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The internet of things, enterprise social networks, adaptive case management, mobility systems, analytics for big data, and cloud environments are emerging to support smart connected i.e. digital products and services and the digital transformation. Biological metaphors for living and adaptable ecosystems are currently providing the logical foundation for resilient run-time environments with serviceoriented digitization architectures and for self-optimizing intelligent business services and related distributed information systems. We are investigating mechanisms for flexible adaptation and evolution of information systems with digital architecture in the context of the ongoing digital transformation. The goal is to support flexible and agile transformations for both business and related information systems through adaptation and dynamical evolution of their digital architectures. The present research paper investigates mechanisms of decision analytics for digitization architectures, putting a spotlight to internet of things micro-granular architectures, by extending original enterprise architecture reference models with digitization architectures and their multi-perspective architectural decision management.
The digitization of our society changes the way we live, work, learn, communicate, and collaborate. This disruptive change interacts with all information processes and systems that are important business enablers for the context of digitization since years. Our aim is to support flexibility and agile transformations for both business domains and related information technology with more flexible enterprise information systems through adaptation and evolution of digital enterprise architectures. The present research paper investigates the continuous bottom-up integration of micro-granular architectures for a huge amount of dynamically growing systems and services, like microservices and the Internet of Things, as part of a new digital enterprise architecture. To integrate micro granular architecture models to living architectural model versions we are extending more traditional enterprise architecture reference models with state of art elements for agile architectural engineering to support the digitization of products, services, and processes.
The Internet of Things (IoT), enterprise social networks, adaptive case management, mobility systems, analytics for big data, and cloud services environments are emerging to support smart connected products and services and the digital transformation. Biological metaphors of living and adaptable ecosystems with service oriented enterprise architectures provide the foundation for self-optimizing and resilient run-time environments for intelligent business services and related distributed information systems. We are investigating mechanisms for flexible adaptation and evolution for the next digital enterprise architecture systems in the context of the digital transformation. Our aim is to support flexibility and agile transformation for both business and related enterprise systems through adaptation and dynamical evolution of digital enterprise architectures. The present research paper investigates mechanisms for decision case management in the context of multi-perspective explorations of enterprise services and Internet of Things architectures by extending original enterprise architecture reference models with state of art elements for architectural engineering for the digitization and architectural decision support.
Social networks, smart portable devices, Internet of Things (IoT) on base of technologies like analytics for big data and cloud services are emerging to support flexible connected products and agile services as the new wave of digital transformation. Biological metaphors of living and adaptable ecosystems with service-oriented enterprise architectures provide the foundation for self-optimizing and resilient run-time environments for intelligent business services and related distributed information systems. We are extending Enterprise Architecture (EA) with mechanisms for flexible adaptation and evolution of information systems having distributed IoT and other micro-granular digital architecture to support next digitization products, services, and processes. Our aim is to support flexibility and agile transformation for both IT and business capabilities through adaptive digital enterprise architectures. The present research paper investigates additionally decision mechanisms in the context of multi-perspective explorations of enterprise services and Internet of Things architectures by extending original enterprise architecture reference models with state of art elements for architectural engineering and digitization.
The digital transformation of our society changes the way we live, work, learn, communicate, and collaborate. This disruptive change drive current and next information processes and systems that are important business enablers for the context of digitization since years. Our aim is to support flexibility and agile transformations for both business domains and related information technology with more flexible enterprise information systems through adaptation and evolution of digital architectures. The present research paper investigates the continuous bottom-up integration of micro-granular architectures for a huge amount of dynamically growing systems and services, like microservices and the Internet of Things, as part of a new composed digital architecture. To integrate micro-granular architecture models into living architectural model versions we are extending enterprise architecture reference models by state of art elements for agile architectural engineering to support digital products, services, and processes.
Enterprises are presently transforming their strategy, culture, processes, and their information systems to become more 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 or mobile systems. Since years a lot of new business opportunities appeared using the potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. This has a strong impact for architecting digital services and products. The change from a closed-world modeling perspective to more flexible open-world composition and evolution of system architectures defines the moving context for adaptable systems, which are essential to enable the digital transformation. In this paper, we are focusing on a decision-oriented architectural composition approach to support the transformation for digital services and products.
Enterprises are currently transforming their strategy, processes, and their information systems to extend their degree of digitalization. The potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, artificial intelligence, big data with analytics, mobile systems, collaboration networks, and cyber physical systems both drives and enables new business designs. Digitalization deeply disrupts existing businesses, technologies and economies and fosters the architecture of digital environments with many rather small and distributed structures. This has a strong impact for new value producing opportunities and architecting digital services and products guiding their design through exploiting a Service-Dominant Logic. The main result of the book chapter extends methods for integral digital strategies with value-oriented models for digital products and services which are defined in the framework of a multi-perspective digital enterprise architecture reference model.
Digitization fosters the development of IT environments with many rather small structures, like Internet of Things (IoT), microservices, or mobility systems. They are needed to support flexible and agile digitized products and services. The goal is to create service-oriented enterprise architectures (EA) that are self optimizing and resilient. The present research paper investigates methods for decision-making concerning digitization architectures for Internet of Things and microservices. They are based on evolving enterprise architecture reference models and state of the art elements for architectural engineering for microgranular systems. Decision analytics in this field becomes increasingly complex and decision support, particularly for the development and evolution of sustainable enterprise architectures, is sorely needed. The challenging of the decision processes can be supported with in a more flexible and intuitive way by an architecture management cockpit.
Digitization of societies changes the way we live, work, learn, communicate, and collaborate. In the age of digital transformation IT environments with a large number of rather small structures like Internet of Things (IoT), microservices, or mobility systems are emerging to support flexible and agile digitized products and services. Adaptable ecosystems with service oriented enterprise architectures are the foundation for self-optimizing, resilient run-time environments and distributed information systems. The resulting business disruptions affect almost all new information processes and systems in the context of digitization. Our aim are more flexible and agile transformations of both business and information technology domains with more flexible enterprise information systems through adaptation and evolution of digital enterprise architectures. The present research paper investigates mechanisms for decision-controlled digitization architectures for Internet of Things and microservices by evolving enterprise architecture reference models and state of the art elements for architectural engineering for micro-granular systems.
In current times, a lot of new business opportunities appeared using the potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. Enterprises are presently transforming their strategy, culture, processes, and their information systems to become more digital. The digital transformation deeply disrupts existing enterprises and economies. Digitization fosters the development of IT environments with many rather small and distributed structures, like Internet of Things. This has a strong impact for architecting digital services and products. The change from a closed-world modeling perspective to more flexible open-world and living software and system architectures defines the moving context for adaptable and evolutionary software approaches, which are essential to enable the digital transformation. In this paper, we are putting a spotlight to service oriented software evolution to support the digital transformation with micro granular digital architectures for digital services and products.
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.
Presently, many companies are transforming their strategy and product base, as well as their culture, processes and information systems to become more digital or to approach for a digital leadership. In the last years new business opportunities appeared using the potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, edge and fog computing, social networks, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. Digitization fosters the development of IT environments with many rather small and distributed structures, like the Internet of Things, Microservices, or other micro-granular elements. This has a strong impact for architecting digital services and products. The change from a closed-world modeling perspective to more flexible open-world composition and evolution of micro-granular system architectures defines the moving context for adaptable systems. We are focusing on a continuous bottom-up integration of micro-granular architectures for a huge amount of dynamically growing systems and services, as part of a new digital enterprise architecture for service dominant digital products.
Unternehmen sind derzeit dabei, ihre Strategie, ihre Prozesse und ihre Informationssysteme zu verändern, um ihren Digitalisierungsgrad zu erhöhen. Das Potenzial des Internets und verwandter digitaler Technologien wie Internet der Dinge, Services Computing, Cloud Computing, künstliche Intelligenz, Big Data mit Analysen, mobile Systeme, Kollaborationsnetzwerke und cyber-physikalische Systeme treibt neue Geschäftsmodelle an und ermöglicht sie. Die Digitalisierung führt zu einer tiefgreifenden Umwälzung bestehender Unternehmen, Technologien und Volkswirtschaften und fördert die Architektur digitaler Umgebungen mit vielen eher kleinen und verteilten Strukturen. Dies hat starke Auswirkungen auf neue Wertschöpfungsmöglichkeiten und die Gestaltung digitaler Dienste und Produkte, die durch die Nutzung einer service-dominanten Logik gesteuert werden. Das Hauptergebnis des Buchkapitels erweitert Methoden für integrale digitale Strategien um wertorientierte Modelle für digitale Produkte und Dienstleistungen, die im Rahmen eines multiperspektivischen digitalen Unternehmensarchitektur-Referenzmodells definiert werden.
IT environments that consist of a very large number of rather small structures like microservices, Internet of Things (IoT) components, or mobility systems are emerging to support flexible and agile products and services in the age of digital transformation. Biological metaphors of living and adaptable ecosystems with service-oriented enterprise architectures provide the foundation for self-optimizing, resilient run-time environments and distributed information systems. We are extending Enterprise Architecture (EA) methodologies and models that cover a high degree of heterogeneity and distribution to support the digital transformation and related information systems with micro-granular architectures. Our aim is to support flexibility and agile transformation for both IT and business capabilities within adaptable digital enterprise architectures. The present research paper investigates mechanisms for integrating Microservice Architectures (MSA) by extending original enterprise architecture reference models with elements for more flexible architectural metamodels and EA-mini-descriptions.
The fast moving process of digitization1 demands flexibility in order to adapt to rapidly changing business requirements and newly emerging business opportunities. New features have to be developed and deployed to the production environment a lot faster. To be able to cope with this increased velocity and pressure, a lot of software developing companies have switched to a Microservice Architecture (MSA) approach. Applications built this way consist of several fine-grained and heterogeneous services that are independently scalable and deployable. However, the technological and business architectural impacts of microservices based applications directly affect their integration into the digital enterprise architecture. As a consequence, traditional Enterprise Architecture Management (EAM) approaches are not able to handle the extreme distribution, diversity, and volatility of micro-granular systems and services. We are therefore researching mechanisms for dynamically integrating large amounts of microservices into an adaptable digital enterprise architecture.
