I have spoken at conferences and events worldwide, sharing insights on software engineering, probabilistic modeling, and automated code analysis. With over seven years of teaching experience at Johannes Kepler University Linz, I have guided hundreds of computer science students, helping them develop a deep understanding of software reliability, AI-driven analysis, and modern programming paradigms. My research and talks focus on leveraging probabilistic models to enhance software comprehension, fault detection, and semantic analysis.
2022 25th European Joint Conferences on Theory & Practice of Software (ETAPS), Munich, Bavaria, Germany
Probabilistic Software Modeling enables the detection of semantically equivalent code elements by analyzing program behavior probabilistically. This approach improves code similarity analysis, enhances refactoring opportunities, and aids in detecting redundant or duplicate logic with greater accuracy.
2020 IEEE 14th International Workshop on Software Clones (IWSC), London, ON, Canada
Probabilistic Software Modeling enables the detection of semantically equivalent code elements by analyzing program behavior probabilistically (early concepts and findings).
2020 IEEE 3rd International Workshop on Validation, Analysis, and Evolution of Software Tests (VST), London, ON, Canada
Fault Localization via Probabilistic Software Modeling (FL-PSM) enhances debugging accuracy by analyzing software behavior probabilistically. This approach improves fault detection, reduces false positives, and provides deeper insights for developers, making debugging more efficient and precise.
2019 IEEE 26th International Conference on Software Analysis, Evolution and Reengineering (SANER), Hangzhou, China
Feature Maps provide structured, human- and machine-interpretable representations of software, enabling more effective design pattern detection. Leveraging machine learning techniques such as Random Forests and Convolutional Neural Networks enhances both accuracy and interpretability in software analysis, offering deeper insights into code structure and behavior.
2018 ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA), Amsterdam, 2018, ECOOP and ISSTA Doc Symposium
Probabilistic Software Modeling introduces a novel approach to understanding and predicting software behavior by transforming programs into probabilistic models. It leverages probabilistic inference and machine learning to enhance fault detection, semantic analysis, and automated decision-making, offering new possibilities for improving software reliability and intelligence.
2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Limassol, Cyprus
The impact of code cloning in Programmable Logic Controller (PLC) software, particularly in IEC 61131-3 Structured Text and C/C++, is examined through key findings on clone prevalence, detection challenges, and effective management strategies. Insights highlight duplication risks, maintainability issues, and practical approaches to improving software quality and reliability in industrial automation.
2019 Institute for System Software (SSW), Johannes Kepler University Linz, Austria
At Johannes Kepler University Linz, the Software Development 1 Exercise Track provides students with practical experience in software development. Covering object-oriented programming, concurrency, and programming language grammar construction, it equips students with essential coding and problem-solving skills for building robust software systems.
2018 Institute for Software Systems Engineering (ISSE), Johannes Kepler University Linz, Austria
The Seminar in Software Engineering at Johannes Kepler University Linz allows students to delve into advanced topics like software architecture, quality, evolution, and maintenance. It provides a platform to enhance knowledge and skills, preparing students for complex challenges in modern software development.
2017 Institute for Software Systems Engineering (ISSE), Johannes Kepler University Linz, Austria
The Software Engineering Exercise Track at Johannes Kepler University Linz provides practical experience in requirements engineering, design, implementation, testing, and maintenance. Students apply theoretical knowledge to real-world projects, gaining valuable insights into software development processes.
2017 Institute for Software Systems Engineering (ISSE), Johannes Kepler University Linz, Austria
The Model-Driven Software Development course at Johannes Kepler University Linz teaches model-driven engineering principles. Covering modeling languages, transformations, code generation, and model-based testing, it equips students with the skills to develop software systems using model-driven approaches and tools.