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Open tracing tools
(2023)
Background: Coping with the rapid growing complexity in contemporary software architecture, tracing has become an increasingly critical practice and been adopted widely by software engineers. By adopting tracing tools, practitioners are able to monitor, debug, and optimize distributed software architectures easily. However, with excessive number of valid candidates, researchers and practitioners have a hard time finding and selecting the suitable tracing tools by systematically considering their features and advantages. Objective: To such a purpose, this paper aims to provide an overview of popular Open tracing tools via comparison. Methods: Herein, we first identified 30 tools in an objective, systematic, and reproducible manner adopting the Systematic Multivocal Literature Review protocol. Then, we characterized each tool looking at the 1) measured features, 2) popularity both in peer-reviewed literature and online media, and 3) benefits and issues. We used topic modeling and sentiment analysis to extract and summarize the benefits and issues. Specially, we adopted ChatGPT to support the topic interpretation. Results: As a result, this paper presents a systematic comparison amongst the selected tracing tools in terms of their features, popularity, benefits and issues. Conclusion: The result mainly shows that each tracing tool provides a unique combination of features with also different pros and cons. The contribution of this paper is to provide the practitioners better understanding of the tracing tools facilitating their adoption.
Das Forschungsprojekt Data Sharing Framework untersuchte Data Sharing im Kontext von datenbasierten Services und Produkten in Ökosystemen aus fünf Perspektiven: Kultur, Vertrauen, Wert, Recht & Governance, Sicherheit. Die Forschungsergebnisse bestätigen die Relevanz dieser Perspektiven und es hat sich gezeigt, dass diese Aspekte sowohl Barrieren als auch Treiber für Datennutzung und -austausch zwi- schen Unternehmen darstellen.
Ausgangspunkt waren die folgenden forschungs- und praxisleitenden Annahmen:
• These 1: KMU können durch die Nutzung und das
Teilen von Daten Mehrwerte in Form neuer Produkte und Services generieren. Aus wissenschaftlicher Sicht liegt der Fokus des Themas Daten und Data Science bisher überwiegend auf der technischen Umsetzung datenintensiver Geschäftsmodelle und Kooperationen durch die Unternehmen.
• These 2: Die technische Umsetzung ist eine notwendige Bedingung für die datenbasierte Leistun- gen, sie reicht jedoch nicht aus, um eine Kooperations- und Teilbereitschaft bei KMU hinsichtlich ihrer Daten (Daten-Teilbereitschaft) auszulösen. Zahlreiche Stakeholder zögern, Daten zu teilen, vor allem in einem grenzüberschreitenden Kontext, wie z.B. in der Programmregion.
• These 3: KMU benötigen Data Access und Data Trust Strukturen, um mögliche Kooperationspotenziale tatsächlich zu heben. Dies erfordert u.a. gemeinsa- me Standards, ein annäherndes Verständnis vom Wert der Daten, Data-Governance in Kombination mit zu definierenden Trust-Standards, welche die erforderliche formelle und informelle Sicherheit bieten.
Nachfolgend wird ein Überblick über die hieraus hervorgegangenen Ergebnisse gegeben:
Kultur
Die Perspektive der Organisationskultur stellt das Denken und Handeln im Unternehmen und im Ökosystem in den Mittelpunkt. Eine Organisationskultur, welche die Arbeit mit Daten, Data Science Praktiken und vor allem das Teilen von Daten ermöglicht, stellt Daten in den Mittelpunkt des Wertschöpfungsprozesses. Dies erfordert eine generelle Sensibilisierung
für das Thema Daten, durchlässige Grenzen im und zwischen Unternehmen, ebenso wie ein neues Verständnis von Rollen, Strukturen und Prozessen im Unternehmen.
Vertrauen
Das Vertrauen ist im Ökosystem von großer Bedeutung. Das Einbeziehen von internen Stakeholdern und das Starten mit kleineren Pilotprojekten wird vorgeschlagen, um Vertrauen innerhalb der Organisation und mit externen Partnern zu schaffen.
Wert
Als notwendige Voraussetzung wird der Wert der Daten hervorgehoben. Unternehmen sollten den potenziellen Wert der Datenflüsse kennen, bevor sie sich entscheiden, ob sie diese Daten teilen und nutzen möchten. Es wird empfohlen, eine grobe Quanti- fizierung des Wertflusses vorzunehmen oder gegebe- nenfalls eine detailliertere Analyse durchzuführen.
