an industrial case study of developing a business model for a local event platform. Our results show that situation awareness supports the continuous development of business models.


Towards Situation-specific Software Support for Cross-organizational Design Thinking Processes

S. Gottschalk, E. Yigitbas, A. Nowosad, G. Engels, in: Proceedings of the 5th International Workshop on Software-intensive Business (IWSiB'22) (to appear), ACM, 2022

Due to the increasing influences of a VUCA world, design thinking workshops have been established as a standard technique to build solutions according to uncertain customer needs. Concerning the ongoing pandemic and rising development of solutions across organizations, more and more workshops were conducted online with software support. However, existing software tools insufficiently address the different workshop situations in terms of the process (i.e., fixed tasks to conduct), the place (e.g., static online whiteboards), and people (i.e., synchronous working of all stakeholders). Therefore, we propose a design science study to develop a situation-specific software support that can be configured with flexible development processes, different places, and task-related people. Based on practical experience in existing research projects, we derive the initial design requirements and map them to a set of design principles. Out of that, we design a concept with its implementation as a software tool and point out open challenges.


Requirements-Based Composition of Tailored Decision Support Systems (to appear)

J. Kirchhoff, C. Weskamp, G. Engels, 2022

Corporate decision makers have individual requirements for decision support influenced by business goals, regulatory restrictions or access to resources such as data. Ideally, decision makers could quickly create tailored decision support systems (DSS) themselves which optimally address their individual requirements for decision support. Although service-oriented architectures have been proposed for DSS customization, they are primarily targeting trained software developers and cannot immediately be adapted by decision makers or domain experts with little to no software development knowledge. In this paper, we therefore motivate an assisted process-based service composition approach which can be used by non-developers to create tailored DSS. For assistance during service composition, we contribute a meta-model for the formalization of both decision support requirements and functionality of decision support services. Models created according to the meta-model can be used to detect mismatches between a decision maker’s requirements for decision support and services selected in the service composition representing a DSS. Furthermore, the formalizations may even be used for automated service composition given a decision maker’s decision support requirements. We demonstrate the expressiveness of our meta-model in the domain of regional energy distribution network planning


Detecting Data Incompatibilities in Process-Driven Decision Support Systems

J. Kirchhoff, S. Gottschalk, G. Engels, in: Lecture Notes in Business Information Processing, Springer International Publishing, 2022

Decision makers in complex business environments have different goals and constraints and therefore require tailored decision support systems (DSS). Following a low-code approach, a tailored DSS can be created by a decision maker as a process-based composition of existing, interoperable decision support services. Data incompatibilities may be introduced during the design or execution of such a process-driven DSS, e.g., when a service always generates or a decision maker selects data which violates a data constraint of a subsequent service. These incompatibilities cause interrupted or erroneous decision processes. In this paper, we contribute an approach which enables the detection of data incompatibilities in process-driven DSS during process design and execution. Our approach utilizes the JSON Schema specification to define service interfaces and associated type constraints which data produced by services or decision makers can be validated against. We demonstrate our approach in the context of decision support for energy network planning using a prototypical open-source implementation.



2021

Extending Business Model Development Tools with Consolidated Expert Knowledge

S. Gottschalk, J. Kirchhoff, G. Engels, in: Business Modeling and Software Design, 2021


eMoflon: : Neo - Consistency and Model Management with Graph Databases

N. Weidmann, A. Anjorin, in: {STAF} 2021 Workshop Proceedings: 9th International Workshop on Bidirectional Transformations, Joint Workshop on Foundations and Practice of Visual Modeling and Data for Model-Driven Engineering, International workshop on {MDE} for Smart IoT Systems, 4th International Workshop on (Meta)Modeling for Healthcare Systems, and 20th International Workshop on {OCL} and Textual Modeling co-located with Software Technologies: Applications and Foundations, Federation of Conferences {(STAF} 2021), Virtual Event / Bergen, Norway, June 21-25, 2021, CEUR-WS.org, 2021, pp. 54-64


Von datenbasierter zu datengetriebener Geschäftsmodellentwicklung: Ein Überblick über Software-Tools und deren Datennutzung

S. Gottschalk, E. Yigitbas, Gesellschaft für Informatik, 2021

Die kontinuierliche Weiterentwicklung des eigenen Geschäftsmodells ist für eine Organisation von entscheidender Bedeutung, um wettbewerbsfähig und somit nachhaltig erfolgreich zu bleiben. Während für die Entwicklung neuer Geschäftsmodelle häufig Workshops und einfache Software-Tools zur Visualisierung genutzt werden, wurden in der Forschung bereits erste Ansätze von datengetriebener Geschäftsmodellentwicklung (GME) vorgestellt. Diese Ansätze nutzen dabei Daten, Informationen oder auch Wissen aus internen und externen Unternehmensquellen, um den GME-Prozess zu unterstützen. Innerhalb dieses Beitrags zeigen wir einige Ansätze aus der aktuellen Literatur und analysieren wie ihre Datennutzung den GME-Prozess unterstützt. Weiterhin stellen wir mit dem BMDL Feature Modeler ein Tool vor, welches den GME-Prozess mit Expertenwissen unterstützt.


