1,400 research outputs found

    What skills pay more? The changing demand and return to skills for professional workers

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    Technology is disrupting labor markets. We analyze the demand and reward for skills at occupation and state level across two time periods using job postings. First, we use principal components analysis to derive nine skills groups: ‘collaborative leader’, ‘interpersonal & organized’, ‘big data’, ‘cloud computing’, ‘programming’, ‘machine learning’, ‘research’, ‘math’ and ‘analytical’. Second, we comment on changes in the price and demand for skills over time. Third, we analyze non-linear returns to all skills groups and their interactions. We find that ‘collaborative leader’ skills become significant over time and that legacy data skills are replaced over time by innovative ones

    Enhancing healthcare services through cloud service: a systematic review

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    Although cloud-based healthcare services are booming, in-depth research has not yet been conducted in this field. This study aims to address the shortcomings of previous research by analyzing all journal articles from the last five years using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) systematic literature review methodology. The findings of this study highlight the benefits of cloud-based healthcare services for healthcare providers and patients, including enhanced healthcare services, data security, privacy issues, and innovative information technology (IT) service delivery models. However, this study also identifies challenges associated with using cloud services in healthcare, such as security and privacy concerns, and proposes solutions to address these issues. This study concludes by discussing future research directions and the need for a complete solution that addresses the conflicting requirements of the security, privacy, efficiency, and scalability of cloud technologies in healthcare

    Monitoring tools for DevOps and microservices: A systematic grey literature review

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    Microservice-based systems are usually developed according to agile practices like DevOps, which enables rapid and frequent releases to promptly react and adapt to changes. Monitoring is a key enabler for these systems, as they allow to continuously get feedback from the field and support timely and tailored decisions for a quality-driven evolution. In the realm of monitoring tools available for microservices in the DevOps-driven development practice, each with different features, assumptions, and performance, selecting a suitable tool is an as much difficult as impactful task. This article presents the results of a systematic study of the grey literature we performed to identify, classify and analyze the available monitoring tools for DevOps and microservices. We selected and examined a list of 71 monitoring tools, drawing a map of their characteristics, limitations, assumptions, and open challenges, meant to be useful to both researchers and practitioners working in this area. Results are publicly available and replicable

    The value and structuring role of web APIs in digital innovation ecosystems: the case of the online travel ecosystem

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    Interfaces play a key role in facilitating the integration of external sources of innovation and structuring ecosystems. They have been conceptualized as design rules that ensure the interoperability of independently produced modules, with important strategic value for lead firms to attract and control access to complementary assets in platform ecosystems. While meaningful, these theorizations do not fully capture the value and structuring role of web APIs in digital innovation ecosystems. We show this with an empirical study of the online travel ecosystem in the 26 years (1995–2021) after the first Online Travel Agencies (OTAs) were launched. Our findings reveal that web APIs foster a dynamic digital innovation ecosystem with a distributed networked structure in which multiple actors design and use them. We provide evidence of an ecosystem where decentralized interfaces enable decentralized governance and where interfaces establish not only cooperative relationships, but also competitive ones. Instead of locking in complementors, web APIs enable the integration of capabilities from multiple organizations for the co-production of services and products, by interfacing their information systems. Web APIs are important sources of value creation and capture, increasingly being used to offer or sell services, constituting important sources of revenue

    Optimized Strategy in Cloud-Native Environment for Inter-Service Communication in Microservices

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    Cloud computing has become a prominent technology in the software development industry. The term “cloud-native” is derived from cloud computing technologies and refers to the development and deployment of applications in a cloud environment. In the software industry, most enterprise-grade software buildings use the microservice architecture and cloud natively, ultimately leading to an expansive development in the software development framework. Microservices are deployed in a distributed environment and function as independent services. However, they need to communicate with each other in order to fulfill the functional requirement. Additional latency will be introduced when communicating with other services. Hence, it will impact the overall application response time and throughput. This research proposes a solution for the aforementioned problem in the cloud-native environment. A Request-response-based TCP communication solution has been developed and tested in the cloud-native, containerized environment. Experimental results showed that the turnaround time of the proposed solution is shorter than that of traditional HTTP communication methods. Furthermore, the results summarize that both vertical and horizontal scaling are improving the overall performance of the systems performance in terms of response time. Conclusively, the proposed solution improved the microservice performance and preserved the existing cloud-native qualities, such as scalability, maintainability, and portability

