Abstract: Over the last two decades, agile methods have transformed and brought unique changes to software development practice by strongly emphasizing team collaboration, customer involvement, and change tolerance. The success of agile methods for small, co-located teams has inspired organizations to increasingly apply agile practices to large-scale efforts. Since these methods are originally designed for small teams, unprecedented challenges occur when introducing them at larger scale, such as inter-team coordination and communication, dependencies with other organizational units or general resistances to changes. Compared to the rich body of agile software development literature describing typical challenges, recurring challenges of stakeholders and initiatives in large-scale agile development has not yet been studied through secondary studies sufficiently. With this paper, we aim to fill this gap by presenting a structured literature review on challenges in large-scale agile development. We identified 79 challenges grouped into eleven categories.

Abstract: The digital transformation of our life changes the way we work, learn, communicate, and collaborate. Enterprises are presently transforming their strategy, culture, processes, and their information systems to become digital. The digital transformation deeply disrupts existing enterprises and economies. Digitization fosters the development of IT systems with many rather small and distributed structures, like Internet of Things, Microservices and mobile services. Since years a lot of new business opportunities appear using the potential of services computing, Internet of Things, mobile systems, big data with analytics, cloud computing, collaboration networks, and decision support. Biological metaphors of living and adaptable ecosystems provide the logical foundation for self-optimizing and resilient run-time environments for intelligent business services and adaptable distributed information systems with service-oriented enterprise architectures. This has a strong impact for architecting digital services and products following both a value-oriented and a service perspective. The change from a closed-world modeling world to a more flexible open-world composition and evolution of enterprise architectures defines the moving context for adaptable and high distributed systems, which are essential to enable the digital transformation. The present research paper investigates the evolution of Enterprise Architecture considering new defined value-oriented mappings between digital strategies, digital business models and an improved digital enterprise architecture.

Abstract: Industry 4.0 is an emerging business paradigm that is reaping the benefits of enabling technologies driving intelligent systems and environments. By acquiring, processing and acting upon various kinds of relevant context information, smart automated manufacturing systems can make well-informed decisions to adapt and optimize their production processes at runtime. To manage this complexity, the manufacturing world is proposing the 'Digital Twin' model to represent physical products in the real space and their virtual counterparts in the virtual space, with data connections to tie the virtual and real products together for an augmented view of the manufacturing workflow. The benefits of such representations are simplified process simulations and efficiency optimizations, predictions, early warnings, etc. However, the robustness and fidelity of digital twins are a critical concern, especially when independently developed production systems and corresponding digital twins interfere with one another in a manufacturing workflow and jeopardize the proper behavior of production systems. We therefore evaluate the addition of safeguards to digital twins for smart cyber-physical production systems (CPPS) in an Industry 4.0 manufacturing workflow in the form of feature toggles that are managed at runtime by software circuit breakers. Our evaluation shows how these improvements can increase the robustness of interacting digital twins by avoiding local errors from cascading through the distributed production or manufacturing workflow.

Abstract: Nowadays, both agile development and enterprise architecture are often employed in large organizations. However there is still some confusion if these can and should be used together, and there is not much research about the possible interplay. The aim of this study is to bring new knowledge to the field of enterprise architecture and its relation to agile development. Twelve qualitative interviews with professionals in different roles, such as developers and architects, have been carried out. The participants belong to five different companies and the information obtained from them has been used to compare opinions and stated challenges regarding agile and EA. We found that some common opinions among the interviewees are; 1) agile development and enterprise architecture can be combined, 2) there are clear communication problems among architects, different teams, and project owners, and 3) there is a lack of system and application reusability.

Abstract: Industry 4.0 has begun to shape the way organizations operate by emphasizing the need for a duality between physical machines and sensors, and the (big) data they generate, exchange and use. Manufacturing is one of several industries which is expected to be impacted by this technological revolution. Increasing the information flows and integration of systems within organizations, and along the supply chain is considered one of the main challenges that needs to be addressed by these organizations. One approach for addressing this challenge is to investigate how this abundance of (big) operational data can be used in combination with IT-driven design approaches, such as Enterprise Architecture. Therefore, in this paper we propose our vision for Enterprise Architecture 4.0, i.e. an extended Enterprise Architecture approach for the context of Industry 4.0, and we give an account of our (work-in-progress) efforts to design a model management and analytics software platform supporting this vision. The usage of the software tool is exemplified with the help of a case study with an organization that develops IT and automation systems for the husbandry sector.