Distributed merchandise management system

T. Göllner, J. Schwarz, S. Gottschalk, S. Sauer. Distributed merchandise management system, Patent US 2021/0081978 A1. 2021.

The invention describes a distributed merchandise management system, in which the client, retailer and the manufacturer are linked by a network. This is implemented by a cloud storage (105), the cloud storage (105) comprising a means (105 a) for storing data, a means for receiving first data from a first network node (110), the first data being associated with a physical object, a means for receiving request data from a second network node (120), a means for receiving second data from a third network node (130), the second data being associated with the first data and comprising at least one data piece adapted to change the first data depending on the received request data, a means for changing the first data based at least in part on the second data and the request data, and a means for sending a changed portion of the first data from the cloud storage (105) to the first network node (110).


Situation-specific Business Model Development Methods for Mobile App Developers

S. Gottschalk, E. Yigitbas, A. Nowosad, G. Engels, in: Enterprise, Business-Process and Information Systems Modeling, Springer, 2021

The development of effective business models is an essential task in highly competitive markets like mobile ecosystems. Existing development methods for these business models do not specifically focus that the development process profoundly depends on the situation (e.g., market size, regulations) of the mobile app developer. Here, a mismatch between method and situation can lead to poor resource management and longer development cycles. In software engineering, situational method engineering is used for software projects to configure a development method out of a method repository based on the project situation. Analogously, we support creating situation-specific business model development methods with a method base and new user roles. Here, the method engineer obtains the knowledge of the domain expert and stores it in the method base as elements, building blocks, and patterns. The expert knowledge is derived from a grey literature review on mobile development processes. After this, the method engineer constructs the development method based on the described situation of the business developer. We provide an open-source tool and evaluate it by constructing a local event platform's business model development method.


Schema Compliant Consistency Management via Triple Graph Grammars and Integer Linear Programming

N. Weidmann, A. Anjorin, Formal Aspects of Computing (2021)

<jats:title>Abstract</jats:title><jats:p>In the field of Model-Driven Engineering, Triple Graph Grammars (TGGs) play an important role as a rule-based means of implementing consistency management. From a declarative specification of a consistency relation, several operations including forward and backward transformations, (concurrent) synchronisation, and consistency checks can be automatically derived. For TGGs to be applicable in realistic application scenarios, expressiveness in terms of supported language features is very important. A TGG tool is schema compliant if it can take domain constraints, such as multiplicity constraints in a meta-model, into account when performing consistency management tasks. To guarantee schema compliance, most TGG tools allow application conditions to be attached as necessary to relevant rules. This strategy is problematic for at least two reasons: First, ensuring compliance to a sufficiently expressive schema for all previously mentioned derived operations is still an open challenge; to the best of our knowledge, all existing TGG tools only support a very restricted subset of application conditions. Second, it is conceptually demanding for the user to indirectly specify domain constraints as application conditions, especially because this has to be completely revisited every time the TGG or domain constraint is changed. While domain constraints can in theory be automatically transformed to obtain the required set of application conditions, this has only been successfully transferred to TGGs for a very limited subset of domain constraints. To address these limitations, this paper proposes a search-based strategy for achieving schema compliance. We show that all correctness and completeness properties, previously proven in a setting without domain constraints, still hold when schema compliance is to be additionally guaranteed. An implementation and experimental evaluation are provided to support our claim of practical applicability.</jats:p>


A Modeling Workbench for the Development of Situation-specific Test Co-Migration Methods

I. Jovanovikj, A.T. Thottam, V. Joseph Vincent, E. Yigitbas, S. Sauer, G. Engels, in: Proceedings of the 9th International Conference on Model-Driven Engineering and Software Development , SCITEPRESS, 2021, pp. 232-239


Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts

T. Nickchen, S. Heindorf, G. Engels, in: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2021, pp. 1994-2002


Situation-specific Development of Business Models for Services in Software Ecosystems

S. Gottschalk, in: Advanced Software Engineering. Doctorial Consortium, CEUR, 2021


Automating Model Transformations for Railway Systems Engineering.

N. Weidmann, S. Salunkhe, A. Anjorin, E. Yigitbas, G. Engels, The Journal of Object Technology (2021), 10:1

DOI


Enhancing Human-in-the-Loop Adaptive Systems through Digital Twins and VR Interfaces

E. Yigitbas, K. Karakaya, I. Jovanovikj, G. Engels, in: 2021 International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), 2021

DOI


Concurrent model synchronisation with multiple objectives

N. Weidmann, G. Engels, in: Proceedings of the Genetic and Evolutionary Computation Conference, 2021

DOI


Towards Visualizing and Simulating Business Models in Dynamic Platform Ecosystems

C. Vorbohle, S. Gottschalk, in: Proceedings of the 29th European Conference on Information Systems (ECIS), AIS, 2021

Platform-based business models underlie the success of many of today’s largest, fastest-growing, and most disruptive companies. Despite the success of prominent examples, such as Uber and Airbnb, creating a profitable platform ecosystem presents a key challenge for many companies across all industries. Although research provides knowledge about platforms’ different value drivers (e.g., network effects), companies that seek to transform their current business model into a platform-based one lack an artifact to reduce knowledge boundaries, collaborate effectively, and cope with the complexities and dynamics of platform ecosystems. We address this challenge by developing two artifacts and combining research from variability modeling, business model dependencies, and system dynamics. This paper presents a design science research approach to develop the platform ecosystem modeling language and the platform ecosystem development tool that support researcher and practitioner by visualizing and simulating platform ecosystems.