Context
Microservices as a lightweight and decentralized architectural style with fine-grained services promise several beneficial characteristics for sustainable long-term software evolution. Success stories from early adopters like Netflix, Amazon, or Spotify have demonstrated that it is possible to achieve a high degree of flexibility and evolvability with these systems. However, the described advantageous characteristics offer no concrete guidance and little is known about evolvability assurance processes for microservices in industry as well as challenges in this area. Insights into the current state of practice are a very important prerequisite for relevant research in this field.
Objective
We therefore wanted to explore how practitioners structure the evolvability assurance processes for microservices, what tools, metrics, and patterns they use, and what challenges they perceive for the evolvability of their systems.
Method
We first conducted 17 semi-structured interviews and discussed 14 different microservice-based systems and their assurance processes with software professionals from 10 companies. Afterwards, we performed a systematic grey literature review (GLR) and used the created interview coding system to analyze 295 practitioner online resources.
Results
The combined analysis revealed the importance of finding a sensible balance between decentralization and standardization. Guidelines like architectural principles were seen as valuable to ensure a base consistency for evolvability and specialized test automation was a prevalent theme. Source code quality was the primary target for the usage of tools and metrics for our interview participants, while testing tools and productivity metrics were the focus of our GLR resources. In both studies, practitioners did not mention architectural or service-oriented tools and metrics, even though the most crucial challenges like Service Cutting or Microservices Integration were of an architectural nature.
Conclusions
Practitioners relied on guidelines, standardization, or patterns like Event-Driven Messaging to partially address some reported evolvability challenges. However, specialized techniques, tools, and metrics are needed to support industry with the continuous evaluation of service granularity and dependencies. Future microservices research in the areas of maintenance, evolution, and technical debt should take our findings and the reported industry sentiments into account.
Towards a practical maintainability quality model for service- and microservice-based systems
(2017)
Although current literature mentions a lot of different metrics related to the maintainability of service-based systems (SBSs), there is no comprehensive quality model (QM) with automatic evaluation and practical focus. To fill this gap, we propose a Maintainability Model for Services (MM4S), a layered maintainability QM consisting of service properties (SPs) related with automatically collectable Service Metrics (SMs). This research artifact created within an ongoing Design Science Research (DSR) project is the first version ready for detailed evaluation and critical feedback. The goal of MM4S is to serve as a simple and practical tool for basic maintainability estimation and control in the context of BSs and their specialization
microservice-based systems (μSBSs).
In a time of digital transformation, the ability to quickly and efficiently adapt software systems to changed business requirements becomes more important than ever. Measuring the maintainability of software is therefore crucial for the long-term management of such products. With service-based systems (SBSs) being a very important form of enterprise software, we present a holistic overview of such metrics specifically designed for this type of system, since traditional metrics – e.g. object oriented ones – are not fully applicable in this case. The selected metric candidates from the literature review were mapped to 4 dominant design properties: size, complexity, coupling, and cohesion. Microservice-based systems (μSBSs) emerge as an agile and fine grained variant of SBSs. While the majority of identified metrics are also applicable to this specialization (with some limitations), the large number of services in combination with technological heterogeneity and decentralization of control significantly impacts automatic metric collection in such a system. Our research therefore suggests that specialized tool support is required to guarantee the practical applicability of the presented metrics to μSBSs.
To bring a pattern-based perspective to the SOA vs. microservices discussion, we qualitatively analyzed a total of 118 SOA patterns from 2 popular catalogs for their (partial) applicability to microservices. Patterns had to hold up to 5 derived microservices principles to be applicable. 74 patterns (63%) were categorized as fully applicable, 30 (25%) as partially applicable, and 14 (12%) as not applicable. Most frequently violated microservices characteristics werde Decentralization and Single System. The findings suggest that microservices and SOA share a large set of architectural principles and solutions in the general space of service-based systems while only having a small set of differences in specific areas.
Maintainability assurance techniques are used to control this quality attribute and limit the accumulation of potentially unknown technical debt. Since the industry state of practice and especially the handling of service- and microservice-based systems in this regard are not well covered in scientific literature, we created a survey to gather evidence for a) used processes, tools, and metrics in the industry, b) maintainability-related treatment of systems based on service orientation, and c) influences on developer satisfaction w.r.t. maintainability. 60 software professionals responded to our online questionnaire. The results indicate that using explicit and systematic techniques has benefits for maintainability. The more sophisticated the applied methods the more satisfied participants were with the maintainability of their software while no link to a hindrance in productivity could be established. Other important findings were the absence of architecture-level evolvability control mechanisms as well as a significant neglect of service-oriented particularities for quality assurance. The results suggest that industry has to improve its quality control in these regards to avoid problems with long living service-based software systems.
While the recently emerged microservices architectural style is widely discussed in literature, it is difficult to find clear guidance on the process of refactoring legacy applications. The importance of the topic is underpinned by high costs and effort of a refactoring process which has several other implications, e.g. overall processes (DevOps) and team structure. Software architects facing this challenge are in need of selecting an appropriate strategy and refactoring technique. One of the most discussed aspects in this context is finding the right service granularity to fully leverage the advantages of a microservices architecture. This study first discusses the notion of architectural refactoring and subsequently compares 10 existing refactoring approaches recently proposed in academic literature. The approaches are classified by the underlying decomposition technique and visually presented in the form of a decision guide for quick reference. The review yielded a variety of strategies to break down a monolithic application into independent services. With one exception, most approaches are only applicable under certain conditions. Further concerns are the significant amount of input data some approaches require as well as limited or prototypical tool support.
While there are several theoretical comparisons of Object Orientation (OO) and Service Orientation (SO), little empirical research on the maintainability of the two paradigms exists. To provide support for a generalizable comparison, we conducted a study with four related parts. Two functionally equivalent systems (one OO and one SO version) were analyzed with coupling and cohesion metrics as well as via a controlled experiment, where participants had to extend the systems. We also conducted a survey with 32 software professionals and interviewed 8 industry experts on the topic. Results indicate that the SO version of our system possesses a higher degree of cohesion, a lower degree of coupling, and could be extended faster. Survey and interview results suggest that industry sees systems built with SO as more loosely coupled, modifiable, and reusable. OO systems, however, were described as less complex and easier to test.
While Microservices promise several beneficial characteristics for sustainable long-term software evolution, little empirical research covers what concrete activities industry applies for the evolvability assurance of Microservices and how technical debt is handled in such systems. Since insights into the current state of practice are very important for researchers, we performed a qualitative interview study to explore applied evolvability assurance processes, the usage of tools, metrics, and patterns, as well as participants’ reflections on the topic. In 17 semi-structured interviews, we discussed 14 different Microservice-based systems with software professionals from 10 companies and how the sustainable evolution of these systems was ensured. Interview transcripts were analyzed with a detailed coding system and the constant comparison method.
We found that especially systems for external customers relied on central governance for the assurance. Participants saw guidelines like architectural principles as important to ensure a base consistency for evolvability. Interviewees also valued manual activities like code review, even though automation and tool support was described as very important. Source code quality was the primary target for the usage of tools and metrics. Despite most reported issues being related to Architectural Technical Debt (ATD), our participants did not apply any architectural or service-oriented tools and metrics. While participants generally saw their Microservices as evolvable, service cutting and finding an appropriate service granularity with low coupling and high cohesion were reported as challenging. Future Microservices research in the areas of evolution and technical debt should take these findings and industry sentiments into account.
To remain competitive in a fast changing environment, many companies started to migrate their legacy applications towards a Microservices architecture. Such extensive migration processes require careful planning and consideration of implications and challenges likewise. In this regard, hands-on experiences from industry practice are still rare. To fill this gap in scientific literature, we contribute a qualitative study on intentions, strategies, and challenges in the context of migrations to Microservices. We investigated the migration process of 14 systems across different domains and sizes by conducting 16 in-depth interviews with software professionals from 10 companies. Along with a summary of the most important findings, we present a separate discussion of each case. As primary migration drivers, maintainability and scalability were identified. Due to the high complexity of their legacy systems, most companies preferred a rewrite using current technologies over splitting up existing code bases. This was often caused by the absence of a suitable decomposition approach. As such, finding the right service cut was a major technical challenge, next to building the necessary expertise with new technologies. Organizational challenges were especially related to large, traditional companies that simultaneously established agile processes. Initiating a mindset change and ensuring smooth collaboration between teams were crucial for them. Future research on the evolution of software systems can in particular profit from the individual cases presented.
Software evolvability is an important quality attribute, yet one difficult to grasp. A certain base level of it is allegedly provided by service- and microservice-based systems, but many software professionals lack systematic understanding of the reasons and preconditions for this. We address this issue via the proxy of architectural modifiability tactics. By qualitatively mapping principles and patterns of Service Oriented Architecture (SOA) and microservices onto tactics and analyzing the results, we cannot only generate insights into service-oriented evolution qualities, but can also provide a modifiability comparison of the two popular service-based architectural styles. The results suggest that both SOA and microservices possess several inherent qualities beneficial for software evolution. While both focus strongly on loose coupling and encapsulation, there are also differences in the way they strive for modifiability (e.g. governance vs. evolutionary design). To leverage the insights of this research, however, it is necessary to find practical ways to incorporate the results as guidance into the software development process.
Background: Design patterns are supposed to improve various quality attributes of software systems. However, there is controversial quantitative evidence of this impact. Especially for younger paradigms such as service- and microservice-based systems, there is a lack of empirical studies.
Objective: In this study, we focused on the effect of four service-based patterns - namely process abstraction, service façade, decomposed capability, and event-driven messaging - on the evolvability of a system from the viewpoint of inexperienced developers.
Method: We conducted a controlled experiment with Bachelor students (N = 69). Two functionally equivalent versions of a service-based web shop - one with patterns (treatment group), one without (control group) - had to be changed and extended in three tasks. We measured evolvability by the effectiveness and efficiency of the participants in these tasks. Additionally, we compared both system versions with nine structural maintainability metrics for size, granularity, complexity, cohesion, and coupling.
