Software Systems
We Transform Ideas into Software
Fast societal, economic, and technological changes demand a quick pace in developing and maintaining software systems. Therefore, our mission at the Software Systems (SWS) research group is to develop novel methods and tools to ensure rapid software development of high-quality software products. We are experts in the application of empirical software engineering methods and tools to ensure the successful development and transfer of our research products for and to industry. Currently, we focus on the following topics:
- Use Case-oriented Software Production and Model-Driven Engineering Tools
- Requirements Engineering
- Traceability Engineering
- Digitalisation of the Software Development Life Cycle
- Agile Software Development and Continues Integration
- Virtual Tools for Collaboration in Software Engineering
- Test Automation
We work on these topics together with external business partners within national and international projects. Our research expertise is as well incorporated into the computer science degree program and is passed on to students in modules such as the software project, programming, software engineering, web development, and various elective modules like rapid software prototyping for engineering sciences, which involves students from other engineering programs like avionics and mechanical engineering.
Research Topics
Automated Software Generation
Model-Driven Engineering (MDE) enables the automatic generation of software by means of incremental transformation of models (e.g., graphically represented as diagrams) specifying information systems’ business logic, data structures, business rules, graphical user interface, etc. Among other advantages, MDE approaches ensure code quality by supporting requirements engineering, allow high development speed, and foster separation of business logic from underlying platform technologies. We have extensive experience in developing MDE methods and tools that support object-oriented and domain-specific modelling languages.
Automation for the Software development Life Cycle
We investigate and develop state of the art methods and tools to support the automation of the software development life cycle. Our methods aim at automating continues integration and deployment activities. The core research activities of this line involve the application of virtual collaboration tools in software engineering, traceability engineering, and test automation.
Virtual Software Engineering Lab
The Virtual Software Engineering Lab provides the technical equipment to investigates the application of research prototypes developed at the SWS group in real world context. The lab has an interactive projector and diverse touch devices for evaluating new modelling languages, collaborative methods, or flexible modelling tools. To facilitate virtuality and its research in software engineering, the lab integrates a double robot, Microsoft HoloLens and Google Glass, and drones. Diverse equipment for empirical software engineering like microphones and cameras is also available.
Projects
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DOSSMA – Detection of Suspicious Social Media Activities
The DOSSMA project will investigate suspicious and malicious behaviour on social media platforms. In a first phase, we will compile an extensive survey report on the areas that are currently being researched, including the respective state-of-the-art, existing solutions and initiatives. This report will serve as a ...
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ARIES: Exploiting User Journeys for Supporting Mobility as a Service Platforms
Emerging Mobility As A Services (MAAS) are pushing the boundaries of DevOps practices and processes, with new challenges to handle for both practitioners and researchers. MAAS providers such as BOND (Bike ON Demand start-up in Switzerland) employ DevOps innovations to sustain the evolution of future MAAS services ...
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Speech-to-Text for Swiss German
Student projects
- Google Glass App
- AirTraffic LIVE
- AirTraffic Worldwide
- Blue Marble
Publications
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Benites de Azevedo e Souza, Fernando; Hürlimann, Manuela; von Däniken, Pius; Cieliebak, Mark,
2020.
ZHAW-InIT : social media geolocation at VarDial 2020 [paper].
In:
Zampieri, Marcos; Nakov, Preslav; Ljubešić, Nikola; Tiedemann, Jörg; Scherrer, Yves, eds.,
Proceedings of the 7th Workshop on NLP for Similar Languages, Varieties and Dialects.
Workshop on NLP for Similar Languages, Varieties and Dialects, Barcelona (Spain), online, 13 December 2020.
International Committee on Computational Linguistics (ICCL).
pp.254-264.
Available from: https://doi.org/10.21256/zhaw-21551
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Tuggener, Lukas; Amirian, Mohammadreza; Benites de Azevedo e Souza, Fernando; von Däniken, Pius; Gupta, Prakhar; Schilling, Frank-Peter; Stadelmann, Thilo,
2020.
Design patterns for resource-constrained automated deep-learning methods.
AI.
1(4),
pp.510-538.
Available from: https://doi.org/10.3390/ai1040031
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Deriu, Jan Milan; Tuggener, Don; von Däniken, Pius; Campos, Jon Ander; Rodrigo, Alvaro; Belkacem, Thiziri; Soroa, Aitor; Agirre, Eneko; Cieliebak, Mark,
2020.
In:
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP).
Conference on Empirical Methods in Natural Language Processing (EMNLP), Online, 16-20 November 2020.
Association for Computational Linguistics.
pp.3971-3984.
Available from: https://doi.org/10.18653/v1/2020.emnlp-main.326
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Di Sorbo, Andrea; Grano, Giovanni; Visaggio, Corrado Aaron; Panichella, Sebastiano,
2020.
Investigating the criticality of user‐reported issues through their relations with app rating.
Journal of Software: Evolution and Process.
Available from: https://doi.org/10.1002/smr.2316
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Panichella, Sebastiano; Zaugg, Nik,
2020.
An empirical investigation of relevant changes and automation needs in modern code review.
Empirical Software Engineering.
25(6),
pp.4833-4872.
Available from: https://doi.org/10.1007/s10664-020-09870-3