VREUD - An End-User Development Tool to Simplify the Creation of Interactive VR Scenes

E. Yigitbas, J. Klauke, S. Gottschalk, G. Engels, in: Proceedings of the 2021 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) , IEEE, 2021



Design Principles for a Crowd-Based Prototype Validation Platform

S. Gottschalk, M.S. Aziz, E. Yigitbas, G. Engels, in: Software Business - 12th International Conference, ICSOB 2021, Drammen, Norway, December 2-3, 2021, Proceedings, Springer, 2021, pp. 205–220

DOI


Situation- and Domain-specific Composition and Enactment of Business Model Development Methods

S. Gottschalk, E. Yigitbas, A. Nowosad, G. Engels, in: Product-focused Software Process Improvement, Springer, 2021

Developing effective business models is a complex process for a company where several tasks (e.g., conduct customer interviews) need to be accomplished, and decisions (e.g., advertisement as a revenue stream) must be made. Here, domain experts can guide the choices of tasks and decisions with their knowledge. Nevertheless, this knowledge needs to match the situation of the company (e.g., financial resources) and the application domain of the product/service (e.g., mobile app) to reduce the risk of developing ineffective business models with low market penetration. This is not covered by one-size-fits-all development methods without tailoring before the enaction. Therefore, we conduct a design science study to create a situation-specific development approach for business models. Based on situational method engineering and our previous work in storing knowledge of methods and models in distinct repositories, this paper shows the situation-specific composition and enaction of business model development methods. First, the method engineer composes the development method out of both repositories based on the situational context. Second, the business developer enacts the method and develops the business model. We implement the approach in a tool and evaluate it with a industrial case study on mobile apps.



Convolutional Hypercomplex Embeddings for Link Prediction

C. Demir, D. Moussallem, S. Heindorf, A. Ngonga Ngomo, in: The 13th Asian Conference on Machine Learning, ACML 2021, 2021

Knowledge graph embedding research has mainly focused on the two smallest normed division algebras, $\mathbb{R}$ and $\mathbb{C}$. Recent results suggest that trilinear products of quaternion-valued embeddings can be a more effective means to tackle link prediction. In addition, models based on convolutions on real-valued embeddings often yield state-of-the-art results for link prediction. In this paper, we investigate a composition of convolution operations with hypercomplex multiplications. We propose the four approaches QMult, OMult, ConvQ and ConvO to tackle the link prediction problem. QMult and OMult can be considered as quaternion and octonion extensions of previous state-of-the-art approaches, including DistMult and ComplEx. ConvQ and ConvO build upon QMult and OMult by including convolution operations in a way inspired by the residual learning framework. We evaluated our approaches on seven link prediction datasets including WN18RR, FB15K-237 and YAGO3-10. Experimental results suggest that the benefits of learning hypercomplex-valued vector representations become more apparent as the size and complexity of the knowledge graph grows. ConvO outperforms state-of-the-art approaches on FB15K-237 in MRR, Hit@1 and Hit@3, while QMult, OMult, ConvQ and ConvO outperform state-of-the-approaches on YAGO3-10 in all metrics. Results also suggest that link prediction performances can be further improved via prediction averaging. To foster reproducible research, we provide an open-source implementation of approaches, including training and evaluation scripts as well as pretrained models.


Drift Detection in Text Data with Document Embeddings

R. Feldhans, A. Wilke, S. Heindorf, M.H. Shaker, B. Hammer, A. Ngonga Ngomo, E. Hüllermeier, in: Intelligent Data Engineering and Automated Learning – IDEAL 2021, Springer International Publishing, 2021


ASSET: A Semi-supervised Approach for Entity Typing in Knowledge Graphs

H.M. Zahera, S. Heindorf, A.N. Ngomo, in: Proceedings of the 11th on Knowledge Capture Conference, ACM, 2021


Simplifying Robot Programming using Augmented Reality and End-User Development

E. Yigitbas, I. Jovanovikj, G. Engels, in: Proceedings of the 18th IFIP TC13 International Conference on Human-Computer Interaction (INTERACT 2021) , Springer, 2021


Using Augmented Reality for Enhancing Planning and Measurements in the Scaffolding Business

E. Yigitbas, S. Sauer, G. Engels, in: Proceedings of the 13th ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS 2021), ACM, 2021


Collaborative Software Modeling in Virtual Reality

E. Yigitbas, S. Gorissen, N. Weidmann, G. Engels, in: Proceedings of the 24th International Conference on Model Driven Engineering Languages and Systems (MODELS'21) , ACM/IEEE, 2021


Ensuring User Interface Adaptation Consistency through Triple Graph Grammers

K. Biermeier, E. Yigitbas, N. Weidmann, G. Engels, in: Proceedings of the International Workshop on Human-Centered Software Engineering for Changing Contexts of Use , 2021


