Lehrstuhl für Angewandte Softwaretechnik
Chair for Applied Software Engineering

Bachelor Theses

Bachelorthesis
TBD
Advisor
Dominic Henze
Author
Philipp Eichstetter
Date
15.02.2020

 

Bachelor or Master Theses

Bachelorthesis
TBD
Advisor
Dominic Henze
Author
Philipp Eichstetter
Date
15.02.2020
Masterthesis / Bachelorthesis / Guided Research
Serverless Swift Deployment
Advisor
Author
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Date
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The goal of the thesis should be an evaluation of different deployment strategies in serverless server architectures. One area of interest is the decomposition a declarative Server-Side Swift framework into functional segments that could be individually deployed and how the components must be orchestrated so they can communicate with each other. Reach out to me via email if you are interested in the thesis or related components that could support the development of such a system. Your email should contain information about your previous Swift and server-side programming experience and a short proposal of a possible approach you would like to take.
Masterthesis / Bachelorthesis / Guided Research
A Declarative Server-Side Swift Framework
Advisor
Author
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Date
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  The goal of the thesis should be an evaluation of declarative frameworks in Swift and the implementation of a Server-Side Swift framework based on the conducted research. The framework should build on top of Swift NIO and should be able to run on Apple platforms as well as Linux. Reach out to me via email if you are interested in the thesis or related Swift frameworks that could support the development of such a system. Your email should contain information about your previous Swift and server-side programming experience and a short proposal of a possible approach you would like to take.
Masterthesis 
/ Bachelorthesis / Guided Research
Learning Deployment Strategies
Advisor
Author
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Date
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  The goal of the thesis should be the evaluation of current research about machine learning techniques for deployment strategies and the creation of a prototype implementation. The system should continuously learn the users' behavior and generate deployment rules using machine learning techniques. Reach out to me via email if you are interested in the thesis or related components that could support the development of such a system. Your email should contain information about your previous Swift and server-side programming experience and a short proposal of a possible approach you would like to take.
Masterthesis / Bachelorthesis
Step-wise exercises with interactive help tutorials in ArTEMiS
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Author
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Many exercises include multiple parts that depend on each other. Then it is impossible, difficult and/or demotivating for students to continue with the 2nd or 3rd part if they were not able to solve the 1st part. It is also misleading if the 1st part is finished and the student gets the feedback that e.g. 8 out of 12 test cases still fail. In this thesis, you will extend ArTEMiS so that instructors can easily add multiple parts for exercises. In addition, ArTEMiS should allow student to receive automatic help in form of live tutorials for exercise parts that they don't understand or cannot solve. While they cannot obtain the full points any more, they can work on the other parts as well and learn the system and the theory behind the concept through interactive live tutorials (comparable to an on-boarding in a mobile app). The thesis should also evaluate if these improvements help and motivate students to achieve a better learning experience. ArTEMiS is open source and available on https://github.com/ls1intum/ArTEMiS

 

Master Theses

Master's Thesis
Automatic Maintenance of Yachts using Machine Learning and Robotics
Advisor
Sajjad Taheri
Author
-
Date
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  The goal of this thesis is to build a semi-automatic system consisting of a mobile platform and an industrial robot to assist the process of maintaining the yachts. It must recognize the shape of the 3D surface, and decide which tool and robotic movement should be used for processing the surface, depending on the type of damage or dirt. The thesis built be done on top of a prototype which was done during our practical course in summer 2019. It includes improving the machine learning model to detect the damages and dirts, port the path planning C++ code into Python, and enable the system to work on mobile platforms.
Masterthesis
Extension of Programming Exercise in ArTEMiS
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Author
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Date
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Extension of Semi-Automatic Grading of Modeling Exercises in ArTEMiS (https://artemis.ase.in.tum.de) --> https://github.com/ls1intum/ArTEMiS