@inproceedings{KieslerScholzAlbrechtetal.2024, author = {Kiesler, Natalie and Scholz, Ingo and Albrecht, Jens and Stappert, Friedhelm and Wienkop, Uwe}, title = {Novice Learners of Programming and Generative AI - Prior Knowledge Matters}, series = {Proceedings of the 24th Koli Calling International Conference on Computing Education Research}, booktitle = {Proceedings of the 24th Koli Calling International Conference on Computing Education Research}, publisher = {ACM}, address = {New York, NY, USA}, doi = {10.1145/3699538.3699580}, pages = {1 -- 2}, year = {2024}, abstract = {With the broad availability of Generative AI (GenAI), introductory programming education is starting to change. At Nuremberg Tech, we observed the doubling of failure rates to approximately 50\% in the first semester course "Procedural Programming" across students of all study programs. Due to these exam results in winter 2023/24, we conducted a pilot study to gather students' use of GenAI tools, their exam results, and prior programming education and experience. The results imply significant differences of students' use of GenAI tools depending on their prior programming education. We will therefore extend the investigation in winter term 2024/25.}, language = {en} } @inproceedings{WaegemannLangerMottoketal.2016, author = {W{\"a}gemann, Tobias and Langer, Tobias and Mottok, J{\"u}rgen and Osinski, Lukas and Stappert, Friedhelm and Tavakoli Kolagari, Ramin}, title = {Models for Dependable Heterogenous Multi- and Many-Core System Software Design Revisited}, series = {29th International Conference on Architecture of Computing Systems}, booktitle = {29th International Conference on Architecture of Computing Systems}, year = {2016}, language = {en} } @article{AltenberndGustafssonLisperetal.2016, author = {Altenbernd, Peter and Gustafsson, Jan and Lisper, Bj{\"o}rn and Stappert, Friedhelm}, title = {Early execution time-estimation through automatically generated timing models}, series = {Real-Time Systems}, volume = {52}, journal = {Real-Time Systems}, number = {6}, publisher = {Springer Science and Business Media LLC}, issn = {0922-6443}, doi = {10.1007/s11241-016-9250-7}, pages = {731 -- 760}, year = {2016}, abstract = {Traditional timing analysis, such as worst-case execution time analysis, is normally applied only in the late stages of embedded system software development, when the hardware is available and the code is compiled and linked. However, preliminary timing estimates are often needed in early stages of system development as an essential prerequisite for the configuration of the hardware setup and dimensioning of the system. During this phase the hardware is often not available, and the code might not be ready to link. This article describes an approach to predict the execution time of software through an early, source-level timing analysis. A timing model for source code is automatically derived from a given combination of hardware architecture and compiler. The model is identified from measured execution times for a set of synthetic training programs, compiled for the hardware platform in question. It can be used to estimate the execution time for code running on the platform: the estimation is then done directly from the source code, without compiling and running it. Our experiments show that, using this model, we can predict the execution times of the final, compiled code surprisingly well. For instance, we achieve an average deviation of 8\% for a set of benchmark programs for the ARM7 architecture.}, language = {en} } @techreport{Stappert2026, author = {Stappert, Friedhelm}, title = {On the Examination Timetabling Problem at TH N{\"u}rnberg, Dept. of Computer Science}, doi = {10.34646/thn/ohmdok-4690}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:92-opus4-46904}, pages = {26}, year = {2026}, abstract = {This report examines the Examination Timetabling Problem (ETP) at the Department of Computer Science (IN) at Technische Hochschule N{\"u}rnberg (THN), focusing on the specific constraints and challenges of the institution. The report surveys various algorithms and approaches applied to solve the ETP. The Step Counting Hill Climbing (SCHC) algorithm, originally proposed by Bykov and Petrovic, is highlighted as a particularly effective solution. The report details the implementation and enhancements of the SCHC algorithm at IN, which has been successfully applied to the department's timetabling needs. Experimental results demonstrate that the SCHC algorithm, with its simplicity and efficiency, produces high-quality timetables within minutes, comparable to manually created schedules. The report also discusses the limitations of integer linear programming for real-world ETPs due to its exponential complexity. The findings suggest that the SCHC algorithm is well-suited for the ETP at IN, with potential for further optimisation to improve speed and solution quality.}, language = {en} }