Towards a Decision Support System for Cross-Sectoral Energy Distribution Network Planning

J. Kirchhoff, S.C. Burmeister, C. Weskamp, G. Engels, in: Energy Informatics and Electro Mobility ICT, 2021

Requirements for energy distribution networks are changing fast due to the growing share of renewable energy, increasing electrification, and novel consumer and asset technologies. Since uncertainties about future developments increase planning difficulty, flexibility potentials such as synergies between the electricity, gas, heat, and transport sector often remain unused. In this paper, we therefore present a novel module-based concept for a decision support system that helps distribution network planners to identify cross-sectoral synergies and to select optimal network assets such as transformers, cables, pipes, energy storage systems or energy conversion technology. The concept enables long-term transformation plans and supports distribution network planners in designing reliable, sustainable and cost-efficient distribution networks for future demands.


2020

ProConAR: A Tool Support for Model-based AR Product Configuration

S. Gottschalk, E. Yigitbas, E. Schmidt, G. Engels, in: Human-Centered Software Engineering. HCSE 2020, Springer, 2020

Mobile shopping apps have been using Augmented Reality (AR) in the last years to place their products in the environment of the customer. While this is possible with atomic 3D objects, there is is still a lack in the runtime configuration of 3D object compositions based on user needs and environmental constraints. For this, we previously developed an approach for model-based AR-assisted product configuration based on the concept of Dynamic Software Product Lines. In this demonstration paper, we present the corresponding tool support ProConAR in the form of a Product Modeler and a Product Configurator. While the Product Modeler is an Angular web app that splits products (e.g. table) up into atomic parts (e.g. tabletop, table legs, funnier) and saves it within a configuration model, the Product Configurator is an Android client that uses the configuration model to place different product configurations within the environment of the customer. We show technical details of our ready to use tool-chain ProConAR by describing its implementation and usage as well as pointing out future research directions.


Augmented and Virtual Reality Object Repository for Rapid Prototyping

I. Jovanovikj, E. Yigitbas, S. Sauer, G. Engels, in: Proceedings of the 8th International Working Conference on Human-Centered Software Engineering (HCSE'20), Springer, 2020, pp. 216-224


Der digitale Fußabdruck, Schatten oder Zwilling von Maschinen und Menschen

G. Engels, Gruppe. Interaktion. Organisation. Zeitschrift für Angewandte Organisationspsychologie (GIO) (2020), pp. 363-370


Automating test schedule generation with domain-specific languages

A. Anjorin, N. Weidmann, R. Oppermann, L. Fritsche, A. Schürr, in: Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS 2020, ACM, 2020

DOI


A search-based and fault-tolerant approach to concurrent model synchronisation

N. Weidmann, L. Fritsche, A. Anjorin, in: Proceedings of the 13th ACM SIGPLAN International Conference on Software Language Engineering, SLE 2020, ACM, 2020

DOI


VICToRy: Visual Interactive Consistency Management in Tolerant Rule-based Systems

N. Weidmann, A. Anjorin, J. Cheney, in: Proceedings of the Eleventh International Workshop on Graph Computation Models, GCM@STAF 2020, EPTCS, 2020, pp. 1-12

DOI


A Model-Driven Mutation Framework for Validation of Test Case Migration

I. Jovanovikj, N. Weidmann, E. Yigitbas, A. Anjorin, S. Sauer, G. Engels, in: Proceedings of the First International Conference on Systems Modelling and Management, ICSMM 2020 , Springer, 2020

DOI


Modeling and Analyzing Architectural Diversity of Open Platforms

B. Jazayeri, S. Schwichtenberg, J. Küster, O. Zimmermann, G. Engels, in: Advanced Information Systems Engineering, 2020

DOI




Experiencing and Programming the ENIAC in VR

E. Yigitbas, C.B. Tejedor, G. Engels, in: Proceedings of the Mensch und Computer 2020 (MuC ’20), 2020


UCAI 2020 - 1st International Workshop on User-Centered Artificial Intelligence

M. Augstein, D. Buschek, E. Herder, B. Loepp, E. Yigitbas, J. Ziegler, in: Proceedings of the Mensch und Computer 2020 (MuC ’20), ACM, 2020


VR Training for Warehouse Management

E. Yigitbas, I. Jovanovikj, J. Scholand, G. Engels, in: Proceedings of the 26th ACM Symposium on Virtual Reality Software and Technology (VRST), ACM, 2020


Model-based Product Configuration in Augmented Reality Applications

S. Gottschalk, E. Yigitbas, E. Schmidt, G. Engels, in: Human-Centered Software Engineering. HCSE 2020, Springer, 2020

Augmented Reality (AR) has recently found high attention in mobile shopping apps such as in domains like furniture or decoration. Here, the developers of the apps focus on the positioning of atomic 3D objects in the physical environment. With this focus, they neglect the configuration of multi-faceted 3D object composition according to the user needs and environmental constraints. To tackle these challenges, we present a model-based approach to support AR-assisted product con-figuration based on the concept of Dynamic Software Product Lines. Our approach splits products (e.g. table) into parts (e.g. tabletop, ta-ble legs, funnier) with their 3D objects and additional information (e.g. name, price). The possible products, which can be configured out of these parts, are stored in a feature model. At runtime, this feature model can be used to configure 3D object compositions out of the product parts and adapt to user needs and environmental constraints. The benefits of this approach are demonstrated by a case study of configuring modular kitchens with the help of a prototypical mobile-based implementation.


