TY  - CHAP
A1  - Sildatke, Michael
A1  - Karwanni, Hendrik
A1  - Kraft, Bodo
A1  - Schmidts, Oliver
A1  - Zündorf, Albert
T1  - Automated Software Quality Monitoring in Research Collaboration Projects
T2  - ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops
N2  - In collaborative research projects, both researchers and practitioners work together solving business-critical challenges. These projects often deal with ETL processes, in which humans extract information from non-machine-readable documents by hand. AI-based machine learning models can help to solve this problem.

Since machine learning approaches are not deterministic, their quality of output may decrease over time. This fact leads to an overall quality loss of the application which embeds machine learning models. Hence, the software qualities in development and production may differ.

Machine learning models are black boxes. That makes practitioners skeptical and increases the inhibition threshold for early productive use of research prototypes. Continuous monitoring of software quality in production offers an early response capability on quality loss and encourages the use of machine learning approaches. Furthermore, experts have to ensure that they integrate possible new inputs into the model training as quickly as possible.

In this paper, we introduce an architecture pattern with a reference implementation that extends the concept of Metrics Driven Research Collaboration with an automated software quality monitoring in productive use and a possibility to auto-generate new test data coming from processed documents in production.

Through automated monitoring of the software quality and auto-generated test data, this approach ensures that the software quality meets and keeps requested thresholds in productive use, even during further continuous deployment and changing input data.
Y1  - 2020
U6  - https://doi.org/10.1145/3387940.3391478
N1  - ICSE '20: 42nd International Conference on Software Engineering, Seoul, Republic of Korea, 27 June 2020 - 19 July 2020
SP  - 603
EP  - 610
PB  - IEEE
CY  - New York, NY
ER  - 
TY  - CHAP
A1  - Kurz, Melanie
ED  - Feijs, Loe
T1  - On the benefit of moving images for the evaluation of form in virtual space : reflections in model theory
T2  - Design and semantics of form and movement : DeSForM 2008 ; [Hochschule für Gestaltung Offenbach am Main, 6.-7.11.2008]
Y1  - 2008
SN  - 978-90-809801-2-9
SP  - 31
EP  - 34
PB  - Philips
CY  - Eindhoven
ER  - 
TY  - CHAP
A1  - Kurz, Melanie
T1  - Recognition of shape in virtual visualizations
T2  - Proceedings : November 15 - 17, 2006, Technische Universität Darmstadt, Darmstadt, Germany ; PACE, Partners for the advancement of collaborative engineering education
Y1  - 2006
SN  - 978-3-00-020161-5
N1  - International PACE Forum Collaborative Visualization ; (2006, Darmstadt)
SP  - 203
EP  - 209
PB  - Techn. Univ.
CY  - Darmstadt
ER  -