Abstract: The Object Management Group maintains two notations to model business processes, BPMN and CMMN. While the two follow different approaches, both offer structures to model flexible processes or parts thereof. This gives rise to the question which standard should be chosen to adequately model such processes. We compare BPMN with a focus on its ad-hoc sub-process with elements of CMMN case models along a practical case study. While BPMN offers a certain degree of flexibility, CMMN has several benefits but also drawbacks. We discuss advantages and disadvantages of both notations. To answer the question of which notation to use for modeling flexible processes, we derive simple guidelines to help in making an informed choice.

Abstract: The BPMN 2.0 standard is nowadays largely used to model distributed informative systems in both academic and industrial contexts. The notation makes possible to represent these systems from different perspectives. A local perspective, using collaboration diagrams, to describe the internal behaviour of each component of the systems, and a global perspective, using choreography diagrams, where the interactions between system components are highlighted without exposing their internal structure. In this paper, we propose a formal approach for checking conformance of collaborations, representing possible system implementations, with respect to choreographies, representing global constraints concerning components' interactions. In particular, we provide a direct formal operational semantics for both BPMN collaboration and choreography diagrams, and we formalise the conformance concept by means of two relations defined on top of the semantics. To support the approach into practice we have developed the C 4 tool. Its main characteristic is to make the exploited formal methods transparent to systems designers, thus fostering a wider adoption of them in the development of distributed informative systems. We illustrate the benefits of our approach by means of a simple, yet realistic, example concerning a traveling scenario.

Abstract: Enterprise computing applications generally consists of several inter-related business processes linked together via shared data objects and events. We address the open challenge of providing formal modelling and implementation techniques for such enterprise computing applications, introducing the declarative, data-centric and event-driven process language RESEDA for REactive SEmi-structured DAta. The language is inspired by the computational model of spreadsheets and recent advances in declarative business process modelling notations. The key idea is to associate either input events or reactive computation events to the individual elements of semi-structured data and declare reactive behaviour as explicit reaction rules and constraints between these events. Moreover, RESEDA comes with a formal operational semantics given as rewrite rules supporting both formal analysis and persistent execution of the application as sequences of rewrites of the data. The data, along with the set of constraints, thereby at the same time constitutes the specification of the data, its behaviour and the run-time execution component. This key contribution of the paper is to introduce the RESEDA language, its formal execution semantics and give a sufficient condition for liveness of programs. We also establish Turing-equivalence of the language independently of the choice of underlying data expressions and exemplify the use of RESEDA by a running example of an online store. A prototype implementation of RESEDA and the examples of the paper are available on-line at http://dcr.tools/reseda.

Abstract: Business process management is often deployed to improve enterprise integration, but its impact is yet to reach manufacturing operations. We propose the concept of unified process management that facilitates integration between business management and manufacturing operations. The proposition is presented as an updated enterprise architecture for computer integrated manufacturing, converged around a centralized process management system. The process management system can orchestrate both business and operations activities by issuing work items to humans and robots connected via the internet-of-things. We present a realization of such a process management system and evaluate the proposition with an industrial case study. The results support the unification of process management as an enabler of smart manufacturing.

Abstract: The new era of digitization increases the impact of IT on the overall success of organizations. Even though the business generally recognizes the importance of IT, business-IT alignment is still considered a major challenge by IT executives. A widely adapted Enterprise Architecture Management tool addressing this challenge is the business capability map. However, there are only few approaches specifying the creation of business capability maps. This paper presents a case study describing the initiation of a business capability map at a medium-sized, state-controlled organization following an approach to business capability map implementation presented by The Open Group. Based on the case study, we detail each phase of the approach presenting necessary activities and resulting artifacts. Additionally, lessons learned are presented with the major finding being that an involvement of the whole business leadership leads to a better business-IT alignment, a common language, and a better understanding between all business units. Furthermore, a business capability map provides a suitable tool for structuring strategy development.

Abstract: The environment of organizations is changing more rapidly in recent years, which makes it increasingly more difficult to stay competitive. Organizations need to ensure that when they make transformations, they focus on maintaining and improving their strategic alignment. Strategic alignment is a process of continuous change which focuses on creating a synergy between the position of the organization within the competitive environment and the design of the appropriate structure to support its execution. However, while many developments have been made over the past few decades, there are still some areas which could benefit from further research. One such example is relating high-level strategic information and plans to the detailed enterprise architecture (EA) of an organization. Therefore, in this paper, we choose to explore how several of the most popular strategy techniques can be modelled with the help of concepts from the EA modeling language ArchiMate, in the context of the strategy process. Additionally, we introduce the software tool which was developed to support the modeling of these strategy techniques with the EA modeling language ArchiMate.

