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pro vyhledávání: '"Hesse, Guenter"'
Growing data volumes and velocities in fields such as Industry 4.0 or the Internet of Things have led to the increased popularity of data stream processing systems. Enterprises can leverage these developments by enriching their core business data and
Externí odkaz:
http://arxiv.org/abs/2103.06775
Software Repositories contain knowledge on how software engineering teams work, communicate, and collaborate. It can be used to develop a data-informed view of a team's development process, which in turn can be employed for process improvement initia
Externí odkaz:
http://arxiv.org/abs/2007.08265
Message brokers see widespread adoption in modern IT landscapes, with Apache Kafka being one of the most employed platforms. These systems feature well-defined APIs for use and configuration and present flexible solutions for various data storage sce
Externí odkaz:
http://arxiv.org/abs/2003.06452
Autor:
Matthies, Christoph, Hesse, Guenter
Publikováno v:
Proceedings of the 14th International Conference on Software Technologies - Volume 1: ICSOFT, 2019, ISBN 978-989-758-379-7, pages 552-559
Software development comprises complex tasks which are performed by humans. It involves problem solving, domain understanding and communication skills as well as knowledge of a broad variety of technologies, architectures, and solution approaches. As
Externí odkaz:
http://arxiv.org/abs/1907.12959
Publikováno v:
Proceedings of the 8th International Conference on Data Science, Technology and Applications (DATA), 2019, pages 304-310
Industry 4.0 is becoming more and more important for manufacturers as the developments in the area of Internet of Things advance. Another technology gaining more attention is data stream processing systems. Although such streaming frameworks seem to
Externí odkaz:
http://arxiv.org/abs/1907.09387
Publikováno v:
2019 International Conference on Distributed Computing Systems (ICDCS), pp. 1381-1392
With the demand to process ever-growing data volumes, a variety of new data stream processing frameworks have been developed. Moving an implementation from one such system to another, e.g., for performance reasons, requires adapting existing applicat
Externí odkaz:
http://arxiv.org/abs/1907.08302
Industry 4.0 and the Internet of Things are recent developments that have lead to the creation of new kinds of manufacturing data. Linking this new kind of sensor data to traditional business information is crucial for enterprises to take advantage o
Externí odkaz:
http://arxiv.org/abs/1903.06453
Publikováno v:
2019 IEEE/ACM 1st International Workshop on Bots in Software Engineering (BotSE), Montreal, QC, Canada, 2019, pp. 34-37
Recent advances in natural-language processing and data analysis allow software bots to become virtual team members, providing an additional set of automated eyes and additional perspectives for informing and supporting teamwork. In this paper, we pr
Externí odkaz:
http://arxiv.org/abs/1903.02443
Publikováno v:
2018 IEEE Frontiers in Education Conference (FIE), San Jose, CA, USA, 2018, pp. 1-9
This Innovative Practice Full Paper presents an approach of using software development artifacts to gauge student behavior and the effectiveness of changes to curriculum design. There is an ongoing need to adapt university courses to changing require
Externí odkaz:
http://arxiv.org/abs/1807.02400
Autor:
Hesse, Guenter
Data stream processing systems (DSPSs) are a key enabler to integrate continuously generated data, such as sensor measurements, into enterprise applications. DSPSs allow to steadily analyze information from data streams, e.g., to monitor manufacturin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::62bc826c6bebb4533ed3e57e7757861d