Software Engineering
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 Engineering (SWE) research group of the InIT 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 Continuous 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 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 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
-
Green and sustainable digitalization for the textile industry
By optimizing production in the textile industry, digitalization can help to reduce power consumption and thus, emissions of pollutants. Yet, digitalization itself creates emissions, e.g., by using powerful AI algorithms. There is currently no transparency for how digitalization investments can reduce emissions. The ...
-
Smart Hospital – Integrated Framework, Tools & Solutions (SHIFT)
-
Machine Learning for Software User Interface Testing
In this project, various technical aspects for tracing functional/non-functional requirements within user interface test cases were investigated. Originally, this project aimed to detect bugs in user interfaces automatically by using machine learning algorithms. During the execution of the project, we decided to ...
Student projects
- Google Glass App
- AirTraffic LIVE
- AirTraffic Worldwide
- Blue Marble
Publications
-
Kropp, Martin; Meier, Andreas; Anslow, Craig; Biddle, Robert,
2020.
Satisfaction and its correlates in agile software development.
Journal of Systems and Software.
164, pp. 110544.
Available from: https://doi.org/10.1016/j.jss.2020.110544
-
Ashraf, Usman; Mayr-Dorn, Christoph; Egyed, Alexander; Panichella, Sebastiano,
2020.
A mixed graph-relational dataset of socio-technical interactions in open source systems [paper].
In:
Proceedings of the 17th International Conference on Mining Software Repositories.
MSR '20: 17th International Conference on Mining Software Repositories, Seoul, South Korea, June 2020.
Association for Computing Machinery.
pp. 538-542.
Available from: https://doi.org/10.1145/3379597.3387492
-
Azeem, Muhammad Ilyas; Panichella, Sebastiano; Di Sorbo, Andrea; Serebrenik, Alexander; Wang, Qing,
2020.
Action-based recommendation in pull-request development [paper].
In:
Proceedings of the International Conference on Software and System Processes.
ICSSP '20: International Conference on Software and System Processes, Seoul, South Korea, June 2020.
Association for Computing Machinery.
pp. 115-124.
Available from: https://doi.org/10.1145/3379177.3388904
-
Ulasik, Malgorzata Anna; Hürlimann, Manuela; Germann, Fabian; Gedik, Esin; Benites de Azevedo e Souza, Fernando; Cieliebak, Mark,
2020.
CEASR : a corpus for evaluating automatic speech recognition [paper].
In:
Calzolari, Nicoletta; Béchet, Frédéric; Blache, Philippe; Choukri, Khalid; Cieri, Christopher; Declerck, Thierry; Goggi, Sara; Isahara, Hitoshi; Maegaard, Bente; Mariani, Joseph; Mazo, Hélène; Moreno, Asuncion; Odijk, Jan; Piperidis, Stelios, eds.,
Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020).
12th Language Resources and Evaluation Conference (LREC), Marseille, France, 11-16 May 2020.
European Language Resources Association.
pp. 6477-6485.
Available from: https://doi.org/10.21256/zhaw-20125
-
Roy, Devjeet; Zhang, Ziyi; Ma, Maggie; Arnaoudova, Venera; Panichella, Annibale; Panichella, Sebastiano; Gonzalez, Danielle; Mirakhorli, Mehdi,
2020.
DeepTC-Enhancer : improving the readability of automatically generated tests [paper].
In:
Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering.
35th IEEE/ACM International Conference on Automated Software Engineering (ASE), Virtual Event, 21-25 September 2020.
ACM.
pp. 287-298.
Available from: https://doi.org/10.1145/3324884.3416622