Challenges in Model-Driven Development of Multi-Platform Augmented Reality Applications

I. Jovanovikj, E. Yigitbas, S. Sauer, G. Engels, Softwaretechnik-Trends, Proceedings of the 22st Workshop Software-Reengineering & Evolution (WSRE) & 11h Workshop Design for Future (DFF) (2020)


Development Framework for Context-Aware Augmented Reality Applications

S.C. Krings, E. Yigitbas, I. Jovanovikj, S. Sauer, G. Engels, in: Proceedings of the 12th ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS 2020), 2020

DOI


Hypothesis-driven Adaptation of Business Models based on Product Line Engineering

S. Gottschalk, F. Rittmeier, G. Engels, in: Proceedings of the 22nd IEEE International Conference on Business Informatics, IEEE, 2020

The continuous innovation of its business models is an important task for a company to stay competitive. During this process, the company has to validate various hypotheses about its business models by adapting to uncertain and changing customer needs effectively and efficiently. This adaptation, in turn, can be supported by the concept of Software Product Lines (SPLs). SPLs reduce the time to market by deriving products for customers with changing requirements using a common set of features, structured as a feature model. Analogously, we support the process of business model adaptation by applying the engineering process of SPLs to the structure of the Business Model Canvas (BMC). We call this concept a Business Model Decision Line (BMDL). The BMDL matches business domain knowledge in the form of a feature model with customer needs to derive hypotheses about the business model together with experiments for validation. Our approach is effective by providing a comprehensive overview of possible business model adaptations and efficient by reusing experiments for different hypotheses. We implement our approach in a tool and illustrate the usefulness with an example of developing business models for a mobile application.


Model-based Hypothesis Engineering for Supporting Adaptation to Uncertain Customer Needs

S. Gottschalk, E. Yigitbas, G. Engels, in: Business Modeling and Software Design, Springer International Publishing, 2020, pp. 276-286

To build successful products, the developers have to adapt their product features and business models to uncertain customer needs. This adaptation is part of the research discipline of Hypotheses Engineering (HE) where customer needs can be seen as hypotheses that need to be tested iteratively by conducting experiments together with the customer. So far, modeling support and associated traceability of this iterative process are missing. Both, in turn, are important to document the adaptation to the customer needs and identify experiments that provide most evidence to the customer needs. To target this issue, we introduce a model-based HE approach with a twofold contribution: First, we develop a modeling language that models hypotheses and experiments as interrelated hierarchies together with a mapping between them. While the hypotheses are labeled with a score level of their current evidence, the experiments are labeled with a score level of maximum evidence that can be achieved during conduction. Second, we provide an iterative process to determine experiments that offer the most evidence improvement to the modeled hypotheses. We illustrate the usefulness of the approach with an example of testing the business model of a mobile application.


Schema Compliant Consistency Management via Triple Graph Grammars and Integer Linear Programming

N. Weidmann, A. Anjorin, in: Proceedings of the 23rd International Conference on Fundamental Approaches to Software Engineering, FASE 2020, Springer, 2020

DOI


Concept-based Co-Migration of Test Cases

I. Jovanovikj, E. Yigitbas, S. Sauer, G. Engels, in: Proceedings of the 8th International Conference on Model-Driven Engineering and Software Development - Volume 1: MODELSWARD, 2020

DOI


Test Case Co-Migration Method Patterns

I. Jovanovikj, E. Yigitbas, S. Sauer, G. Engels, Software Engineering 2020 Workshopband (2020)


Integrated Model-driven Development of Self-adaptive User Interfaces

E. Yigitbas, I. Jovanovikj, K. Biermeier, S. Sauer, G. Engels, International Journal on Software and Systems Modeling (SoSyM) (2020)


On the Development of Context-aware Augmented Reality Applications

E. Yigitbas, I. Jovanovikj, S. Sauer, G. Engels, in: Handling Security, Usability, User Experience and Reliability in User-Centered Development Processes - IFIP WG 13.2/13.5, Springer, LNCS, 2020


Validating Test Case Migration via Mutation Analysis

I. Jovanovikj, A. Nagaraj, E. Yigitbas, A. Anjorin, S. Sauer, G. Engels, in: Proceedings of the 1st IEEE/ACM International Conference on Automation of Software Test AST, ACM, 2020, pp. 31-40


Integrated model-driven development of self-adaptive user interfaces

E. Yigitbas, I. Jovanovikj, K. Biermeier, S. Sauer, G. Engels, Software and Systems Modeling (2020), 19(5), pp. 1057-1081

