Mag. Michael Moser

Area Manager Software Science

Telefon: +43 50 343 814

michael.moser@scch.at

Publikationen

2023
Iterative Design and Evaluation of a Low-Code Development Platform for Welding Robot Control

Schenkenfelder, B., Moser, M., Pfeiffer, M., Pichler, J., Salomon, C., & Winterer, M. (2023). Iterative Design and Evaluation of a Low-Code Development Platform for Welding Robot Control. 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA).
Leveraging and Evaluating Automatic Code Summarization for JPA Program Comprehension

Mayer, R., Moser, M., & Geist, V. (2023). Leveraging and Evaluating Automatic Code Summarization for JPA Program Comprehension. 2023 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER).
2022
On the Creation and Maintenance of a Documentation Generator in an Applied Research Context

Dorninger, B., Moser, M., Pichler, J., Rappl, M., & Sautter, J. (2022). On the Creation and Maintenance of a Documentation Generator in an Applied Research Context. Database and Expert Systems Applications - DEXA 2022 Workshops, 129–140.
Towards Attribute Grammar Mining by Symbolic Execution

Moser, M., Pichler, J., & Pointner, A. (2022). Towards Attribute Grammar Mining by Symbolic Execution. 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER).
2021
eknows: Platform for Multi-Language Reverse Engineering and Documentation Generation

Moser, M., & Pichler, J. (2021). eknows: Platform for Multi-Language Reverse Engineering and Documentation Generation. 2021 IEEE International Conference on Software Maintenance and Evolution (ICSME).
2020
Leveraging machine learning for software redocumentation – A eomprehensive comparison of methods in practice

Geist, V., Moser, M., Pichler, J., Santos, R., & Wieser, V. (2020). Leveraging machine learning for software redocumentation—A comprehensive comparison of methods in practice. Software: Practice and Experience, 51(4), 798–823. Portico.
Stepwise abstraction of high-level system specifications from source code

Ferrarotti, F., Moser, M., & Pichler, J. (2020). Stepwise abstraction of high-level system specifications from source code. Journal of Computer Languages, 60, 100996.
An early investigation of unit testing practices of component-based software systems

Buchgeher, G., Fischer, S., Moser, M., & Pichler, J. (2020). An Early Investigation of Unit Testing Practices of Component-Based Software Systems. 2020 IEEE Workshop on Validation, Analysis and Evolution of Software Tests (VST).
An integrated approach for power transformer modeling and manufacturing

Lettner, C., Moser, M., & Pichler, J. (2020). An integrated approach for power transformer modeling and manufacturing. Procedia Manufacturing, 42, 351–355.
Leveraging machine learning for software redocumentation

Geist, V., Moser, M., Pichler, J., Beyer, S., & Pinzger, M. (2020). Leveraging Machine Learning for Software Redocumentation. 2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER).
2019
Improving quality of data exchange files. An industrial case study

Fleck, G., Moser, M., & Pichler, J. (2019). Improving Quality of Data Exchange Files. An Industrial Case Study. Lecture Notes in Computer Science, 161–175.
Extracting high-level system specifications from source code via abstract state machines

Ferrarotti, F., Pichler, J., Moser, M., & Buchgeher, G. (2019). Extracting High-Level System Specifications from Source Code via Abstract State Machines. Lecture Notes in Computer Science, 267–283.
Deriving an optimal noise adding mechanism for privacy-preserving machine learning.

Kumar, M., Rossbory, M., Moser, B. A., & Freudenthaler, B. (2019). Deriving an Optimal Noise Adding Mechanism for Privacy-Preserving Machine Learning. Database and Expert Systems Applications, 108–118.