Recht & Governance
Für die Berücksichtigung rechtlicher Rahmenbedingungen gemeinsamer Datennutzung sollten Organisationen zunächst eine interne Data Governance etablieren, um auf neue regulatorische Entwicklungen reagieren zu können. Die Einrichtung von Data-Asset-Management, Data-IP und -Compliance-Ma-nagement und Data-Contract-Management wird hier empfohlen.
Datensicherheit
Im Sicherheitskontext sind Methoden zur Gewährleistung der Datenintegrität, Privatsphäre und Sicherheit entscheidend. Es wird empfohlen, einen kollaborativen Ansatz zur Implementierung von Sicherheitsstandards zu verfolgen und dabei IKT-Experten einzubeziehen. Anfänglich können Best Practices ausreichen, aber längerfristig sollte eine kontinuierliche Sicherheitsrisikobewertung und Ge- schäftsprozessintegration angestrebt werden.
Creating a schedule to perform certain actions in a realworld environment typically involves multiple types of uncertainties. To create a plan which is robust towards uncertainties, it must stay flexible while attempting to be reliable and as close to optimal as possible. A plan is reliable if an adjustment to accommodate for a new requirement causes only a few disruptions. The system needs to be able to adapt to the schedule if unforeseen circumstances make planned actions impossible, or if an unlikely event would enable the system to follow a better path. To handle uncertainties, the used methods need to be dynamic and adaptive. The planning algorithms must be able to re-schedule planned actions and need to adapt the previously created plan to accommodate new requirements without causing critical disruptions to other required actions.
Coupling is one of the most frequently mentioned metric in software systems. However, to measure logical coupling between microservices, runtime information is needed or the availability of service-log files to analyze the calls between services is required. This work presents our emerging results, in which we propose a metric to statically calculate logical coupling between microservices based on commits to versioning systems. We performed an initial validation of the proposed metric with a dataset containing 145 open-source microservices projects. The results illustrate how logical coupling affects every system and increases overtime. However, we did not find a correlation between the number of commits or the number of developers and the introduction of logical coupling. In future, we investigate why, how, and when logical coupling is introduced in a system.
This paper presents design, simulation, and optimization of the three-dimensional 1×4 optical multimode interference splitter using IP-Dip polymer as a core and polydimethylsiloxane (PDMS) Sylgard 184 as a cladding. The splitter was simulated by using beam propagation method in BeamPROP simulation engine of RSoft photonic tool and optimized for an operating wavelength of 1.55 µm. According to the minimum insertion loss, the dimensions of the MMI coupler and the length of the whole MMI splitter structure were optimized applying a waveguide with a core size of 4×4 µm2. The objective of the study is to create a design for fabrication by three-dimensional direct laser writing optical lithography.
Design, simulation, and optimization of the 1×4 optical three-dimensional multimode interference splitter using IP-Dip polymer as a core and polydimethylsiloxane (PDMS) Sylgard 184 as a cladding is demonstrated. The splitter was simulated by using beam propagation method in BeamPROP simulation module of RSoft photonic tool and optimized for an operating wavelength of 1.55 μm . According to the minimum insertion loss, the dimensions of the splitter were optimized for a waveguide with a core size of 4×4 μm2 . The objective of the study is to create the design for fabrication by three-dimensional direct laser writing optical lithography.
The role of entrepreneurs and intrapreneurs in the current zeitgeist is to drive innovation, re-shape rigid, established processes in business as well as for consumers. They use new viewpoints to pioneer new (business) models which focus on ‘smartness’ rather than the purely monetary and short-sighted models of yesteryear. Fostering and supporting the culture of this current zeitgeist is a mayor challenge for entre- and intrapreneurial support infrastructures, namely startup centres and innovation hubs of universities and other public institutions as well as innovation centres of private companies. Hereby, support may range from access to funding over provision of resources such as offices or computing hardware to coaching in the development of business ideas and strategic roadmaps for product and service deployment. In this paper, we focus on describing the status-quo of afore- mentioned support infrastructures in Vorarlberg and the Lake Constance region, then extend the scope to existing (international) approaches for aiding founders and inno- vators in the development of smart services. An analysis of success stories of the Vorarlberg startup centre ‘startupstube’ and other initiatives including their compar- ison to international counterparts builds the basis for a methodological framework for (service science) coaching in entre- and intrapreneurial support infrastructures. The paper is concluded by the description of a framework for choosing the right methods and tools to create service value in entre-/intrapreneurship based upon tested, proven know-how and for defining support infrastructure needs based upon pre-defined stakeholder and target groups as well as the (industry) sectors of the innovators.