Modern user interfaces (UIs) are increasingly expected to be plastic, in the sense that they retain a constant level of usability, even when subjected to context changes at runtime. Self-adaptive user interfaces (SAUIs) have been promoted as a solution for context variability due to their ability to automatically adapt to the context-of-use at runtime. The development of SAUIs is a challenging and complex task as additional aspects like context management and UI adaptation have to be covered. In classical model-driven UI development approaches, these aspects are not fully integrated and hence introduce additional complexity as they represent crosscutting concerns. In this paper, we present an integrated model-driven development approach where a classical model-driven development of UIs is coupled with a model-driven development of context-of-use and UI adaptation rules. We base our approach on the core UI modeling language IFML and introduce new modeling languages for context-of-use (ContextML) and UI adaptation rules (AdaptML). The generated UI code, based on the IFML model, is coupled with the context and adaptation services, generated from the ContextML and AdaptMLmodel, respectively. The integration of the generated artifacts, namely UI code, context, and adaptation services in an overall rule-based execution environment, enables runtime UI adaptation. The benefit of our approach is demonstrated by two case studies, showing the development of SAUIs for different application scenarios and a usability study which has been conducted to analyze end-user satisfaction of SAUIs.


2019

Special issue: Selected papers of BPM 2017

J. Carmona, G. Engels, A. Kumar, M. Reichert, Information Systems (2019), pp. 238-239

DOI


2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)

G. Engels, L. Burgueno, A. Pretschner, S. Voss, M. Chaudron, J. Kienzle, M. Völter, S. Gérard, M. Zahedi, E. Bousse, A. Rensink, F. Polack, G. Kappel, 2019

DOI


Values in Computing (Dagstuhl Seminar 19291)

G. Engels, C. Becker, A. Feenberg, M.A. Ferrario, G. Fitzpatrick, Dagstuhl Reports 9(7) (2019)

DOI


Business Models of Store-Oriented Software Ecosystems: A Variability Modeling Approach

S. Gottschalk, F. Rittmeier, G. Engels, in: Business Modeling and Software Design, Springer International Publishing, 2019, pp. 153-169

In the last years, store-oriented software ecosystems are gaining more and more attention from a business perspective. In these ecosystems, third-party developers upload extensions to a store which can be downloaded by end users. While the functional scope of such ecosystems is relatively similar, the underlying business models differ greatly in and between their different product domains (e.g. Mobile Phone, Smart TV). This variability, in turn, makes it challenging for store providers to find a business model that fits their own needs. To handle this variability, we introduce the Business Variability Model (BVM) for modeling business model decisions. The basis of these decisions is the analysis of 60 store-oriented software ecosystems in eight different product domains. We map their business model decisions to the Business Model Canvas, condense them to a variability model and discuss particular variants and their dependencies. Our work provides store providers a new approach for modeling business model decisions together with insights of existing business models. This, in turn, supports them in creating new and improving existing business models.


Component-Based Development of Adaptive User Interfaces

E. Yigitbas, K. Josifovska, I. Jovanovikj, F.. Kalinci, A. Anjorin, G. Engels, in: Proceedings of the 11th ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS 2019), 2019, pp. 13:1--13:7


Process Weakness Patterns for the Identification of Digitalization Potentials in Business Processes

F. Rittmeier, G. Engels, A. Teetz, in: Business Process Management Workshops, Springer International Publishing, 2019, pp. 531-542


MultiSkipGraph: A Self-stabilizing Overlay Network that Maintains Monotonic Searchability

L. Luo, C. Scheideler, T.F. Strothmann, in: Proceedings of the 2019 IEEE 33rd International Parallel and Distributed Processing Symposium (IPDPS '19), 2019

Self-stabilizing overlay networks have the advantage of being able to recover from illegal states and faults. However, the majority of these networks cannot give any guarantees on their functionality while the recovery process is going on. We are especially interested in searchability, i.e., the functionality that search messages for a specific node are answered successfully if a node exists in the network. In this paper we investigate overlay networks that ensure the maintenance of monotonic searchability while the self-stabilization is going on. More precisely, once a search message from node u to another node v is successfully delivered, all future search messages from u to v succeed as well. We extend the existing research by focusing on skip graphs and present a solution for two scenarios: (i) the goal topology is a super graph of the perfect skip graph and (ii) the goal topology is exactly the perfect skip graph.



A Digital Twin-Based Multi-Modal UI Adaptation Framework for Assistance Systems in Industry 4.0

K. Josifovska, E. Yigitbas, G. Engels, in: Proceedings of the 21st International Conference on Human-Computer Interaction (HCII 2019), Springer, LNCS, 2019, pp. 398-409


Reference Framework for Digital Twins within Cyber-Physical Systems

K. Josifovska, E. Yigitbas, G. Engels, in: Proceedings of 5th International Workshop on Software Engineering for Smart Cyber-Physical Systems (SEsCPS'19), IEEE Press, 2019, pp. 25-31


Förderung von Kreativität in studentischen Kleingruppenprojekten in der Informatik – Ein Prototyping-basierter Ansatz

T.F. Strothmann, die hochschullehre (2019)

