In this thesis simulation environments for self-driving cars are analyzed and scenarios are implmented to test self-driving cars. The simulation scenarios serve as a Digital Twin for a self-driving robot and both, the simulation and the robotic environment, are used to train pupils and practitioners on the integration of AI components into systems.
Um Verhalten und Bewegungen, Bearbeitungsdauer von CNC-Maschinen mit der vorhandenen HMI zu simulieren, muss ein digitaler Zwilling der Maschine benutzt werden. Im Rahmen dieser Bachelorarbeit wird ein Softwaremodell in C# entwickelt, um es mit einem bereits bestehenden Modell und Digitalen Zwilling zu koppeln, mit dem Ziel die Steuerung über C# zu ermöglichen. Das objektorientierte Softwaremodell in C# wird im Rahmen der Arbeit entwickelt, an die bestehende Infrastruktur gekoppelt und evaluiert.
Metamorphic Testing has seen an immense increase in popularity among software engineers and scientists ever since it was first introduced in 1998. It is a software testing technique that focuses on relations between inputs and outputs of a program rather than the inputs and outputs themselves. These relations are referred to as Metamorphic Relations, whose construction is non-trivial and usually requires expertise and domain knowledge. The nature of this strategy facilitates the testing of programs even in the absence of a test oracle. Examples for such programs are search engines, compilers, or simulators, the latter of which will provide the basis for the implementation within this project.
In autonomous systems, it can be extremely difficult to decide whether the behaviour of some autonomous system meets its specifications, hence why applying Metamorphic Testing to this domain should show positive results. Autonomous drones, in particular, are becoming more and more popular for purposes like
surveillance or search operations, while software testing in this field is complex.
The goal of this project is to explore the applicability of Metamorphic Testing in autonomous systems by implementing the technique in respect of testing autonomous drones.
Das Ziel dieser Arbeit ist es einen zentralen Authenifizierungs- und Authorisierungsservice zu entwickeln, dessen Hauptaufgabe es ist, Benutzeridentitäten inklusive Kennwörter zu sichern und zu verwalten.
Über eine Webanwendung sollen Produkte und Benutzer angelegt und bearbeitet werden können. Nachdem ein Benutzer angelegt wurde, soll sich dieser sofort mithilfe des Authenifizierungsservices an den zugewiesenen Produkten anmelden können. Basierend auf standardisierten Protokollen und Konzepten werden Schnittstellen zur Verfügung gestellt, um den Zentralen Authenifizierungs- und Authorisierungsservice mit den angelegten Produkten ansprechen zu können.
Die Bachelorarbeit erfolgt in Zusammenarbeit mit der Firma InfPro.
I have an open PhD position on IoT Testing.
You will be a part of the small team focused on developing testing approaches for different IoT devices. More specifically, your core task will be to build an innovative testbed for drones by actively monitoring the network, sensor and location data. This task will be performed in interconnected real and simulated environments, where multiple IoT devices are collaborating and sharing data.
Further information is available in the job advertisement.
Michael Felderer is PC Co-Chair of TechDebt 2020 collocated with ICSE 2020.
Technical debt describes a universal software development phenomenon: design or implementation constructs that are expedient in the short term but set up a technical context that can make future changes more costly or impossible. Software developers and managers increasingly use the concept to communicate key tradeoffs related to release and quality issues. The goal of this two-day conference is to bring together leading software researchers, practitioners, and tool vendors to explore theoretical and practical techniques that manage technical debt.
The Managing Technical Debt workshop series has provided a forum since 2010 for practitioners and researchers to discuss issues related to technical debt and share emerging practices used in software-development organizations. A week-long Dagstuhl Seminar on Managing Technical Debt in Software Engineering has produced a consensus definition for technical debt, a draft conceptual model, and a research roadmap.
To accelerate progress, an expanded two-day working conference format has become essential. The third edition of the TechDebt Conference will be held jointly with ICSE 2020 in Seoul, South Korea, on May 25-26, 2020. The conference is sponsored by ACM SIGSOFT and IEEE TCSE.
Michael Felderer is General Chair of SE 20 and organizes the conference together with his organization team in Innsbruck from February 24 to 28, 2020. The conference includes several amazing tracks. The website of the conference is available online at https://se20.ocg.at/
Together with Mika Mäntylä and supported by Vahid Garousi and Austen Rainer, Michael Felderer gave a tutorial on Benefitting from Grey Literature in Software Engineering Research at PROFES 2019 in Barcelona.
Description of the Tutorial:
Grey literature is becoming more and more important as a source of knowledge because software engineering practitioners write and share information in different forms of grey literature (GL) like blogs, videos or white papers. The overall goal of this tutorial is to present ways how software engineering research can benefit from the vast amount of information covered by GL. The participants of this tutorial will learn how GL can be used for various aspects of software engineering research, e.g., shaping new directions of research, or using knowledge and evidence from grey literature in empirical studies in software engineering. First, the concept of GL in general and from the perspective of different disciplines like health sciences or social sciences are presented. Second, the concept of GL in software engineering and types of GL are presented and discussed with the participants. Third, ways how GL can be used in primary studies and secondary studies in software engineering are presented. The discussed application scenarios in primary studies comprise analysis of GL materials with a qualitative approach, analysis of GL with a quantitative approach, and reference of GL sources. In secondary studies, GL can be incorporated into multivocal literature reviews and grey literature reviews. The instructors will present their guidelines for these reviews and explore them with the participants of the tutorial. Finally, the challenges and benefits of using GL in software engineering are discussed. The examples presented during the tutorial are from the domains of software processes and software testing. It is sufficient if potential participants are interested in the topic and intend to use grey literature in their empirical studies in software engineering. Knowledge of systematic literature review and empirical studies in software engineering are and advantage but not required. Participants should bring their notebook or tablet to enable participation in the practical part.
On October 29, 2019 Michael Felderer gave a keynote entitled “Gemeinsam sind wir stärker: Empirische Untersuchungen & persönliche Erfahrungen zur erfolgreichen Kooperation zwischen Firmen & Universitäten” covering empirical results and personal experiences on industry academia collaboration at the ASQT in Bolzano.
Link to the event: http://www.asqt.org/
The goal of this thesis is the development of a software prototype that can annotate dangerous sound events. The thesis includes building a pipeline that can detect special such events and developing a Deep Neural Network (DNN) that can classify sound events as dangerous. Furthermore, the pipeline will provide a table-like file (e.g. CSV) which contains for each audio-file an entry with the filename, the probability, the classification and the timestamps (start and end) of the occurred sound-event. The software and thesis are developed in collaboration with MED-EL.
Supervisor: Michael Felderer