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.
As part of the reorganization of the research database, the previous lists of research projects are no longer available. Die Zukunft geht in Richtung Volltextsuche und Filterung, um bestmögliche Suchergebnisse für unsere Besucher:innen zur Verfügung zu stellen.
In the meantime, you can easily find the projects via text search using the following link: «To the new search in the project database»
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Mosquera, David; Ruiz, Marcela; Pastor, Oscar; Spielberger, Jürgen,
2022.
Assisted-modeling requirements for model-driven development tools [paper].
In:
Guizzardi, Renata; Ralyté, Jolita; Franch, Xavier, eds.,
Research Challenges in Information Science.
16th International Conference on Research Challenges in Information Science (RCIS), Barcelona, Spain, 17-20 May 2022.
Cham:
Springer.
pp. 458-474.
Lecture Notes in Business Information Processing ; 446.
Available from: https://doi.org/10.1007/978-3-031-05760-1_27
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Mosquera, David; Martakos, Anastassios; Ruiz, Marcela,
2022.
In:
Augusto, Adriano; Gill, Asif; Bork, Dominik; Nurcan, Selmin; Reinhartz-Berger, Iris; Schmidt, Rainer, eds.,
Enterprise, Business-Process and Information Systems Modeling.
27th International Conference on Exploring Modeling Methods for Systems Analysis and Development (EMMSAD), Leuven, Belgium, 6-7 June 2022.
Cham:
Springer.
pp. 336-343.
Lecture Notes in Business Information Processing ; 450.
Available from: https://doi.org/10.1007/978-3-031-07475-2_23
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2022.
Machine learning for mathematical modelling of Piezo hysteresis [paper].
In:
MikroSystemTechnik Congress 2021 : Proceedings.
MikroSystemTechnik Congress, Ludwigsburg, Germany, 8-10 November 2021.
Berlin:
VDE.
pp. 170-173.
Available from: https://ieeexplore.ieee.org/document/9698304
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Zampetti, Fiorella; Kapur, Ritu; Di Penta, Massimiliano; Panichella, Sebastiano,
2022.
An empirical characterization of software bugs in open-source Cyber–Physical Systems.
Journal of Systems and Software.
192(111425).
Available from: https://doi.org/10.1016/j.jss.2022.111425
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Di Sorbo, Andrea; Zampetti, Fiorella; Visaggio, Corrado A.; Di Penta, Massimiliano; Panichella, Sebastiano,
2022.
ACM Transactions on Software Engineering and Methodology.
32(3), pp. 67.
Available from: https://doi.org/10.1145/3564821