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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.
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.
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.
Sleep quality and in general, behavior in bed can be detected using a sleep state analysis. These results can help a subject to regulate sleep and recognize different sleeping disorders. In this work, a sensor grid for pressure and movement detection supporting sleep phase analysis is proposed. In comparison to the leading standard measuring system, which is Polysomnography (PSG), the system proposed in this project is a non invasive sleep monitoring device. For continuous analysis or home use, the PSG or wearable actigraphy devices tends to be uncomfortable. Besides this fact, they are also very expensive. The system represented in this work classifies respiration and body movement with only one type of sensor and also in a non invasive way. The sensor used is a pressure sensor. This sensor is low cost and can be used for commercial proposes. The system was tested by carrying out an experiment that recorded the sleep process of a subject. These recordings showed the potential for classification of breathing rate and body movements. Although previous researches show the use of pressure sensors in recognizing posture and breathing, they have been mostly used by positioning the sensors between the mattress and bedsheet. This project however, shows an innovative way to position the sensors under the mattress.
Medical applications are becoming increasingly important in the current development of health care and therefore a crucial part of the medical industry. The work focuses on the analysis of requirements and the challenges arisen from designing mobile medical applications in relation to the user interface. The paper describes the current status in the development of mobile medical apps and illustrates the development of e-health market. The author will explain the requirements and will illustrate the hurdles and problems. He refers to the German market which is similar to the European and compares that with the market in the USA.
Scheduled flexibility and individualization of knowledge transfer in foundations of computer science
(2017)
The opening of the German higher education system for new target groups involves a heterogeneous composition of students as never before and face up the universities to new challenges. Due to different educational biographies, the students don't show a homogeneous level of knowledge. Furthermore, their access to course content and their individual learning methods are very diverse. The existing lack of knowledge and the very unequal study speed have a significant influence on the learning behavior and learning motivation. During the first semesters, the dropout rate is appreciably higher. The reform project gives an overview of a didactic restructuring from a formerly conventional teaching and learning concept to a stronger combination of digital offers, combined with classical lectures in the basic modules of computer science. The teaching content is adjusted to the individual requirements and knowledge. Students with different previous knowledge get the possibility to increase their knowledge in different levels of abstraction. The aim of the reform project has to point out the possibilities, also the challenges of the digital process in higher education. At the same time the question has to be explored, how far does an accompanied and self-directed learning in own speed and in own individual depth of knowledge have a positive impact on the motivation and on the study success of a learner.
Incubators in multinational corporations : development of a corporate incubator operator model
(2017)
This paper analyzes the components of a corporate incubator operator model in multinational companies. Thereby, three relevant phases were identified: pre incubation, incubation, and exit. Each phase contains different criteria that represent critical success factors for a corporate incubator, which are based on theoretical findings and lessons learned from practice. During the pre-incubation phase companies should define their need for a corporate incubator, the origin of ideas and the selection criteria for incubator tenants. The actual phase of incubation refers to the incubator program, which should be flexible with respect to each tenant. Furthermore, resource allocation plays an important role during the incubator program. Exit options after a successful incubation differ according to internal ideas and external start-ups, as well as the objective of the incubator. The research is based on a comprehensive screening of existing incubator literature and a qualitative content analysis of statements from eight experts of international corporate incubators.
The digital transformation of the automotive industry has a significant impact on how development processes need to be organized in future. Dynamic market and technological environments require capabilities to react on changes and to learn fast. Agile methods are a promising approach to address these needs but they are not tailored to the specific characteristics of the automotive domain like product line development. Although, there have been efforts to apply agile methods in the automotive domain for many years, significant and widespread adoptions have not yet taken place. The goal of this literature review is to gain an overview and a better understanding of agile methods for embedded software development in the automotive domain, especially with respect to product line development. A mapping study was conducted to analyze the relation between agile software development, embedded software development in the automotive domain and software product line development. Three research questions were defined and 68 papers were evaluated. The study shows that agile and product line development approaches tailored for the automotive domain are not yet fully explored in the literature. Especially, literature on the combination of agile and product line development is rare. Most of the examined combinations are customizations of generic approaches or approaches stemming from other domains. Although, only few approaches for combining agile and software product line development in the automotive domain were found, these findings were valuable for identifying research gaps and provide insights into how existing approaches can be combined, extended and tailored to suit the characteristics of the automotive domain.
Software and system development faces numerous challenges of rapidly changing markets. To address such challenges, companies and projects design and adopt specific development approaches by combining well-structured comprehensive methods and flexible agile practices. Yet, the number of methods and practices is large, and available studies argue that the actual process composition is carried out in a fairly ad-hoc manner. The present paper reports on a survey on hybrid software development approaches. We study which approaches are used in practice, how different approaches are combined, and what contextual factors influence the use and combination of hybrid software development approaches. Our results from 69 study participants show a variety of development approaches used and combined in practice. We show that most combinations follow a pattern in which a traditional process model serves as framework in which several fine-grained (agile) practices are plugged in. We further show that hybrid software development approaches are independent from the company size and external triggers. We conclude that such approaches are the results of a natural process evolution, which is mainly driven by experience, learning, and pragmatism.