Results: Both experiment groups were able to complete a similar number of tasks within the allowed 90 min. Median effectiveness was 1/3. Mean efficiency was 12% higher in the treatment group, but this difference was not statistically significant. Only for the third task, we found statistical support for accepting the alternative hypothesis that the pattern version led to higher efficiency. In the metric analysis, the pattern version had worse measurements for size and granularity while simultaneously having slightly better values for coupling metrics. Complexity and cohesion were not impacted.
Interpretation: For the experiment, our analysis suggests that the difference in efficiency is stronger with more experienced participants and increased from task to task. With respect to the metrics, the patterns introduce additional volume in the system, but also seem to decrease coupling in some areas.
Conclusions: Overall, there was no clear evidence for a decisive positive effect of using service-based patterns, neither for the student experiment nor for the metric analysis. This effect might only be visible in an experiment setting with higher initial effort to understand the system or with more experienced developers.
While the concepts of object-oriented antipatterns and code smells are prevalent in scientific literature and have been popularized by tools like SonarQube, the research field for service-based antipatterns and bad smells is not as cohesive and organized. The description of these antipatterns is distributed across several publications with no holistic schema or taxonomy. Furthermore, there is currently little synergy between documented antipatterns for the architectural styles SOA and Microservices, even though several antipatterns may hold value for both. We therefore conducted a Systematic Literature Review (SLR) that identified 14 primary studies. 36 service-based antipatterns were extracted from these studies and documented with a holistic data model. We also categorized the antipatterns with a taxonomy and implemented relationships between them. Lastly, we developed a web application for convenient browsing and implemented a GitHub-based repository and workflow for the collaborative evolution of the collection. Researchers and practitioners can use the repository as a reference, for training and education, or for quality assurance.
Microservices are a topic driven mainly by practitioners and academia is only starting to investigate them. Hence, there is no clear picture of the usage of Microservices in practice. In this paper, we contribute a qualitative study with insights into industry adoption and implementation of Microservices. Contrary to existing quantitative studies, we conducted interviews to gain a more in-depth understanding of the current state of practice. During 17 interviews with software professionals from 10 companies, we analyzed 14 service-based systems. The interviews focused on applied technologies, Microservices characteristics, and the perceived influence on software quality. We found that companies generally rely on well established technologies for service implementation, communication, and deployment. Most systems, however, did not exhibit a high degree of technological diversity as commonly expected with Microservices. Decentralization and product character were different for systems built for external customers. Applied DevOps practices and automation were still on a mediocre level and only very few companies strictly followed the you build it, you run it principle. The impact of Microservices on software quality was mainly rated as positive. While maintainability received the most positive mentions, some major issues were associated with security. We present a description of each case and summarize the most important findings of companies across different domains and sizes. Researchers may build upon our findings and take them into account when designing industry-focused methods.
While several service-based maintainability metrics have been proposed in the scientific literature, reliable approaches to automatically collect these metrics are lacking. Since static analysis is complicated for decentralized and technologically diverse microservice-based systems, we propose a dynamic approach to calculate such metrics from runtime data via distributed tracing. The approach focuses on simplicity, extensibility, and broad applicability. As a first prototype, we implemented a Java application with a Zipkin integrator, 23 different metrics, and five export formats. We demonstrated the feasibility of the approach by analyzing the runtime data of an example microservice based system. During an exploratory study with six participants, 14 of the 18 services were invoked via the system’s web interface. For these services, all metrics were calculated correctly from the generated traces.
While many maintainability metrics have been explicitly designed for service-based systems, tool-supported approaches to automatically collect these metrics are lacking. Especially in the context of microservices, decentralization and technological heterogeneity may pose challenges for static analysis. We therefore propose the modular and extensible RAMA approach (RESTful API Metric Analyzer) to calculate such metrics from machine-readable interface descriptions of RESTful services. We also provide prototypical tool support, the RAMA CLI, which currently parses the formats OpenAPI, RAML, and WADL and calculates 10 structural service-based metrics proposed in scientific literature. To make RAMA measurement results more actionable, we additionally designed a repeatable benchmark for quartile-based threshold ranges (green, yellow, orange, red). In an exemplary run, we derived thresholds for all RAMA CLI metrics from the interface descriptions of 1,737 publicly available RESTful APIs. Researchers and practitioners can use RAMA to evaluate the maintainability of RESTful services or to support the empirical evaluation of new service interface metrics.
Scenario-based analysis is a comprehensive technique to evaluate software quality and can provide more detailed insights than e.g. maintainability metrics. Since such methods typically require significant manual effort, we designed a lightweight scenario-based evolvability evaluation method. To increase efficiency and to limit assumptions, the method exclusively targets service- and microservice-based systems. Additionally, we implemented web-based tool support for each step. Method and tool were also evaluated with a survey (N=40) that focused on change effort estimation techniques and hands-on interviews (N=7) that focused on usability. Based on the evaluation results, we improved method and tool support further. To increase reuse and transparency, the web-based application as well as all survey and interview artifacts are publicly available on GitHub. In its current state, the tool-supported method is ready for first industry case studies.
The euphoria around microservices has decreased over the years, but the trend of modernizing legacy systems to this novel architectural style is unbroken to date. A variety of approaches have been proposed in academia and industry, aiming to structure and automate the often long-lasting and cost-intensive migration journey. However, our research shows that there is still a need for more systematic guidance. While grey literature is dominant for knowledge exchange among practitioners, academia has contributed a significant body of knowledge as well, catching up on its initial neglect. A vast number of studies on the topic yielded novel techniques, often backed by industry evaluations. However, practitioners hardly leverage these resources. In this paper, we report on our efforts to design an architecture-centric methodology for migrating to microservices. As its main contribution, a framework provides guidance for architects during the three phases of a migration. We refer to methods, techniques, and approaches based on a variety of scientific studies that have not been made available in a similarly comprehensible manner before. Through an accompanying tool to be developed, architects will be in a position to systematically plan their migration, make better informed decisions, and use the most appropriate techniques and tools to transition their systems to microservices.
Enterprise Architectures (EA) consists of many architecture elements, which stand in manifold relationships to each other. Therefore Architecture Analysis is important and very difficult for stakeholders. Due changing an architecture element has impacts on other elements different stakeholders are involved. In practice EAs are often analyzed using visualizations. This article aims at contributing to the field of visual analytics in EAM by analyzing how state of-the-art software platforms in EAM support stakeholders with respect to providing and visualizing the “right” information for decision-making tasks. We investigate the collaborative decision-making process in an experiment with master students using professional EAM tools by developing a research study and accomplishing them in a master’s level class with students.
New or adapted digital business models have huge impacts on Enterprise Architectures (EA) and require them to become more agile, flexible, and adaptable. All these changes are happening frequently and are currently not well documented. An EA consists of a lot of elements with manifold relationships between them. Thus changing the business model may have multiple impacts on other architectural elements. The EA engineering process deals with the development, change and optimization of architectural elements and their dependencies. Thus an EA provides a holistic view for both business and IT from the perspective of many stakeholders, which are involved in EA decision-making processes. Different stakeholders have specific concerns and are collaborating today in often unclear decision-making processes. In our research we are investigating information from collaborative decision-making processes to support stakeholders in taking current decisions. In addition we provide all information necessary to understand how and why decisions were taken. We are collecting the decision-related information automatically to minimize manual time intensive work as much as possible. The core contribution of our research extends a decisional metamodel, which links basic decisions with architectural elements and extends them with an associated decisional case context. Our aim is to support a new integral method for multi perspective and collaborative decision-making processes. We illustrate this by a practice-relevant decision-making scenario for Enterprise Architecture Engineering.
In modern times markets are very dynamic. This situation requires agile enterprises to have the ability to react fast on market influences. Thereby an enterprise’ IT is especially affected, because new or changed business models have to be realized. However, enterprise architectures (EA) are complex structures consisting of many artifacts and relationships between them. Thus analyzing an EA becomes to a complex task for stakeholders. In addition, many stakeholders are involved in decision-making processes, because Enterprise Architecture Management (EAM) targets providing a holistic view of the enterprise. In this article we use concepts of Adaptive Case Management (ACM) to design a decision-making case consisting of a combination of different analysis techniques to support stakeholders in decision-making. We exemplify the case with a scenario of a fictive enterprise.
The Internet of Things (IoT) fundamentally influences today’s digital strategies with disruptive business operating models and fast changing markets. New business information systems are integrating emerging Internet of Things infrastructures and components. With the huge diversity of Internet of Things technologies and products organizations have to leverage and extend previous enterprise architecture efforts to enable business value by integrating the Internet of Things into their evolving Enterprise Architecture Management environments. Both architecture engineering and management of current enterprise architectures is complex and has to integrate beside the Internet of Things synergistic disciplines like EAM - Enterprise Architecture and Management with disciplines like: services & cloud computing, semantic-based decision support through ontologies and knowledge-based systems, big data management, as well as mobility and collaboration networks. To provide adequate decision support for complex business/IT environments, it is necessary to identify affected changes of Internet of Things environments and their related fast adapting architecture. We have to make transparent the impact of these changes over the integral landscape of affected EAM-capabilities, like directly and transitively impacted IoT-objects, business categories, processes, applications, services, platforms and infrastructures. The paper describes a new metamodel-based approach for integrating partial Internet of Things objects, which are semi-automatically federated into a holistic Enterprise Architecture Management environment.
Enterprise architecture management (EAM) is a holistic approach to tackle the complex Business and IT architecture. The transformation of an organization’s EA towards a strategy-oriented system is a continuous task. Many stakeholders have to elaborate on various parts of the EA to reach the best decisions to shape the EA towards an optimized support of the organizations’ capabilities. Since the real world is too complex, analyzing techniques are needed to detect optimization potentials and to get all information needed about an issue. In practice visualizations are commonly used to analyze EAs. However these visualizations are mostly static and do not provide analyses. In this article we combine analyzing techniques from literature and interactive visualizations to support stakeholders in EA decision-making.