Dieser Artikel erörtert, ob in studentischen Kleingruppenprojekten in der Informatik Kreativität und die Erarbeitung kreativer Ideen explizit gefördert werden kann. Dazu wird ein Seminarkonzept detailliert vorgestellt, welches auf zwei Grundkonzepten der Informatikpraxis beruht: agiles Projektvorgehen und Prototyping. Die Teilnehmenden des Seminars wurden gezielt in einen Kreativitätsprozess geleitet, indem sie für gegebene moderne Technologien (Virtual Reality, Augmented Reality, Drohnen, etc.) neuartige Nutzungsszenarien entwickeln sollten. Um zu evaluieren, ob das Lehrkonzept erfolgreich ist, wird sowohl die produktbezogene als auch die prozessbezogene Kreativität betrachtet. Für die produktbezogene Kreativität werden die von den Teilnehmenden erstellten Projektideen inklusive der benutzten Prototypingtechnik vorgestellt und bewertet. Die Teilnehmenden haben nicht nur eine enorme Breite an Ideen entwickelt (in der Summe ca. 40 bei 16 Teilnehmenden), sondern insbesondere auch acht Ideen im Verlaufe des Seminars sehr konkret weiterentwickelt. Hinsichtlich der prozessbezogenen Kreativität wird das Lehrkonzept durch mehrere Fragebögen eruiert. Die Studierenden sind mit dem Seminar, der Herangehensweise und den Ergebnissen sehr zufrieden, was unter anderem durch die äußerst positive studentische Veranstaltungskritik (u.a. 1,0 für den Gesamteindruck sowie Atmosphäre in der Veranstaltung) und die Auswertung der Evaluationsfragebögen unterstrichen wird. Auch von externen Beobachtern werden die erarbeiteten Ergebnisse und der Einsatz von Prototyping als sehr positiv bewertet.


WindCORES - Digital Transformation with Renewable Energy

E. Yigitbas, G. Schomaker, International Tube Association (ITAtube) Journal (2019)


Detection and Resolution of Data-Flow Differences in Business Process Models

I. Jovanovikj, E. Yigitbas, C. Gerth, S. Sauer, G. Engels, in: Information Systems Engineering in Responsible Information Systems - CAiSE Forum 2019, Rome, Italy, June 3-7, 2019, Proceedings, 2019, pp. 145-157


Modular Construction of Context-Specific Test Case Migration Methods

I. Jovanovikj, E. Yigitbas, M. Grieger, S. Sauer, G. Engels, in: Proceedings of the 7th International Conference on Model-Driven Engineering and Software Development - Volume 1: MODELSWARD,, SciTePress, 2019, pp. 536-543

DOI


Consistent Runtime Adaptation of User Interfaces

A. Anjorin, E. Yigitbas, H. Kaindl, in: Proceedings of the 8th International Workshop on Bidirectional Transformations (Bx 2019), CEUR-WS.org, 2019, pp. 61-65


Towards Model-based Development of Context-aware Augmented Reality Applications

E. Yigitbas, I. Jovanovikj, S. Sauer, G. Engels, Softwaretechnik-Trends, Proceedings of the 21st Workshop Software-Reengineering & Evolution (WSRE) & 10th Workshop Design for Future (DFF) (2019), 39(2), pp. 39-40


Context- and Data-driven Satisfaction Analysis of User Interface Adaptations Based on Instant User Feedback

E. Yigitbas, A.. Hottung, S. Mansfield Rojas, A. Anjorin, S. Sauer, G. Engels, Proceedings of the ACM on Human-Computer Interaction (2019), 3, pp. 19:1-19:20


On-the-fly Usability Evaluation of Mobile Adaptive UIs through Instant User Feedback

E. Yigitbas, I. Jovanovikj, K. Josifovska, S. Sauer, G. Engels, in: Proceedings of the 17th IFIP TC.13 International Conference on Human-Computer Interaction (INTERACT 2019), Springer, LNCS, 2019, pp. 563-567


A Value-Centered Approach for Unique and Novel Software Applications

B. Senft, F. Rittmeier, H.G. Fischer, S. Oberthür, in: Design, User Experience, and Usability. Practice and Case Studies, 2019

DOI


A Context-aware Virtual Reality First Aid Training Application

E. Yigitbas, J. Heindörfer, G. Engels, in: Proceedings of the Mensch und Computer 2019 (MuC ’19), ACM, 2019, pp. 885--888


A Model-based Framework for Context-aware Augmented Reality Applications

E. Yigitbas, I. Jovanovikj, S. Sauer, G. Engels, in: Handling Security, Usability, User Experience and Reliability in User-Centered Development Processes (IFIP WG 13.2 & WG 13.5 International Workshop @ INTERACT2019), 2019


ABIS 2019 – 23rd International Workshop on Personalization and Recommendation on the Web and Beyond

M. Augstein, E. Herder, W. Wörndl, E. Yigitbas, in: 30th ACM Conference on Hypertext and Social Media (HT ’19), September 17–20, 2019, Hof, Germany, ACM, 2019


Vandalism Detection in Crowdsourced Knowledge Bases

S. Heindorf, Universität Paderborn, 2019




Projektmanagement und Vorgehensmodelle 2019. Neue Vorgehensmodelle in Projekten – Führung, Kulturen und Infrastrukturen im Wandel.