Abstract: Enterprise Integration Patterns (EIPs) and their extensions denote the informally described building blocks of current Enterprise Application Integration (EAI) systems. Although a recent approach strives to provide an EIP formalization based on Coloured Petri Nets (CPNs), it does not completely consider EAI requirements, such as complex data, transacted resources and time. In the absence of a comprehensive formal definition, the patterns cannot be verified, and thus a formal foundation of EAI is missing. In this work, we leverage the novel db-net approach that finds a better balance between the data and process-related aspects than CPNs and we extend it according to the EAI requirements that we systematically collect on a pattern level. Then we discuss pattern realizations, and evaluate our approach for comprehensiveness, test correctness, and show its applicability.

Abstract: Enterprise Architecture (EA) is a widely accepted means to ease the alignment of IS projects with enterprise-wide objectives. One central artifact of EA are EA models, which provide a holistic view on the organization and support EA's stakeholder to create added value. As EA collects its data from different sources, the data can be contradictory. This work contributes to existing research by proposing a novel approach to deal with contradictory data without solving the thereby caused conflicts. In order to achieve this objective, we refine the Predictive, Probabilistic Architecture Modeling Framework (P²AMF) introduced by Johnson et al., which already incorporates a way to represent uncertainty regarding the existence of modelled entities. To make our technique usable, we generalize P²AMF from its UML/OCL notation to a graph presentation in order to apply it to EA models notated in arbitrary notations like ArchiMate. Furthermore, we add alternative scenarios in different versions along a time series to meet the requirements of a distributed EA evolution. To show the applicability of our approach, we developed a proof of concept prototype by implementing the proposed calculations and guidelines on a Neo4j graph database. Last, we argue that our approach meets the stated requirements of a distributed EA evolution.

Abstract: In recent years, many deployment systems have been developed that process deployment models to automatically provision applications. The main objective of these systems is to shorten delivery times and to ensure a proper execution of the deployment process. However, these systems mainly focus on the correct technical execution of the deployment, but do not check whether the deployed application is working properly. Especially in DevOps scenarios where applications are modified frequently, this can quickly lead to broken deployments, for example, if a wrong component version was specified in the deployment model that has not been adapted to a new database schema. Ironically, even hardly noticeable errors in deployment models quickly result in technically successful deployments, which do not work at all. In this paper, we tackle these issues. We present a modeling concept that enables developers to define deployment tests directly along with the deployment model. These tests are then automatically run by a runtime after deployment to verify that the application is working properly. To validate the technical feasibility of the approach, we applied the concept to TOSCA and extended an existing open source TOSCA runtime.

Abstract: Industry 4.0 has become an increasing driver of change in the manufacturing industry. However, companies are struggling with the often risky and expensive IT transformation projects that are needed to reach full automation of the sales, production and logistics cycle. We observed a lack of research on the practice of modeling and planning IT transformations towards Industry 4.0. To form the basis of research in this area, we conducted a series of expert interviews on the topic of enterprise architecture transformation planning in the context of Industry 4.0. As a result, we identified several pressing challenges that need to be addressed by organizations to successfully model, plan, and execute such IT transformations. This paper contributes to theory by identifying problems and potential design artifacts that are able to mitigate these problems.

Abstract: Power grids form the central critical infrastructure in all developed economies. Disruptions of power supply can cause major effects on the economy and the livelihood of citizens. At the same time, power grids are being targeted by sophisticated cyber attacks. To counter these threats, we propose a domain-specific language and a repository to represent power grids and related IT components that control the power grid. We apply our tool to a standard example used in the literature to assess its expressiveness.

Abstract: In the era of big data, new challenges occur in the field of data federation research. New types of data sources with new formats of data have emerged, and end users need to conduct complex search and data analytical tasks, which impose requirements such flexible data federation, customized security mechanism and high-performance processing (for example, near real time query). To address these challenges, this paper proposes a data federation platform named FEDSA and reports on an initial implementation. Distinctive features of the platform include process-driven data federation, Data Federation as a Service, a simple query language over a high-level common data model, data security protection over all federation services, query re-writing and full distribution. We demonstrate how these features address the challenges, discuss the performance of the current implementation, and outline future extensions.