The digital transformation of our society changes the way we live, work, learn, communicate, and collaborate. This disruptive change interacts with all information processes and systems that are important business enablers for the digital transformation since years. The Internet of Things, social collaboration systems for adaptive case management, mobility systems and services for Big Data in cloud services environments are emerging to support intelligent user-centered and social community systems. They will shape future trends of business innovation and the next wave of information and communication technology. Biological metaphors of living and adaptable ecosystems provide the logical foundation for self-optimizing and resilient run-time environments for intelligent business services and related distributed information systems with service-oriented enterprise architectures. The present research investigates mechanisms for flexible adaptation and evolution of digital enterprise architectures in the context of integrated synergistic disciplines like distributed service-oriented architectures and information systems, EAM - Enterprise Architecture and Management, metamodeling, semantic echnologies, web services, cloud computing and Big Data technology. Our aim is to support flexibility and agile transformations for both business domains and related enterprise systems through adaptation and evolution of digital enterprise architectures. The present research paper investigates digital transformations of business and IT and integrates fundamental mappings between adaptable digital enterprise architectures and service-oriented information systems.
Modern enterprises reshape and transform continuously by a multitude of management processes with different perspectives. They range from business process management to IT service management and the management of the information systems. Enterprise Architecture (EA) management seeks to provide such a perspective and to align the diverse management perspectives. Therefore, EA management cannot rely on hierarchic - in a tayloristic manner designed - management processes to achieve and promote this alignment. It, conversely, has to apply bottom-up, information-centered coordination mechanisms to ensure that different management processes are aligned with each other and enterprise strategy. Social software provides such a bottom-up mechanism for providing support within EAM-processes. Consequently, challenges of EA management processes are investigated, and contributions of social software presented. A cockpit provides interactive functions and visualization methods to cope with this complexity and enable the practical use of social software in enterprise architecture management processes.
The digitization of our society changes the way we live, work, learn, communicate, and collaborate. This disruptive change interacts with all information processes and systems that are important business enablers for the context of digitization since years. Our aim is to support flexibility and agile transformations for both business domains and related information technology and enterprise systems through adaptation and evolution of digital enterprise architectures. The present research paper investigates collaborative decision mechanisms for adaptive digital enterprise architectures by extending original architecture reference models with state of art elements for agile architectural engineering for the digitization and collaborative architectural decision support.
Enterprise Architectures (EA) consist of a multitude of architecture elements, which relate in manifold ways to each other. As the change of a single element hence impacts various other elements, mechanisms for architecture analysis are important to stakeholders. The high number of relationships aggravates architecture analysis and makes it a complex yet important task. In practice EAs are often analyzed using visualizations. This article contributes to the field of visual analytics in enterprise architecture management (EAM) by reviewing how state-of-the-art software platforms in EAM support stakeholders with respect to providing and visualizing the “right” information for decision-making tasks. We investigate the collaborative decision-making process in an experiment with master students using professional EAM tools by developing a research study. We evaluate the students’ findings by comparing them with the experience of an enterprise architect.
Current approaches for enterprise architecture lack analytical instruments for cyclic evaluations of business and system architectures in real business enterprise system environments. This impedes the broad use of enterprise architecture methodologies. Furthermore, the permanent evolution of systems desynchronizes quickly model representation and reality. Therefore we are introducing an approach for complementing the existing top-down approach for the creation of enterprise architecture with a bottom approach. Enterprise Architecture Analytics uses the architectural information contained in many infrastructures to provide architectural information. By applying Big Data technologies it is possible to exploit this information and to create architectural information. That means, Enterprise Architectures may be discovered, analyzed and optimized using analytics. The increased availability of architectural data also improves the possibilities to verify the compliance of Enterprise Architectures. Architectural decisions are linked to clustered architecture artifacts and categories according to a holistic EAM Reference Architecture with specific architecture metamodels. A special suited EAM Maturity Framework provides the base for systematic and analytics supported assessments of architecture capabilities.
Big Data und Cloud Systeme werden zunehmend von mobilen, benutzerzentrierten und agil veränderbaren Informationssystemen im Kontext von digitalen sozialen Netzwerken genutzt. Metaphern aus der Biologie für lebendige und selbstheilende Systeme und Umgebungen liefern die Basis für intelligente adaptive Informationssysteme und für zugehörige serviceorientierte digitale Unternehmensarchitekturen. Wir berichten über unsere Forschungsarbeiten über Strukturen und Mechanismen adaptiver digitaler Unternehmensarchitekturen für die Entwicklung und Evolution von serviceorientierten Ökosystemen und deren Technologien wie Big Data, Services & Cloud Computing, Web Services und Semantikunterstützung. Für unsere aktuellen Forschungsarbeiten nutzen wir praxisrelevante SmartLife Szenarien für die Entwicklung, Wartung und Evolution zukunftsgerechter serviceorientierter Informationssysteme. Diese Systeme nutzen eine stark wachsende Zahl externer und interner Services und fokussieren auf die Besonderheiten der Weiterentwicklung der Informationssysteme für integrierte Big Data und Cloud Kontexte. Unser Forschungsansatz beschäftigt sich mit der systematischen und ganzheitlichen Modellbildung adaptiver digitaler Unternehmensarchitekturen - gemäß standardisierter Referenzmodelle und auf Standards aufsetzenden Referenzarchitekturen, die für besondere Einsatzszenarien auch bei kleineren Anwendungskontexten oder an neue Kontexte einfacher adaptiert werden können. Um Semantik-gestützte Analysen zur Entscheidungsunterstützung von System- und Unternehmensarchitekten zu ermöglichen, erweitern wir unser bisheriges Referenzmodell für ITUnternehmensarchitekturen ESARC – Enterprise Services Architecture Reference Cube – um agile Mechanismen der Adaption und Konsistenzbehandlung sowie die zugehörigen Metamodelle und Ontologien für Digitale Enterprise Architekturen um neue Aspekte wie Big Data und Cloud Kontexte.
A configuration-management-database driven approach for fabric-process specification and automation
(2014)
In this paper we describe an approach that integrates a Configuration- Management-Database into fabric-process specification and automation in order to consider different conditions regarding to cloud-services. By implementing our approach, the complexity of fabric processes gets reduced. We developed a prototype by using formal prototyping principles as research methods and integrated the Configuration-Management-Database Command into the Workflow- Management-System Activiti. We used this prototype to evaluate our approach. We implemented three different fabric-processes and show that by using our approach the complexity of these three fabric-processes gets reduced.
The digital transformation of our society changes the way we live, work, learn, communicate, and collaborate. The digitization of software-intensive products and services is enabled basically by four megatrends: Cloud computing, big data mobile systems, and social technologies. This disruptive change interacts with all information processes and systems that are important business enablers for the current digital transformation. The internet of things, social collaboration systems for adaptive case management, mobility systems and services for big data in cloud services environments are emerging to support intelligent user-centered and social community systems. Modern enterprises see themselves confronted with an ever growing design space to engineer business models of the future as well as their IT support, respectively. The decision analytics in this field becomes increasingly complex and decision support, particularly for the development and evolution of sustainable enterprise architectures (EA), is duly needed. With the advent of intelligent user-centered and social community systems, the challenging decision processes can be supported in more flexible and intuitive ways. Tapping into these systems and techniques, the engineers and managers of the enterprise architecture become part of a viable enterprise, i.e. a resilient and continuously evolving system that develops innovative business models.
The Internet of Things, enterprise social networks, adaptive case management, mobility systems, analytics for big data, and cloud services environments are emerging to support smart connected products and services and the digital transformation. Biological metaphors of living and adaptable ecosystems provide the logical foundation for self-optimizing and resilient run-time environments for intelligent business services and related distributed information systems with service-oriented enterprise architectures. We are investigating mechanisms for flexible adaptation and evolution for the next digital enterprise architecture systems in the context of the digital transformation. Our aim is to support flexibility and agile transformation for both business and related enterprise systems through adaptation and dynamical evolution of digital enterprise architectures. The present research paper investigates digital transformations of business and IT and integrates fundamental mappings between adaptable digital enterprise architectures and service-oriented information systems. We are putting a spotlight with the example domain – Internet of Things.
Excellence in IT is both a driver and a key enabler of the digital transformation. The digital transformation changes the way we live, work, learn, communicate, and collaborate. The Internet of Things (IoT) fundamentally influences today’s digital strategies with disruptive business operating models and fast changing markets. New business information systems are integrating emerging Internet of Things infrastructures and components. With the huge diversity of Internet of Things technologies and products organizations have to leverage and extend previous Enterprise Architecture efforts to enable business value by integrating Internet of Things architectures. Both architecture engineering and management of current information systems and business models are complex and currently integrating beside the Internet of Things synergistic subjects, like Enterprise Architecture in context with services & cloud computing, semantic-based decision support through ontologies and knowledge-based systems, big data management, as well as mobility and collaboration networks. To provide adequate decision support for complex business/IT environments, we have to make transparent the impact of business and IT changes over the integral landscape of affected architectural capabilities, like directly and transitively impacted IoT-objects, business categories, processes, applications, services, platforms and infrastructures. The paper describes a new metamodel-based approach for integrating Internet of Things architectural objects, which are semi-automatically federated into a holistic Digital Enterprise Architecture environment.
Many organizations identified the opportunities of big data analytics to support the business with problem-specific insights through the exploitation of generated data. Socio-technical solutions are developed in big data projects to reach competitive advantage. Although these projects are aligned to specific business needs, common architectural challenges are not addressed in a comprehensive manner. Enterprise architecture management is a holistic approach to tackle the complex business and IT architecture. The transformation of an organization's EA is influenced by big data projects and their data-driven approach on all layers. To enable strategy oriented development of the EA it is essential to synchronize these projects supported by EA management. In
this paper, we conduct a systematic review of big data literature to analyze which requirements for the EA management discipline are proposed. Thereby, a broad overview about existing research is presented to facilitate a more detailed exploration and to foster the evolution o the EA management discipline.