O. Linssen, M. Mikusz, A. Volland, E. Yigitbas, M. Engstler, M. Fazal-Baqaie, M. Kuhrmann. Projektmanagement und Vorgehensmodelle 2019. Neue Vorgehensmodelle in Projekten – Führung, Kulturen und Infrastrukturen im Wandel.. 2019.


Partizipation von Beschäftigten in der Gestaltung einer digitalisierten Arbeitswelt 4.0 mittels einer Canvas-Methode

H.G. Fischer, F. Rittmeier, T.F. Strothmann, N. Schwenniger, in: Arbeit 4.0 im Mittelstand, Springer Gabler, 2019

Sinnvolle und gebrauchstaugliche digitale Assistenzsysteme, die Beschäftigte bei ihren alltäglichen Aufgaben unterstützen, stellen eine Herausforderung für viele Organisationen hinsichtlich der individuellen und organisationalen Akzeptanz einschließlich der Gebrauchstauglichkeit (Usability), dem Benutzererlebnis (User Experience, UX) und „Arbeit 4.0“-Aspekten dar. Vorhandene Methoden des Software Engineering sind nicht geeignet, Beschäftigte angemessen in die Gestaltung und Entwicklung zu integrieren und Lösungskonzepte solcher Systeme auf Augenhöhe zu betrachten. In diesem Beitrag wird eine leichtgewichtige Canvas-Methode vorgestellt, die sich mit diesen Herausforderungen befasst. Sie umfasst die menschliche, die geschäftliche sowie die technologische Perspektive in einem gemeinsamen Kommunikationsinstrument, dem „Digital Assistance System Canvas“. Erste Evaluationen zeigen, dass die Teilnehmenden das Canvas-Konzept schätzen und die Methode vielseitig in verschiedenen Szenarien einsetzbar ist. Vielfältige Fragen in den Canvas-Bausteinen bereichern die gemeinsame Diskussion über neue Systeme und die Verbesserung bzw. Sicherstellung der Akzeptanz sowie die Denkweise in frühen Phasen des Design- und Entwicklungsprozesses.


A feature-based classification of triple graph grammar variants

N. Weidmann, R. Oppermann, P. Robrecht, in: Proceedings of the 12th ACM SIGPLAN International Conference on Software Language Engineering - SLE 2019, ACM, 2019

DOI


Consistency management via a combination of triple graph grammars and linear programming

N. Weidmann, A. Anjorin, E. Leblebici, A. Schürr, in: Proceedings of the 12th ACM SIGPLAN International Conference on Software Language Engineering - SLE 2019, ACM, 2019

DOI


Verteiltes Warenwirtschaftssystem [Distributed Warehouse System]

T. Göllner, J. Schwarz, S. Gottschalk, S. Sauer. Verteiltes Warenwirtschaftssystem [Distributed Warehouse System], Patent DE 10 2018 206 390. 2019.

Beschrieben ist ein verteiltes Warenwirtschaftssystem, bei dem der Kunde, Händler, und der Hersteller vernetzt sind. Dies wird bewerkstelligt durch einen Cloud-Speicher (105), der Cloud-Speicher (105) aufweisend ein Mittel zum Speichern (105a) von Daten, ein Mittel zum Empfangen von ersten Daten von einem ersten Netzwerkteilnehmer (110), wobei die ersten Daten zugehörig sind zu einem physischen Objekt, ein Mittel zum Empfangen von Anfragedaten von einem zweiten Netzwerkteilnehmer (120), ein Mittel zum Empfangen von zweiten Daten von einem dritten Netzwerkteilnehmer (130), wobei die zweiten Daten zugehörig sind zu den ersten Daten und zumindest ein Datum aufweisen, welches angepasst ist, die ersten Daten zu ändern in Abhängigkeit der empfangenen Anfragedaten, ein Mittel zum Ändern der ersten Daten basierend zumindest im Teil auf den zweiten Daten und den Anfragedaten und ein Mittel zum Senden eines geänderten Teils der ersten Daten von dem Cloud-Speicher (105) an den ersten Netzwerkteilnehmer (110).


Intertwined Development of Business Model and Product Functions for Mobile Applications: A Twin Peak Feature Modeling Approach

S. Gottschalk, F. Rittmeier, G. Engels, in: Software Business, Springer International Publishing, 2019, pp. 192-207

Mobile app stores like Apple's AppStore or Google's PlayStore are highly competitive markets for third-party developers wanting to develop successful applications. During the development process, many developers focus on the multitude of product functions but neglect the business model as an equally important part. As a result, developers often fail to meet customer needs, leading to unnecessary development costs and poor market penetration. This, in turn, raises the question of how we intertwine the business model and product functions during the development process to ensure a better alignment between the two. In this paper, we show this intertwined development by adapting the concept of Twin Peaks to the business model and product functions. Based on feature modeling as an abstraction layer, we introduce the concept of a Business Model Decision Line (BMDL) to structure the business model decisions and their relation to product functions structured in a Software Product Line (SPL). The basis of our feature models is the analysis of top listed applications in the app stores of Apple and Google. To create and modify both models, we provide an incremental feature structuring and iterative feature selection process. This combination of abstraction layer and development process supports third-party developers to build successful applications both from a business and a product perspective.


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