Abstract: Due to the rapid shift of companies towards superb customer experience and satisfaction, ticketing systems have come into a prominence and represent a strategic element in business competitiveness. Different software companies have developed very effective software tools for issue tracking, nevertheless, some sub-processes and tasks within the ticketing systems are still performed manually. These manually performed tasks represent bottlenecks, especially at large organizations they result in declined productivity and increased response time. Advancements in machine learning can be used in a novel way in which they are combined with the traditional issue tracking and ticketing systems on the market, to enable optimal operational efficiency in the Customer Service and Support(CSS) Department of large-scale businesses that deal with customer reports. This paper proposes an integrated approach to customer support by treating three seemingly different bottlenecks in the ticketing system: spam detection, ticket assignment and sentiment analysis. We use primary data to implement and apply the proposed machine learning approach. The evaluation shows promising results in terms of accuracy and efficiency of our approach.

Abstract: Information systems produce different types of event logs; in many situations, it may be desirable to look for trends inside these logs. We show how trends of various kinds can be computed over such logs in real time, using a generic framework called the trend distance workflow. Many common computations on event streams turn out to be special cases of this workflow, depending on how a handful of workflow parameters are defined. This process has been implemented and tested in a real-world event stream processing tool, called BeepBeep. Experimental results show that deviations from a reference trend can be detected in realtime for streams producing up to thousands of events per second.

Abstract: This paper is concerned with the engineering of modelling languages, and the engineering of modelling languages for enterprise architecture in particular. In line with this, this paper aims to provide two key contributions. Firstly, it aims to contribute to the field of (enterprise) modelling language engineering by refining an existing approach for the engineering of requirements on modelling languages. It will do so, by suggesting specific classes of purpose and quality criteria for models and their creation. The second contribution involves an initial application of the latter approach, in terms of a critical reflection on the language requirements as formulated for the ArchiMate standard.

Abstract: Contemporary process management systems support users during the execution of repetitive, predefined business processes. However, when unforeseen situations occur, which are not part of the process model serving as the template for process execution, contemporary process management technology is often unable to offer adequate user support. One solution to this problem is to allow for ad-hoc changes to process models, i.e., changes that may be applied on the fly to a running process instance. As opposed to the widespread activity-centric process modeling paradigm, for which the support of instance-specific ad-hoc changes is well researched, albeit not supported by most commercial solutions, there is no corresponding support for ad-hoc changes in other process support paradigms, such as artifact-centric or object-aware process management. This paper presents concepts for supporting such ad-hoc changes in object-aware process management, and gives insights into the challenges we tackled when implementing this kind of process flexibility in the PHILharmonicFlows process execution engine. The development of such advanced features is highly relevant for data-centric BPM, as the research field is generally perceived as having low maturity when compared to activity-centric BPM.

Abstract: COBIT 5 is a widely-used framework for implementing sound governance of enterprise IT (GEIT). Despite the existence of official guidance, there are still several challenges that we can encounter. Currently, the ISACA's official implementation solution follows a sequentially ordered process corresponding to a traditional approach, however, organizations are increasingly embracing more agile ones for managing projects where the solution is not clear from the beginning. Using the Design Science Research Methodology, the authors analyse the current state of art and provide a Scrum based methodology for managing at team level a COBIT 5 programme. With a hybrid agile-traditional approach, the authors aim to eliminate some known challenges of COBIT 5, such as lack of support from top management and misaligned scopes and solutions. Additionally, in this paper, the authors present the results obtained from applying the designed methodology in a COBIT 5 programme in the Portuguese Finance Ministry, as well as inspect two series of interviews: 10 performed with experts from both Scrum and COBIT 5 areas to evaluate the solution, and 6 others with the team involved in the demonstration programme, to understand if the objectives where achieved. The article ends with lessons learned, limitations and future work.

Abstract: Industry 4.0 has become an important concept in the manufacturing industry that increasingly drives change. However, the implementation of this concept is associated to business critical and expensive IT transformation projects, with which companies are currently struggling. We observed a lack of research on the practice of planning IT transformation projects towards Industry 4.0 and its modeling support within currently available EA tools. To investigate this gap, we conducted a series of expert interviews and a tool survey. As a result, we identified several drawbacks of EA tools that need to be addressed in order to be able to efficiently support the modeling and planning of such IT transformations.

