Termin in Kalender importieren: iCal (Download)
Vorträge
| Vortragende(r)
|
Anne-Kathrin Hermann
|
| Titel
|
Low-Code in der Sichtenbasierten Entwicklung
|
| Vortragstyp
|
Vortrag
|
| Betreuer(in)
|
Lars König
|
| Vortragssprache
|
Englisch
|
| Vortragsmodus
|
in Präsenz
|
| Kurzfassung
|
In recent years, low-code development has been established as an innovative method for software development. It enables the development of a wide range of applications using graphical tools, with little or no knowledge of text-based programming languages. Closely related is model-driven development, where models play a primary role in specifying software systems and generating code partially automatically. While model-driven development supports development processes where developers from different domains work on different models that are kept consistent, in practice, classical model-driven tools are often difficult to use for domain experts with a less technical background. To bridge this gap, we propose a concept for integrating low-code platforms through projective views into model-driven development environments. We provide an initial evaluation of the feasibility of our concept using a development platform for smart home systems as a case study.
|
| Vortragende(r)
|
Alexander Milster
|
| Titel
|
Multi-Language and Cross-Language Software Plagiarism Detection
|
| Vortragstyp
|
Bachelorarbeit
|
| Betreuer(in)
|
Robin Maisch
|
| Vortragssprache
|
Deutsch
|
| Vortragsmodus
|
in Präsenz
|
| Kurzfassung
|
Currently, commonly used plagiarism detection tools can only handle code from one language for a single run.
This thesis deals with two different sub-problems. Firstly, parsing and comparing the code of each occurring language in a single submission set separately (multi-language plagiarism detection) and, secondly, comparing submissions as a whole, despite containing code from multiple languages (cross-language plagiarism detection).
In this thesis, we propose supporting multi-language plagiarism detection by concatenating
the token lists. For cross-language plagiarism detection, we propose a set of language-agnostic tokens and rules for the order they should be extracted in, which have to be implemented for each supported language. In addition, a dynamic approach that allows more flexible matching of tokens is considered.
|
- Neuen Vortrag erstellen
Hinweise