Organizations identified the opportunities of big data analytics to support the business with problem-specific insights through the exploitation of generated data. Sociotechnical solutions are developed in big data projects to reach competitive advantage. Although these projects are aligned to specific business needs, common architectural challenges are not addressed in a comprehensive manner. Enterprise architecture management is a holistic approach to tackle complex business and IT architectures. The transformation of an organization’s EA is influenced by big data transformation processes and their data-driven approach on all layers. In this paper, we review big data literature to analyze which requirements for the EA management discipline are proposed. Based on a systematic literature identification, conceptual categories of requirements for EA management are elicited utilizing an inductive category formation. These conceptual categories of requirements constitute a category system that facilitates a new perspective on EA management and fosters the innovation-driven evolution of the EA management.
discipline.
Analysis is an important part of the enterprise architecture management process. Prior to decisions regarding transformation of the enterprise architecture, the current situation and the outcomes of alternative action plans have to be analysed. Many analysis approaches have been proposed by researchers and current enterprise architecture management tools implement analysis functionalities. However, few work has been done structuring and classifying enterprise architecture analysis approaches. This paper collects and extends existing classification schemes, presenting a framework for enterprise architecture analysis classification. For evaluation, a collection of enterprise architecture analysis approaches has been classified based on this framework. As a result, the description of these approaches has been assessed, a common set of important categories for enterprise architecture analysis classification has been derived and suggestions for further development are drawn.
In times of dynamic markets, enterprises have to be agile to be able to quickly react to market influences. Due to the increasing digitization of products, the enterprise IT often is affected when business models change. Enterprise Architecture Management (EAM) targets a holistic view of the enterprise’ IT and their relations to the business. However, Enterprise Architectures (EA) are complex structures consisting of many layers, artifacts and relationships between them. Thus, analyzing EA is a very complex task for stakeholders. Visualizations are common vehicles to support analysis. However, in practice visualization capabilities lack flexibility and interactivity. A solution to improve the support of stakeholders in analyzing EAs might be the application of visual analytics. Starting from a systematic literature review, this article investigates the features of visual analytics relevant for the context of EAM.
The digitization of our society changes the way we live, work, learn, communicate, and collaborate. The Internet of Things, enterprise social networks, adaptive case management, mobility systems, analytics for big data, and cloud services environments are emerging to support smart connected products and services and the digital transformation. Biological metaphors of living and adaptable ecosystems provide the logical foundation for self-optimizing and resilient run-time environments for intelligent business services and service-oriented enterprise architectures. Our aim is to support flexibility and agile transformations for both business domains and related information technology. The present research paper investigates mechanisms for decision analytics in the context of multi-perspective explorations of enterprise services and their digital enterprise architectures by extending original architecture reference models with state of art elements for agile architectural engineering for the digitization and collaborative architectural decision support. The paper’s context focuses on digital transformations of business and IT and integrates fundamental mappings between adaptable digital enterprise architectures and service-oriented information systems. We are putting a spotlight on the example domain – Internet of Things.
Enterprise Governance, Risk and Compliance (GRC) systems are key to managing risks threatening modern enterprises from many different angles. Key constituent to GRC systems is the definition of controls that are implemented on the different layers of an Enterprise Architecture (EA). As part of the compliance aspect of GRC, the effectiveness of these controls is assessed and reported to relevant management bodies within the enterprise. In this paper we present a metamodel which links controls to the affected elements of an EA and supplies a way of expressing associated assessment techniques and results. We complement the metamodel with an expository instantiation in a cockpit for control compliance applied in an international enterprise in the insurance industry.
Enterprise Governance, Risk and Compliance (GRC) systems are key to managing risks threatening modern enterprises from many different angles. Key constituent to GRC systems is the definition of controls that are implemented on the different layers of an Enterprise Architecture (EA). Controls become part of a “concern” of the EA, which allows to use an EA viewpoint to cover control compliance assessments. In this article we explore this relationship further, derive a metamodel linking control and EA, and elicit how this linkage give rise to a hierarchic understanding of the viewpoint concept for EAs. We complement these considerations with an expository instantiation in a cockpit for control compliance applied in an international enterprise in the insurance industry.
New business opportunities appeared using the potential of the Internet and related digital technologies, like the Internet of Things, services computing, artificial intelligence, cloud, edge, and fog computing, social networks, big data with analytics, mobile systems, collaboration networks, and cyber-physical systems. Companies are transforming their strategy and product base, as well as their culture, processes and information systems to adopt digital transformation or to approach for digital leadership. Digitalization fosters the development of IT environments with many rather small and distributed structures, like the Internet of Things, Microservices, or other micro-granular elements. Digitalization has a substantial impact for architecting the open and complex world of highly distributed digital servcies and products, as part of a new digital enterprise architecture, which structure and direct service-dominant digital products and services. The present research paper investigates mechanisms for supporting the evolution of digital enterprise architectures with user-friendly methods and instruments of interaction, visualization, and intelligent decision management during the exploration of multiple and interconnected perspectives by an architecture management cockpit.
Companies are continuously changing their strategy, processes, and information systems to benefit from the digital transformation. Controlling the digital architecture and governance is the fundamental goal. Enterprise Governance, Risk and Compliance (GRC) systems are vital for managing digital risks threatening in modern enterprises from many different angles. The most significant constituent to GRC systems is the definition of controls that is implemented on different layers of a digital Enterprise Architecture (EA). As part of the compliant aspect of GRC, the effectiveness of these controls is assessed and reported to relevant management bodies within the enterprise. In this paper, we present a metamodel which links controls to the affected elements of a digital EA and supplies a way of expressing associated assessment techniques and results. We complement a metamodel with an expository instantiation of a control compliance cockpit in an international insurance enterprise.
Intelligent systems and services are the strategic targets of many current digitalization efforts and part of massive digital transformations based on digital technologies with artificial intelligence. Digital platform architectures and ecosystems provide an essential base for intelligent digital systems. The paper raises an important question: Which development paths are induced by current innovations in the field of artificial intelligence and digitalization for enterprise architectures? Digitalization disrupts existing enterprises, technologies, and economies and promotes the architecture of cognitive and open intelligent environments. This has a strong impact on new opportunities for value creation and the development of intelligent digital systems and services. Digital technologies such as artificial intelligence, the Internet of Things, service computing, cloud computing, blockchains, big data with analysis, mobile systems, and social business network systems are essential drivers of digitalization. We investigate the development of intelligent digital systems supported by a suitable digital enterprise architecture. We present methodological advances and an evolutionary path for architectures with an integral service and value perspective to enable intelligent systems and services that effectively combine digital strategies and digital architectures with artificial intelligence.
Digital technologies are main strategic drivers for digitalization and offer ubiquitous data availability, unlimited connectivity, and massive processing power for a fundamentally changing business. This leads to the development and application of intelligent digital systems. The current state of research and practice of architecting digital systems and services lacks a solid methodological foundation that fully accommodates all requirements linked to efficient and effective development of digital systems in organizations. Research presented in this paper addresses the question, how management of complexity in digital systems and architectures can be supported from a methodological perspective. In this context, the current focus is on a better understanding of the causes of increased complexity and requirements to methodological support. For this purpose, we take an enterprise architecture perspective, i.e. how the introduction of digital systems affects the complexity of EA. Two industrial case studies and a systematic literature analysis result in the proposal of an extended Digital Enterprise Architecture Cube as framework for future methodical support.
Platforms and their surrounding ecosystems are becoming increasingly important components of many companies' strategies. Artificial Intelligence, in particular, has created new opportunities to create and develop ecosystems around the platform. However, there is not yet a methodology to systematically develop these new opportunities for enterprise development strategy. Therefore, this paper aims to lay a foundation for the conceptualization of Artificial Intelligence-based service ecosystems exploiting a Service-Dominant Logic. The basis for conceptualization is the study of value creation and particularly effective network effects. This research investigates the fundamental idea of extending specific digital concepts considering the influence of Artificial Intelligence on the design of intelligent services, along with their architecture of digital platforms and ecosystems, to enable a smooth evolutionary path and adaptability for human-centric collaborative systems and services. The paper explores an extended digital enterprise conceptual model through a combined, iterative, and permanent task of co-creating value between humans and intelligent systems as part of a new idea of cognitively adapted intelligent services.
Real Time Charging (RTC) applications that reside in the telecommunications domain have the need for extremely fast database transactions. Today´s providers rely mostly on in-memory databases for this kind of information processing. A flexible and modular benchmark suite specifically designed for this domain provides a valuable framework to test the performance of different DB candidates. Besides a data and a load generator, the suite also includes decoupled database connectors and use case components for convenient customization and extension. Such easily produced test results can be used as guidance for choosing a subset of candidates for further tuning/testing and finally evaluating the database most suited to the chosen use cases. This is why our benchmark suite can be of value for choosing databases for RTC use cases.
Several studies analyzed existing Web APIs against the constraints of REST to estimate the degree of REST compliance among state-of-the-art APIs. These studies revealed that only a small number of Web APIs are truly RESTful. Moreover, identified mismatches between theoretical REST concepts and practical implementations lead us to believe that practitioners perceive many rules and best practices aligned with these REST concepts differently in terms of their importance and impact on software quality. We therefore conducted a Delphi study in which we confronted eight Web API experts from industry with a catalog of 82 REST API design rules. For each rule, we let them rate its importance and software quality impact. As consensus, our experts rated 28 rules with high, 17 with medium, and 37 with low importance. Moreover, they perceived usability, maintainability, and compatibility as the most impacted quality attributes. The detailed analysis revealed that the experts saw rules for reaching Richardson maturity level 2 as critical, while reaching level 3 was less important. As the acquired consensus data may serve as valuable input for designing a tool-supported approach for the automatic quality evaluation of RESTful APIs, we briefly discuss requirements for such an approach and comment on the applicability of the most important rules.
Continuous refactoring is necessary to maintain source code quality and to cope with technical debt. Since manual refactoring is inefficient and error prone, various solutions for automated refactoring have been proposed in the past. However, empirical studies have shown that these solutions are not widely accepted by software developers and most refactorings are still performed manually. For example, developers reported that refactoring tools should support functionality for reviewing changes. They also criticized that introducing such tools would require substantial effort for configuration and integration into the current development environment.