Abstract: We demonstrate a tool for identifying, prioritizing and evaluating vulnerabilities in software. The tool aims to improve security in products by making maintenance more efficient and robust. Software components and release versions are matched with vulnerability information from open resources. The results are visualized on several different levels, ranging from product portfolio and individual products, to specific releases and vulnerabilities. The tool keeps track of how security evolves over time in deployed releases, and also how the maintenance organization progresses in evaluating new vulnerabilities. This will result in more efficient, accurate, and robust security analysis and awareness within the organization, and the anticipated long term effect is more secure products.

Abstract: Complexity management has become an essential undertaking for enterprise architecture (EA). It strives for an optimal level of complexity to efficiently and effectively use the EA for its intended purposes. The basis for complexity management is measurement, yet no standardized or proven method for EA complexity measurement currently exists, nor is there consensus about the attributes contributing to complexity. Additionally, the many stakeholders involved in an EA all have a different perception of complexity, leading to the notion of subjective complexity. This research aims to incorporate objective and subjective complexity metrics in a single EA complexity measurement model. A systematic literature review has been carried out to make an inventory of existing complexity metrics. Semi-structured interviews were used to gain insights in stakeholder perceptions and subjective complexity attributes. Based on these results, a conceptual model of EA complexity was designed. The constructs in this model have been operationalized with metrics to create a measurement instrument of EA complexity. The model and its operationalization was then validated through expert interviews, and tested during a case study, where it has been applied in practice.

Abstract: The paper is an experience report on applying a socio-technical approach to business process improvement. The approach is based on an augmented socio-technical matrix (STS-matrix) that differentiates 4 quadrants of socio-technical system: (1) culture/mind set, (2) type of structure, (3) methods/techniques, and (4) type of technology. It was applied in a study related to knowledge creation and sharing in a sales process in a multinational company. The augmented STS-matrix has been used for both holistic analysis of the situation and developing suggestions for organizational intervention.

Abstract: CMMN, developed by OMG, is a graphical language for modeling and managing knowledge work. Being highly unstructured and unpredictable and therefore very challenging, knowledge work is studied by Adaptive Case Management. CMMN encompasses a variety of ACM concepts, facilitating case management, however, is still bound by the traditional separation of design and execution phase, restricting adaptability. However, CMMN can be proven useful to study a category of cases, prior to its automation. In this paper, the restrictions of CMMN are discussed, based on current CMMN-enabled platforms. Having them in mind, we suggest alternatives to empower knowledge workers with CMMN possible benefits, without restricting their work, which worth further investigation. Case learning is introduced as such an alternative.

Abstract: With the rise of Internet of Things, end-users expect to obtain data from well-connected smart devices and stations through data services being provisioned in distributed architectures. Such services could be aggregated in a number of smart ways to provide the end-users and third-party applications with sophisticated data (e.g., weather data coupled with soil pollution), resulting in a growing number of service offerings to be requested. Service offerings that have been shortlisted for a certain data request (e.g., rainfall in a particular farming site) need to be ranked according to the end-users' preference. Service level agreements, i.e., the mutual responsibilities between the service provider and its consumers, address this sort of preference. Unfortunately, provisioning quality-aware services under this term still stays on the sidelines. In this paper, we propose a novel service architecture where the service level agreements shall be: (i) accumulated overtime on IoT service transactions; (ii) compiled when aggregating IoT services; (iii) used as a ranking criterion for suggesting IoT service offerings. We demonstrate our new approach in the service provisioning of agricultural datasets taken from a farming site of the Mekong Delta in Vietnam.

Abstract: Simulation is often used to provide quantitative predictions on the performance of business processes. However, the current available business process simulation engines only support basic resource constructs and even these are sometimes lacking. This leads to simulated performance metrics that can deviate significantly from the real process performance. This paper provides an overview of the quantitative effects of incorporating these advanced resource constructs in business process simulation. Experiments are conducted to assess whether there are significant differences between the effects of using basic resource constructs and using their advanced counterparts. The main conclusions are: that the allocation strategy deployed by the resources is of significant influence on the performance of the process; that the ability to assign resources to multiple roles has a significant influence; and that simulation replications are absolutely necessary to produce reliable simulation results. These insights can be used by researchers and practitioners to understand the validity of the results of their simulation studies and as a direction for future research.