First International Workshop on Hybrid dEveLopmENt Approaches in Software Systems Development
(2017)
A software process is the game plan to organize project teams and run projects. Yet, it still is a challenge to select the appropriate development approach for the respective context. A multitude of development approaches compete for the users’ favor, but there is no silver bullet serving all possible setups. Moreover, recent research as well as experience from practice shows companies utilizing different development approaches to assemble the bestfitting approach for the respective company: a more traditional process provides the basic framework to serve the organization, while project teams embody this framework with more agile (and/or lean) practices to keep their flexibility. The first HELENA workshop aims to bring together the community to discuss recent findings and to steer future work.
Using measurement and simulation for understanding distributed development processes in the Cloud
(2017)
Organizations increasingly develop software in a distributed manner. The Cloud provides an environment to create and maintain software-based products and services. Currently, it is widely unknown which software processes are suited for Cloud-based development and what their effects in specific contexts are. This paper presents a process simulation to study distributed development in the Cloud. We contribute a simulation model, which helps analyzing different project parameters and their impact on projects carried out in the Cloud. The simulator helps reproducing activities, developers, issues and events in the project, and it generates statistics, e.g., on throughput, total time, and lead and cycle time. The aim of this simulation model is thus to analyze the tradeoffs regarding throughput, total time, project size, and team size. Furthermore, the modified simulation model aims to help project managers select the most suitable planning alternative. Based on observed projects in Finland and Spain, we simulated a distributed project using artificial and real data. Particularly, we studied the variables project size, team size, throughput, and total project duration. A comparison of the real project data with the results obtained from the simulation shows the simulation producing results close to the real data, and we could successfully replicate a distributed software project. By improving the understanding of distributed development processes, our simulation model thus supports project managers in their decision-making.
Rapid Prototyping Plattformen reduzieren die Entwicklungszeit, indem das Überprüfen einer Idee in Form eines Prototyps schnell umzusetzen ist und mehr Zeit für die eigentliche Anwendungsentwicklung mit Benutzerschnittstellen zur Verfügung steht. Dieser Ansatz wird schon lange bei technischen Plattformen, wie bspw. dem Arduino, verfolgt. Um diese Form von Prototyping auf Wearables zu übertragen, wird in diesem Paper WearIT vorgestellt. WearIT besteht als Wearable Prototyping Plattform aus vier Komponenten: Einer Weste, Sensor- und Aktorshieldss, einer eigenen bibliothek sowie einem Mainboard bestehend aus Arduino, Raspberry Pi, einer Steckplatine und einem GPS-Modul. Als Ergebnis kann ein Wearable Prototyp schnell, durch das Anbringen von Sensor- und Aktorshields an der WearIT Weste, entwickelt werden. Diese Sensor- und Aktorshields können anschließend durch die WearIT-Bibliothek programmiert werden. Dafür kann über Virtual Network Computing (VNC) mit einem entfernten Rechner auf die Bildschirminhalte des Rasperry Pis zugegriffen und der Arduino programmiert werden.
Im Rahmen der wissenschaftlichen Vertieung werden unterschiedliche empirische Forschungsmethoden erörtert.
Im ersten Schritt werden die Grundlagen der empirischen Forschungsmethoden ermittelt und klassifiziert. Nach der Klassifikation der Forschungsmethoden werden zwei Forschunsmethoden angewandt. Die Auswahl der Methoden fällt auf die quantitative und qualitative Forschungsmethode.
Diese Forschungsmethoden werden während der Analysephase eingesetzt, um den weltweiten Ist-Zustand der Tochtergesellschaften zu ermitteln. Hierbei geht es um die Analyse des Import- und Export-Prozesses bei den Tochtergesellschaften der HUGO BOSS AG. Ziel ist es, die Ergebnisse für die Master Thesis einzusetzen. Anhand der Ergebnisse können Gemeinsamkeiten oder auch Abweichungen im Zollabwicklungsprozess aufgezeigt werden, die später in der Konzeption berücksichtigt werden.
Hierzu wird die qualitative Methode eingesetzt, welche die Basis für die Konzeptionierung der Umfrage liefert. Abschließend wurde für die Verifikation der Ergebnisse die qualitative Methode für die Interviews eingesetzt.