In this paper, we present our work towards the Refactoring-Bot, an autonomous bot that integrates into the team like a human developer via the existing version control platform. The bot automatically performs refactorings to resolve code smells and presents the changes to a developer for asynchronous review via pull requests. This way, developers are not interrupted in their workflow and can review the changes at any time with familiar tools. Proposed refactorings can then be integrated into the code base via the push of a button. We elaborate on our vision, discuss design decisions, describe the current state of development, and give an outlook on planned development and research activities.
Context: Fast moving markets and the age of digitization require that software can be quickly changed or extended with new features. The associated quality attribute is referred to as evolvability: the degree of effectiveness and efficiency with which a system can be adapted or extended. Evolvability is especially important for software with frequently changing requirements, e.g. internet-based systems. Several evolvability-related benefits were arguably gained with the rise of service-oriented computing (SOC) that established itself as one of the most important paradigms for distributed systems over the last decade. The implementation of enterprise-wide software landscapes in the style of service-oriented architecture (SOA) prioritizes loose coupling, encapsulation, interoperability, composition, and reuse. In recent years, microservices quickly gained in popularity as an agile, DevOps-focused, and decentralized service-oriented variant with fine-grained services. A key idea here is that small and loosely coupled services that are independently deployable should be easy to change and to replace. Moreover, one of the postulated microservices characteristics is evolutionary design.
Problem Statement: While these properties provide a favorable theoretical basis for evolvable systems, they offer no concrete and universally applicable solutions. As with each architectural style, the implementation of a concrete microservice-based system can be of arbitrary quality. Several studies also report that software professionals trust in the foundational maintainability of service orientation and microservices in particular. A blind belief in these qualities without appropriate evolvability assurance can lead to violations of important principles and therefore negatively impact software evolution. In addition to this, very little scientific research has covered the areas of maintenance, evolution, or technical debt of microservices.
Objectives: To address this, the aim of this research is to support developers of microservices with appropriate methods, techniques, and tools to evaluate or improve evolvability and to facilitate sustainable long-term development. In particular, we want to provide recommendations and tool support for metric-based as well as scenario-based evaluation. In the context of service-based evolvability, we furthermore want to analyze the effectiveness of patterns and collect relevant antipatterns. Methods: Using empirical methods, we analyzed the industry state of the practice and the academic state of the art, which helped us to identify existing techniques, challenges, and research gaps. Based on these findings, we then designed new evolvability assurance techniques and used additional empirical studies to demonstrate and evaluate their effectiveness. Applied empirical methods were for example surveys, interviews, (systematic) literature studies, or controlled experiments.
Contributions: In addition to our analyses of industry practice and scientific literature, we provide contributions in three different areas. With respect to metric-based evolvability evaluation, we identified a set of structural metrics specifically designed for service orientation and analyzed their value for microservices. Subsequently, we designed tool-supported approaches to automatically gather a subset of these metrics from machine-readable RESTful API descriptions and via a distributed tracing mechanism at runtime. In the area of scenario-based evaluation, we developed a tool-supported lightweight method to analyze the evolvability of a service-based system based on hypothetical evolution scenarios. We evaluated the method with a survey (N=40) as well as hands-on interviews (N=7) and improved it further based on the findings. Lastly with respect to patterns and antipatterns, we collected a large set of service-based patterns and analyzed their applicability for microservices. From this initial catalogue, we synthesized a set of candidate evolvability patterns via the proxy of architectural modifiability tactics. The impact of four of these patterns on evolvability was then empirically tested in a controlled experiment (N=69) and with a metric-based analysis. The results suggest that the additional structural complexity introduced by the patterns as well as developers' pattern knowledge have an influence on their effectiveness. As a last contribution, we created a holistic collection of service-based antipatterns for both SOA and microservices and published it in a collaborative repository.
Conclusion: Our contributions provide first foundations for a holistic view on the evolvability assurance of microservices and address several perspectives. Metric- and scenario-based evaluation as well as service-based antipatterns can be used to identify "hot spots" while service-based patterns can remediate them and provide means for systematic evolvability construction. All in all, researchers and practitioners in the field of microservices can use our artifacts to analyze and improve the evolvability of their systems as well as to gain a conceptual understanding of service-based evolvability assurance.
Successful transitions to a sustainable bioeconomy require novel technologies, processes, and practices as well as a general agreement about the overarching normative direction of innovation. Both requirements necessarily involve collective action by those individuals who purchase, use, and co-produce novelties: the consumers. Based on theoretical considerations borrowed from evolutionary innovation economics and consumer social responsibility, we explore to what extent consumers’ scope of action is addressed in the scientific bioeconomy literature. We do so by systematically reviewing bioeconomy-related publications according to (i) the extent to which consumers are regarded as passive vs. active, and (ii) different domains of consumer responsibility (depending on their power to influence economic processes). We find all aspects of active consumption considered to varying degrees but observe little interconnection between domains. In sum, our paper contributes to the bioeconomy literature by developing a novel coding scheme that allows us to pinpoint different aspects of consumer activity, which have been considered in a rather isolated and undifferentiated manner. Combined with our theoretical considerations, the results of our review reveal a central research gap which should be taken up in future empirical and conceptual bioeconomy research. The system-spanning nature of a sustainable bioeconomy demands an equally holistic exploration of the consumers’ prospective and shared responsibility for contributing to its coming of age, ranging from the procurement of information on bio-based products and services to their disposal.
Context
Web APIs are one of the most used ways to expose application functionality on the Web, and their understandability is important for efficiently using the provided resources. While many API design rules exist, empirical evidence for the effectiveness of most rules is lacking.
Objective
We therefore wanted to study 1) the impact of RESTful API design rules on understandability, 2) if rule violations are also perceived as more difficult to understand, and 3) if demographic attributes like REST-related experience have an influence on this.
Method
We conducted a controlled Web-based experiment with 105 participants, from both industry and academia and with different levels of experience. Based on a hybrid between a crossover and a between-subjects design, we studied 12 design rules using API snippets in two complementary versions: one that adhered to a rule and one that was a violation of this rule. Participants answered comprehension questions and rated the perceived difficulty.
Results
For 11 of the 12 rules, we found that violation performed significantly worse than rule for the comprehension tasks. Regarding the subjective ratings, we found significant differences for 9 of the 12 rules, meaning that most violations were subjectively rated as more difficult to understand. Demographics played no role in the comprehension performance for violation.
Conclusions
Our results provide first empirical evidence for the importance of following design rules to improve the understandability of Web APIs, which is important for researchers, practitioners, and educators.
Analysis and planning of Enterprise Architectures (EA) is a complex task for stakeholders. The change of one architecture element has impact on multiple other elements because of manifold relationships and interactions between them. The interactive cockpit approach presented in this paper supports stakeholders planning and analyzing EAs and to tackle the intrinsic complexity. This approach supplies a cockpit with multiple viewpoints to put relevant information side-by-side without losing the context combined with interaction functionality. In this paper, we develop such cockpit starting with relevant use cases, describing a potential design based on well-established foundations in EA modeling, and outline an exemplary usage scenario.
EAM ist ein holistischer Ansatz, um komplexe IT- und Unternehmensstrukturen darzustellen. Dabei ist es von zentraler Bedeutung, diese Strukturen möglichst komplett und übersichtlich zu visualisieren. Ein Ansatz, dies zu erreichen, ist eine multiperspektivische Darstellung von mehreren Views in einem Architekturcockpit. Dabei können mehrere Views simultan betrachtet und analysiert werden. Dadurch ist es möglich, die Auswirkungen einer Analyse des Views eines Stakeholders simultan aus den Views anderer Stakeholder betrachten zu können, um eventuelle Wechselwirkungen zu erkennen und einen allgemeinen Überblick über die Unternehmensarchitektur zu behalten. In dieser Arbeit zeigen wir, von der Konzeption über die Umsetzung bis zu einem Anwendungsbeispiel, wie ein solches Architekturcockpit realisiert werden kann.
Due to digitalization, constant technological progress and ever shorter product life cycles, enterprises are currently facing major challenges. In order to succeed in the market, business models have to be adapted more often and more quickly to changing market conditions than they used to be. Fast adaptability, also called agility, is a decisive competitive factor in today’s world. Because of the ever-growing IT part of products and the fact that they are manufactured using IT, changing the business model has a major impact on the enterprise architecture (EA). However, developing EAs is a very complex task, because many stakeholders with conflicting interests are involved in the decision-making process. Therefore, a lot of collaboration is required. To support organizations in developing their EA, this article introduces a novel integrative method that systematically integrates stakeholder interests into decision-making activities. By using the method, collaboration between stakeholders involved is improved by identifying points of contact between them. Furthermore, standardized activities make decision-making more transparent and comparable without limiting creativity.
Unternehmen stehen aktuell aufgrund der Digitalisierung, des stetigen technologischen Fortschritts und immer kürzer werdenden Produktlebenszyklen vor großen Herausforderungen. Um am Markt bestehen zu können, müssen Geschäftsmodelle öfter und schneller an sich verändernde Marktverhältnisse angepasst werden als dies früher der Fall war. Eine schnelle Anpassungsfähigkeit, auch Agilität genannt, ist in der heutigen Zeit ein entscheidender Wettbewerbsfaktor. Aufgrund des stetig wachsenden IT Anteils in Produkten sowie der Tatsache, dass diese IT-gestützt hergestellt werden, haben Änderungen des Geschäftsmodells große Auswirkungen auf die Unternehmensarchitektur eines Unternehmens.
Eine Unternehmensarchitektur umspannt das Unternehmen, indem diese die fachlichen und technischen Strukturen, insbesondere die gesamte IT, des Unternehmens beinhaltet und integriert. Das Management der Unternehmensarchitektur ist die Disziplin zur Beherrschung und Abstimmung dieser Strukturen. An der Gestaltung der Unternehmensarchitektur wirken viele Stakeholder mit individuellen und teils gegensätzlichen Interessen aus den unterschiedlichsten Bereichen des Unternehmens mit. Dies macht die Entscheidungsfindung zu einer komplexen Aufgabe.
