Software Engineering
We Transform Ideas into Software
Fast societal, economic, and technological digital transformation demand a quick pace in developing and maintaining software systems. Therefore, our mission at the Software Engineering (SWE) research group is to develop novel methods and tools to ensure rapid software development of high-quality software products. As experts in empirical software engineering, we ensure the successful technology transfer of our research products for and to industry. Among other things, we address research questions such as:
- How to leverage Low-Code/No-Code tools to lower the entry barrier of software development for experts without coding knowledge?
- How to identify reusable use cases to reduce the effort of generating software?
- How to improve software quality and maintenance effort by means of automatic transformations of requirements into code and test cases?
- How to automatically generate traceability links between software requirements, code, and test cases for software development monitoring and quality assurance?
- How can phases of the software development life cycle be automated?
- Which methods can improve continuous integration (CI) and continuous deployment (CD) for sustainable software development??
- Can Virtual Reality tools help to enhance agile software development and collaboration?
- How to automate the generation of complete and high-quality test cases?
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, which integrates students from other engineering programs like avionics and mechanical engineering.
Automated Software Generation
The topic of Automated Software Generation covers the design, development, and analysis of low-code/no-code Tools for 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.
We investigate how low-code/no-code Tools can 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 low-code/no-code tools and Model-Driven Engineering methods 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 continuous 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 SWE group in real world use cases. 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, Google Glass, and drones. Diverse equipment for empirical software engineering like microphones and cameras is also available.
Unfortunately, no list of projects can be displayed here at the moment. Until the list is available again, the project search on the ZHAW homepage can be used.
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Deriu, Jan Milan; Cieliebak, Mark,
2017.
In:
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017).
SemEval 2017 - International Workshop on Semantic Evaluation, Vancouver, Canada, 3-4 August 2017.
Association for Computational Linguistics.
pp. 334-338.
Available from: https://doi.org/10.18653/v1/S17-2054
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Müller, Simon; Huonder, Tobias; Deriu, Jan Milan; Cieliebak, Mark,
2017.
In:
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017).
11th International Workshop on Semantic Evaluation, Vancouver, Canada, 3-4 August 2017.
Association for Computational Linguistics.
pp. 766-771.
Available from: https://doi.org/10.21256/zhaw-1529
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von Däniken, Pius; Cieliebak, Mark,
2017.
Transfer learning and sentence level features for named entity recognition on tweets [paper].
In:
Proceedings of the 3rd Workshop on Noisy User-generated Text.
3rd Workshop on Noisy User-generated Text (W-NUT), Copenhagen, Denmark, 7 September 2017.
Association for Computational Linguistics.
pp. 166-171.
Available from: https://doi.org/10.21256/zhaw-1528
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Meier, Andreas; Kropp, Martin,
2016.
From SAS to SARN : the Swiss Agile Research Network.
In:
Lean Agile Scrum Conference, SwissICT, Zürich, 13 September 2016.
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Biddle, Robert; Kropp, Martin; Meier, Andreas,
2016.
Agile adolescence to maturity : experience leads to collaboration (Workshop).
In:
OOP Conference 2016, Munich, Germany, 2016.