Automatisierte Analyse von Review-Daten beschäftigt sich mit den Möglichkeiten, freien Text zu analysieren und relevante Informationen daraus zu extrahieren. Die Arbeit setzt sich dabei mit Methoden des unüberwachten Lernens auseinander. Hierbei steht die Methode der Topic Modellierung im Mittelpunkt. Es werden Verfahren betrachtet, die im Bereich der textbasierten Informationsgewinnung bekannt sind. Latent Semantic Indexing LSI, (probabilistic) pLSI und Latent Dirichlet Allocation (LDA) werden erläutert und verglichen. Die Arbeit zeigt, wie LDA genutzt wurde, um einen nhaltlichen Überblick über einen Datenkorpus von 1 Mio. Reviews zu bekommen und diesen auf einen feineren Detailgrad zu betrachten. Die Topic-basierte Analyse wird genutzt, um Erkentnisse für ein Opinion Mining System zu generieren, welches eine tiefergehende Analyse vornehmen wird. Der gesamte Prozess ist als vollständig automatisiert und maschinell unüberwacht konzeptioniert.
Im Rahmen dieser Arbeit wurde ein urbaner Mixed-Reality Fahrsimulator umgesetzt. Die reale Umgebung wird hierbei in einer Greenscreen-Kammer mit Hilfe von Kamerabildern aus Nutzersicht und einem Chroma Key Shader innerhalb der virtuellen Umgebung sichtbar gemacht. Dies soll die Immersion und die Interaktivität innerhalb der virtuellen Umgebung durch die Darstellung und Verwendung von realen Elementen erhöhen.
Als virtuelle Umgebung wurde eine zufallsgenerierte Stadt geschaffen, in der KI-Fahrzeuge fahren. Die Ergebnisse der Entwicklung dieses Fahrsimulators werden in dieser Arbeit erläutert.
Der Fahrsimulator soll der Entwicklung von menschzentrierten Human-Machine-Interfaces und Motion-Capture-Komponenten dienen.
Asymmetric read/write storage technologies such as Flash are becoming
a dominant trend in modern database systems. They introduce
hardware characteristics and properties which are fundamentally
different from those of traditional storage technologies such
as HDDs.
Multi-Versioning Database Management Systems (MV-DBMSs)
and Log-based Storage Managers (LbSMs) are concepts that can
effectively address the properties of these storage technologies but
are designed for the characteristics of legacy hardware. A critical
component of MV-DBMSs is the invalidation model: commonly,
transactional timestamps are assigned to the old and the new version,
resulting in two independent (physical) update operations.
Those entail multiple random writes as well as in-place updates,
sub-optimal for new storage technologies both in terms of performance
and endurance. Traditional page-append LbSM approaches
alleviate random writes and immediate in-place updates, hence reducing
the negative impact of Flash read/write asymmetry. Nevertheless,
they entail significant mapping overhead, leading to write
amplification.
In this work we present an approach called Snapshot Isolation
Append Storage Chains (SIAS-Chains) that employs a combination
of multi-versioning, append storage management in tuple granularity
and novel singly-linked (chain-like) version organization.
SIAS-Chains features: simplified buffer management, multi-version
indexing and introduces read/write optimizations to data placement
on modern storage media. SIAS-Chains algorithmically avoids
small in-place updates, caused by in-place invalidation and converts
them into appends. Every modification operation is executed
as an append and recently inserted tuple versions are co-located.
To analyze the humans’ sleep it is necessary as to identify the sleep stages, occurring during the sleep, their durations and sleep cycles. The gold standard procedure for this approach is polysomnography (PSG), which classify the sleep stages based on Rechtschaffen and Kales (R-K) method. This method aside the advantages as high accuracy has however some disadvantages, among others time-consuming and uncomfortable for the patient procedure. Therefore, the development of further methods for the sleep classification in addition to PSG is a promising topic for the investigation and this work has as its aim the presentation of possible ways and goals for this development.
A sleep study is a test used to diagnose sleep disorders and is usually done in sleep laboratories. The golden standard for evaluation of sleep is overnight polysomnography (PSG). Unfortunately, in-lab sleep studies are expensive and complex procedures. Furthermore, with a minimum of 22 wire attachments to the patient for sleep recording, this medical procedure is invasive and unfamiliar for the subjects. To solve this problem, low-cost home diagnostic systems, based on noninvasive recording methods requires further researches.
For this intention it is important to find suitable bio vital parameters for classifying sleep phases WAKE, REM, light sleep and deep sleep without any physical impairment at the same time. We decided to analyse body movement (BM), respiration rate (RR) and heart rate variability (HRV) from existing sleep recordings to develop an algorithm which is able to classify the sleep phases automatically. The preliminary results of this project show that BM, RR and HRV are suitable to identify WAKE, REM and NREM stage.
Medical applications are becoming increasingly important in the current development of health care and therefore a crucial part of the medical industry. An essential component is the development of user interfaces for mobile medical applications. The conceptual process is crucial for the further development of the main development process. Inconsistency or errors in the conceptual phase, have a serious impact on all areas and could prevent the certification for market approval.
This paper presents a guide to support developer with this process. It was developed based on a requirement analysis of the legal requirements to publish a medical device.