Die in dieser Arbeit entworfene integrative Methode für die Entscheidungsfindung hat das Ziel, die Betroffenen und Beteiligten, im Folgenden Stakeholder, bei ihren Entscheidungen zu unterstützen. Die Grundidee hierbei ist die systematische Einbeziehung der Interessen der Stakeholder und davon abgeleiteter Visualisierungen. Dies verleiht der Methode ihren integrativen Charakter und hilft Abhängigkeiten zwischen Stakeholdern zu erkennen. Dadurch wird die Zusammenarbeit zwischen den an Entscheidungen beteiligten Stakeholdern gefördert. Neben der systematischen Einbeziehung von Visualisierungen wird im Rahmen dieser Arbeit das Konzept der Technik eingeführt. Techniken werden ebenfalls von den Interessen der Stakeholder abgeleitet und dienen der Unterstützung bei der Durchführung von Aktivitäten der Entscheidungsfindung, indem Vorgehensweisen bei bestimmten Aufgaben vorgegeben oder Teilprozesse der Entscheidungsfindung sogar automatisiert durchgeführt werden. Das Konzept der Technik, die systematische Ableitung von den Interessen der Stakeholder sowie das Zusammenspiel mit Visualisierungen wird in dieser Arbeit in Form einer erweiterten Konzeptualisierung der Architekturbeschreibung definiert.
Da die Werkzeugunterstützung in der Praxis häufig eine Herausforderung darstellt, rundet diese Arbeit ein eigens konzipiertes und prototypisch validiertes Architekturcockpit ab. Das Cockpit ist eine auf einem elektronischen Sitzungsraum basierende Werkzeugunterstützung der eingeführten integrativen Methode.
Modeling interactive Enterprise Architecture visualizations: an extended architecture description
(2018)
Enterprise architectures consist of a multitude of architecture elements, which relate in manifold ways to each other. Due to the high number of relationships between these elements, architectural analysis mechanisms are essential for all stakeholders to keep track and to work out relevant model characteristics. In practice EAs are often analyzed using visualizations by hand. However, the visualizations are often static and there are only few interaction possibilities. As a result, new visualizations have to be created or configured by experts if information demands change. In addition, hardly any tools are used for analysis of complex model characteristics. In this article we introduce an extended conceptualization of the architecture description that defines the structure of interactive visualizations and the integration of further tools to flexibly respond to the information demands of stakeholders. In addition, we develop a so-called Architecture Cockpit that realizes the extended conceptualization in a prototype. At the end we demonstrate and evaluate our approach through a practical test in a company in the finance and insurance industry.
Die Digitalisierung, der ständige technologische Fortschritt und immer kürzere Produktlebenszyklen stellen Unternehmen derzeit vor große Herausforderungen. Um am Markt erfolgreich zu sein, müssen Geschäftsmodelle häufiger und schneller als früher an veränderte Marktbedingungen angepasst werden. Schnelle Anpassungsfähigkeit, auch Agilität genannt, ist in der heutigen Zeit ein entscheidender Wettbewerbsfaktor. Aufgrund des ständig wachsenden IT-Anteils von Produkten und der Tatsache, dass diese mit Hilfe von IT hergestellt werden, hat die Änderung des Geschäftsmodells große Auswirkungen auf die Unternehmensarchitektur (EA). Die Entwicklung von EAs ist jedoch eine sehr komplexe Aufgabe, da viele Beteiligte mit gegensätzlichen Interessen in den Entscheidungsprozess eingebunden sind. Daher ist ein hohes Maß an Zusammenarbeit erforderlich. Um Unternehmen bei der Entwicklung ihrer EA zu unterstützen, wird in diesem Artikel eine neuartige integrative Methode vorgestellt, die die Interessen der Stakeholder systematisch in die Entscheidungsfindung einbezieht. Durch die Anwendung der Methode wird die Zusammenarbeit zwischen den beteiligten Interessengruppen verbessert, indem Berührungspunkte zwischen ihnen identifiziert werden. Darüber hinaus machen die standardisierten Aktivitäten die Entscheidungsfindung transparenter und vergleichbarer, ohne die Kreativität einzuschränken.
New business concepts such as Enterprise 2.0 foster the use of social software in enterprises. Especially social production significantly increases the amount of data in the context of business processes. Unfortunately, these data are still an unearthed treasure in many enterprises. Due to advances in data processing such as Big Data, the exploitation of context data becomes feasible. To provide a foundation for the methodical exploitation of context data, this paper introduces a classification, based on two classes, intrinsic and extrinsic data.
Leveraging textual information for improving decision making in the business process lifecycle
(2015)
Business process implementations fail, because requirements are elicited incompletely. At the same time, a huge amount of unstructured data is not used for decision-making during the business process lifecycle. Data from questionnaires and interviews is collected but not exploited because the effort doing so is too high. Therefore, this paper shows how to leverage textual information for improving decision making in the business process lifecycle. To do so, text mining is used for analyzing questionnaires and interviews.
Many future Services Oriented Architecture (SOA) systems may be pervasive SmartLife applications that provide real-time support for users in everyday tasks and situations. Development of such applications will be challenging, but in this position paper we argue that their ongoing maintenance may be even more so. Ontological modelling of the application may help to ease this burden, but maintainers need to understand a system at many levels, from a broad architectural perspective down to the internals of deployed components. Thus we will need consistent models that span the range of views, from business processes through system architecture to maintainable code. We provide an initial example of such a modelling approach and illustrate its application in a semantic browser to aid in software maintenance tasks.
Der lokale Bekleidungseinzelhandel steht unter immer stärkerem Konkurrenzdruck durch Versandunternehmen. Zusätzlich bestehen durch gewachsene Architekturen eine Reihe von Wachstumshemmnissen. Daher sollen hier eine Reihe von Ansätzen zur Gestaltung datenzentrierter Unternehmensarchitekturen für den Bekleidungseinzelhandel vorgestellt werden. Sie basieren auf dem Einsatz von RFID zur Gewinnung von Kundenprofilen in den Niederlassungen und dem Einsatz von Big-Data basierten Auswertungs- und Analysemechanismen. Mit den vorgestellten Konzepten ist es Unternehmen des Bekleidungseinzelhandels möglich, ähnlich wie Versandunternehmen, individuelle Ansprachen des Kunden und Angebote zu entwickeln
SmartLife ecosystems are emerging as intelligent user-centered systems that will shape future trends in technology and communication. Biological metaphors of living adaptable ecosystems provide the logical foundation for self-optimizing and self-healing run-time environments for intelligent adaptable business services and related information systems with service-oriented enterprise architectures. The present research in progress work investigates mechanisms for adaptable enterprise architectures for the development of service-oriented ecosystems with integrated technologies like Semantic Technologies, Web Services, Cloud Computing and Big Data Management. With a large and diverse set of ecosystem services with different owners, our scenario of service-based SmartLife ecosystems can pose challenges in their development, and more importantly, for maintenance and software evolution. Our research explores the use of knowledge modeling using ontologies and flexible metamodels for adaptable enterprise architectures to support program comprehension for software engineers during maintenance and evolution tasks of service-based applications. Our previous reference enterprise architecture model ESARC -- Enterprise Services Architecture Reference Cube -- and the Open Group SOA Ontology was extended to support agile semantic analysis, program comprehension and software evolution for a SmartLife applications scenario. The Semantic Browser is a semantic search tool that was developed to provide knowledge-enhanced investigation capabilities for service-oriented applications and their architectures.
The evolution of Services Oriented Architectures (SOA) presents many challenges due to their complex, dynamic and heterogeneous nature. We describe how SOA design principles can facilitate SOA evolvability and examine several approaches to support SOA evolution. SOA evolution approaches can be classified based on the level of granularity they address, namely, service code level, service interaction level and model level. We also discuss emerging trends, such as microservices and knowledge-based support, which can enhance the evolution of future SOA systems.
An enormous amount of data in the context of business processes is stored as images. They contain valuable information for business process management. Up to now this data had to be integrated manually into the business process. By advances of capturing it is possible to extract information from an increasing number of images. Therefore, we systematically investigate the potentials of Image Mining for business process management by a literature research and an in-depth analysis of the business process lifecycle. As a first step to evaluate our research, we developed a prototype for recovering process model information from drawings using Rapidminer.
Preface of IDEA 2015
(2016)
Digitization is more than using digital technologies to transfer data and perform computations and tasks. Digitization embraces disruptive effects of digital technologies on economy and society. To capture these effects, two perspectives are introduced, the product and the value-creation perspective. In the product perspective, digitization enables the transition from material, static products to interactive and configurable services. In the value-creation perspective, digitization facilitates the transition from centralized, isolated models of value creation, to bidirectional, co-creation oriented approaches of value creation.
Services Oriented Architectures (SOA) have emerged as a useful framework for developing interoperable, large-scale systems, typically implemented using the Web Services (WS) standards. However, the maintenance and evolution of SOA systems present many challenges. SmartLife applications are intelligent user-centered systems and a special class of SOA systems that present even greater challenges for a software maintainer. Ontologies and ontological modeling can be used to support the evolution of SOA systems. This paper describes the development of a SOA evolution ontology and its use to develop an ontological model of a SOA system. The ontology is based on a standard SOA ontology. The ontological model can be used to provide semantic and visual support for software maintainers during routine maintenance tasks. We discuss a case study to illustrate this approach, as well as the strengths and limitations.
Excellence in IT is a key enabler for the digital transformation of enterprises. To realize the vision of digital enterprises it is necessary to cope with changing business requirements and to align business and IT. In order to evaluate the contribution of enterprise architecture management to these goals, our paper explores the impact of various factors to the perceived benefit of EAM in enterprises. Based on literature, we build an empirical research model. It is tested with empirical data of European EAM experts using a structural equation modelling approach. It is shown that changing business requirements, IT business alignment, the complexity of information technology infrastructure as well as enterprise architecture knowledge of information technology employees are crucial impact factors to the perceived benefit of EAM in enterprises.