    Insights into software development approaches: mining Q &A repositories

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    © 2023 The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Context: Software practitioners adopt approaches like DevOps, Scrum, and Waterfall for high-quality software development. However, limited research has been conducted on exploring software development approaches concerning practitioners’ discussions on Q &A forums. Objective: We conducted an empirical study to analyze developers’ discussions on Q &A forums to gain insights into software development approaches in practice. Method: We analyzed 13,903 developers’ posts across Stack Overflow (SO), Software Engineering Stack Exchange (SESE), and Project Management Stack Exchange (PMSE) forums. A mixed method approach, consisting of the topic modeling technique (i.e., Latent Dirichlet Allocation (LDA)) and qualitative analysis, is used to identify frequently discussed topics of software development approaches, trends (popular, difficult topics), and the challenges faced by practitioners in adopting different software development approaches. Findings: We identified 15 frequently mentioned software development approaches topics on Q &A sites and observed an increase in trends for the top-3 most difficult topics requiring more attention. Finally, our study identified 49 challenges faced by practitioners while deploying various software development approaches, and we subsequently created a thematic map to represent these findings. Conclusions: The study findings serve as a useful resource for practitioners to overcome challenges, stay informed about current trends, and ultimately improve the quality of software products they develop.Peer reviewe

    Modern computing: Vision and challenges

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    Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapting to cover multifaceted societal niches. This has led to new paradigms such as cloud, fog, edge computing, and the Internet of Things (IoT), which offer fresh economic and creative opportunities. Nevertheless, this rapid change poses complex research challenges, especially in maximizing potential and enhancing functionality. As such, to maintain an economical level of performance that meets ever-tighter requirements, one must understand the drivers of new model emergence and expansion, and how contemporary challenges differ from past ones. To that end, this article investigates and assesses the factors influencing the evolution of computing systems, covering established systems and architectures as well as newer developments, such as serverless computing, quantum computing, and on-device AI on edge devices. Trends emerge when one traces technological trajectory, which includes the rapid obsolescence of frameworks due to business and technical constraints, a move towards specialized systems and models, and varying approaches to centralized and decentralized control. This comprehensive review of modern computing systems looks ahead to the future of research in the field, highlighting key challenges and emerging trends, and underscoring their importance in cost-effectively driving technological progress

    Desarrollo de un proceso de creación y despliegue de microservicios a partir de requerimientos funcionales

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    El paulatino avance de las arquitecturas de software basadas en microservicios y la creciente relevancia de la ingeniería de requerimientos en el desarrollo de aplicaciones y sistemas web han generado la necesidad de automatizar el proceso de creación y despliegue de microservi- ci os. En este senti do, l a combi naci ón de técnicas de Procesa mi ento de Len guaj e Natural (PLN) con análisis de grafos y detección de comunidades se presenta como un enfoque poderoso para abordar desafíos en diversos campos, incluyendo la ingeniería de software y el diseño de arquitecturas basadas en microservicios. Asimismo, en los últimos tiempos, los modelos de lenguaje de inteligencia artificial, como ChatGPT, han experimentado una notable popular- idad y atención en diferentes ámbitos. Su capacidad para mejorar y generar texto existente ha despertado un gran interés entre investigadores, empresas y usuarios en general. Teniendo en cuenta este contexto, el siguiente trabajo de titulación propone un proceso para la identifi- cación y despliegue automatizado de microservicios, aprovechando las ventajas que ofrecen las técnicas de procesamiento de lenguaje natural y análisis de grafos. Se espera que este enfoque contribuya significativamente a mejorar y automatizar el desarrollo de aplicaciones basadas en microservicios.With the gradual advancement of microservices-based software architectures and the increas- ing relevance of requirements engineering in the development of applications and web sys - tems, there is a need for methods or processes that automate the creation and deployment of microservices. The combination of Natural Language Processing (NLP) techniques with graph analysis and community detection offers a powerful approach to address challenges in various fi el ds. In the real m of software engi neeri ng, this combi nati on has been expl ored to enh ance the design and deployment process of microservices-based architectures. Additionally, in recent times, language models of artificial intelligence, such as ChatGPT, have gained great popu - larity and attention in various domains. The ability to improve and generate existing text has sparked interest among researchers, companies, and users in general. In this context, the fol- lowing thesis work proposes a process for the identification and deployment of microservices, leveraging the advantages of natural language processing techniques and graph analysis. It is expected that this approach will contribute to improving and automating the development of microservices-based applications.0000-0002-2438-922
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