Neue Modelle für digitale Unternehmensarchitekturen mit Big Data, Services & Cloud Computing, mobilen Systemen, Internet of Things sowie Industrie 4.0 Ökosystemen machen eine enge Kooperation verschiedener Partner aus Wissenschaft, Anwendungsunternehmen, öffentlichen Organisationen, Softwarehersteller und IT- Dienstleister notwendig. Ziel dieser Zusammenarbeit ist die Zusammenführung neuer Konzepte und Möglichkeiten der Informationstechnologie zur bestmöglichen Unterstützung sich verändernder Unternehmensziele und -strategien. Software- und Unternehmensarchitekturen spielen hierbei eine zentrale Rolle. So werden Anforderungen bezüglich Flexibilität und Agilität in digitalen Unternehmen wesentlich durch serviceorientierte Ansätze unterstützt. Der Ordnungsgrad und die kosteneffiziente Gestaltung komplexer IT-Landschaften soll durch Digital Enterprise Architecture Management deutlich verbessert werden – passend zu neuen Möglichkeiten von Services & Cloud Computing, Big Data, sowie kollaborativen Geschäftsprozessen.
Steady growing research material in a variety of databases, repositories and clouds make academic content more than ever hard to discover. Finding adequate material for the own research however is essential for every researcher. Based on recent developments in the field of artificial intelligence and the identified digital capabilities of future universities a change in the basic work of academic research is predicted. This study defines the idea of how artificial intelligence could simplifiy academic research at a digital university. Today's studies in the field of AI spectacle the true potential and its commanding impact on academic research.
Revenue management information systems are very important in the hospitality sector. Revenue decisions can be better prepared based on different information from different information systems and decision strategies. There is a lack of research about the usage of such systems in small and medium-sized hotels and architectural configurations. Our paper empirically shows the current development of revenue information systems. Furthermore, we define future developments and requirements to improve such systems and the architectural base.
The digital transformation is today’s dominant business transformation having a strong influence on how digital services and products are designed in a service-dominant way. A popular underlying theory of value creation and economic exchange that is known as the service-dominant (S-D) logic can be connected to many successful digital business models. However, S-D logic by itself is abstract. Companies cannot directly use it as an instrument for business model innovation and design in an easy way. To address this a comprehensive ideation method based on S-D logic is proposed, called service-dominant design (SDD). SDD is aimed at supporting firms in the transition to a service- and value-oriented perspective. The method provides a simplified way to structure the ideation process based on four model components. Each component consists of practical implications, auxiliary questions and visualization techniques that were derived from a literature review, a use case evaluation of digital mobility and a focus group discussion. SDD represents a first step of having a toolset that can support established companies in the process of service- and value-orientation as part of their digital transformation efforts.
Enterprise architecture (EA) is useful for promoting digital transformation in global companies and information societies. In this paper, the authors investigated and analyzed the process for digital transformation in global companies, together with related work in using and applying an enterprise architecture framework for the digital era named the adaptive integrated digital architecture framework (AIDAF). Moreover, they position the AIDAF framework for processing digital transformation in global companies. Based on this analysis, the authors propose and describe a new enterprise architecture process for promoting digital transformation in global companies. Furthermore, the authors propose an adaptive EA cycle-based architecture board framework on digital platforms, while verifying them with case studies in global companies. Finally, the authors clarify the challenges and critical success factors of the process and framework for digital transformation with architecture board reviews in the adaptive EA cycle to assist EA practitioners with its implementation.
Enterprise architecture (EA) is useful for effectively structuring digital platforms with digital transformation in information societies. Moreover, digital platforms in the healthcare industry accelerate and increase the efficiency of drug discovery and development processes. However, there is the lack of knowledge concerning relationships between EA and digital platforms, in spite of the needs of it. In this paper, we investigated and analyzed the process of drug design and development within the healthcare industry, together with related work in using an enterprise architecture framework for the digital era named the Adaptive Integrated Digital Architecture Framework (AIDAF), specifically supporting the design of digital platforms there. Based on this analysis, we evaluate a method and propose a new reference architecture for promoting digital platforms in the healthcare industry, with future specific aspects of them making effective use of Artificial Intelligence (AI). The practical and theoretical contributions include: (1) Streamlined processes through digital platforms in organizations. (2) Informal knowledge supply and sharing among organizational members through digital platforms. (3) Efficiency and effectiveness in planning production and business for drug development. The findings indicate that EA with digital platforms using the AIDAF contribute to digital transformation with effectiveness for new drugs in the healthcare industry.
Theory and practice of implementing a successful enterprise IoT strategy in the industry 4.0 era
(2021)
Since the arrival of the internet and affordable access to technologies, digital technologies have occupied a growing place in industries, propelling us towards a 4th industrial revolution: Industry 4.0. In today’s era of digital upheaval, enterprises are increasingly undergoing transformations that are leading to their digitalization. The traditional manufacturing industry is in the throes of a digital transformation that is accelerated by exponentially growing technologies (e.g., intelligent robots, Internet of Things, sensors, 3D printing). Around the world, enterprises are in a frantic race to implement solutions based on IoT to improve their productivity, innovation, and reduce costs and improve their markets on the international scene. Considering the immense transformative potential that IoTs and big data have to bring to the industrial sector, the adoption of IoT in all industrial systems is a challenge to remain competitive and thus transform the industry into a smart factory. This paper presents the description of the innovation and digitalization process, following the Industry 4.0 paradigm to implement a successful enterprise IoT strategy.
Enterprises and information societies confront crucial challenges currently, while Industry 4.0 becomes important in the global manufacturing industry and Society 5.0 should contribute to a supersmart society, especially for healthcare. Physical activity monitoring digital platforms are architected to improve the healthcare status of patients with diabetes and other lifestyle-related diseases. Furthermore, digital platforms are expected to generate profits for health technology companies and help control costs in the healthcare ecosystem. However, current digital enterprise architecture approaches are not well-established, and the potentials have not yet been realized. Design thinking approach and agile software development methodologies can overcome these limitations, beginning with proof of concept and pilot projects and then scaling to the production environment. In this paper, we describe how that the adaptive integrated digital architecture framework (AIDAF) for Design Thinking approach is proposed and verified in a case of a university hospital in the Americas. In addition, challenges and future activities for this area are discussed that cover the directions for Society 5.0.
Digitization transforms business process models and processes in many enterprises. However, many of them need guidance, how digitization is impacting the design of their information systems. Therefore, this paper investigates the influence of digitization on information system design. We apply a two-phase research method applying a literature review and an exploratory case study. The case study took place in the IT service provider of a large insurance enterprise. The study’s results suggest that a number of areas of information system design are affected, such as architecture, processes, data and services.
Digital enterprise architecture management in tourism : state of the art and future directions
(2018)
The advance of information technology impacts tourism more than many other industries, due to the service character of its products. Most offerings in tourism are immaterial in nature and challenging in coordination. Therefore, the alignment of IT and strategy and digitization is of crucial importance to enterprises in tourism. To cope with the resulting challenges, methods for the management of enterprise architectures are necessary. Therefore, we scrutinize approaches for managing enterprise architectures based on a literature research. We found many areas for future research on the use of enterprise architecture in tourism.
Mit dem Kunstbegriff "Virtuelle Realität" beschreibt man die Darstellung von künstlichen Welten und die Interaktion mit den selbigen. Meist verbindet man damit teure Spiel- und Filmproduktionen. Doch durch derzeitige Entwicklungen können auch kleine Entwicklerstudios und Endanwender auf Bewegungserkennungssysteme zurückgreifen. In dieser Ausarbeitung werden zwei Prototypen vorgestellt, die auf eben diese Systeme zurückgreifen. In den Prototypen soll eine Interaktion mit der Umwelt und ein "Mittendringefühl" im Rahmen von Serious Games ermöglicht werden.
The relative pros and cons of using students or practitioners in experiments in empirical software engineering have been discussed for a long time and continue to be an important topic. Following the recent publication of “Empirical software engineering experts on the use of students and professionals in experiments” by Falessi, Juristo, Wohlin, Turhan, Münch, Jedlitschka, and Oivo (EMSE, February 2018) we received a commentary by Sjøberg and Bergersen. Given that the topic is of great methodological interest to the community and requires nuanced treatment, we invited two editorial board members, Martin Shepperd and Per Runeson, respectively, to provide additional views.
Digital Enterprise Architecture allows multiple viewpoints on a company’s IT landscape. To gain valuable information out of huge amounts of operational data, it is indispensable to have both an understanding of the operations architecture and an engine capable of managing Big Data. The mechanism of understanding huge amounts of data is based on three main steps: collect, process and use. The main idea is focused on extracting valuable information out of Big Data to make better design decisions. The Elastic Stack is an open-source solution to comfortably and quickly handle Big Data scenarios.
The digitization of our society changes the way we live, work, learn, communicate, and collaborate. This defines the strategical context for composing resilient enterprise architectures for micro-granular digital services and products. The change from a closed-world modeling perspective to more flexible open-world composition and evolution of system architectures defines the moving context for adaptable systems, which are essential to enable the digital transformation. Enterprises are presently transforming their strategy and culture together with their processes and information systems to become more digital. The digital transformation deeply disrupts existing enterprises and economies. Since years a lot of new business opportunities appeared using the potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. Digitization fosters the development of IT systems with many rather small and distributed structures, like Internet of Things or mobile systems. In this paper, we are focusing on the continuous bottom-up integration of micro-granular architectures for a huge amount of dynamically growing systems and services, like Internet of Things and Microservices, as part of a new digital enterprise architecture. To integrate micro-granular architecture models to living architectural model versions we are extending more traditional enterprise architecture reference models with state of art elements for agile architectural engineering to support the digitalization of services with related products, and their processes.
A new class of information system architecture, decision-oriented service systems, is spreading more and more. Decision-oriented service systems provide services that support decisions in business processes and products based on the capabilities of cloud-computing environments. To pave the way for the creation of design methods of business processes and products based on decision-oriented service systems, this article introduces a capability-oriented approach. Starting from technological capabilities, more abstract operational and dynamic capabilities are created. The framework created is based on an integrated conceptualization of decision-oriented service systems that allows capturing synergetic effects. By creating the framework, the gap between the technological capabilities of technologies and the strategic goals of enterprises shall be narrowed.
Digitization is the use of digital technologies for creating innovative digital business models and transforming existing business models, processes and systems. Digitization creates profound changes in the economy and society. Information is often captured and processed without human intervention using digital means. Digitization impacts nearly all products and services as well as the customer and the value-creation perspective.