Markus Schnappinger

msg Research

Robert-Bürkle-Straße 1

85737 Ismaning near Munich

GERMANY

In 2023, I joined msg Research, a cross-cutting department of the msg group that focuses both on innovation projects and advanced education, as well as engaging in consulting and customer projects.

Between 2018 and 2023 I worked as a Research Associate and PhD student at the Chair of Software and Systems Engineering of Prof. Pretschner at the Technical University of Munich. My dissertation “On Machine Learning Assisted Software Maintainability Assessments” is concerned with expert analyses of large software systems and how machine learning techniques can help identify problematic source code.

Prior to joining the chair, I studied Software Engineering in an elite graduate program hosted by the TU Munich in cooperation with the Ludwig-Maximilians University Munich and the University of Augsburg. These studies included stays at Capgemini and Lero - the Irish Software Research Institute. I am also an alumnus of the German Academic Scholarship Foundation (Studienstiftung des deutschen Volkes), the Elite Network of Bavaria (Elitenetzwerk Bayern) as well as the Lothar and Sigrid Rohde-Foundation. I am also a certified Professional Scrum Master (PSM I). I

Research Interests

My main area of research is Software Quality. In summary, I am interested in i) doing things right in the first place and ii) assessing the quality of created artifacts.

Software quality is viewpoint-specific, multi-dimensional and an extensive research field. The aspects I am most interested in include:

Software maintainability and its assessment: This includes analyzing source code or designs for their comprehensibility, readability, adequate scoping and other attributes.
Regression test selection: This discipline is concerned with selecting a subset of test cases from a large test suite to reduce the cost and time of testing while still finding all bugs.
Requirements Engineering: Arguably, high-quality software satisfies its stakeholders' needs. However, eliciting, modeling, validating and managing requirements is not trivial, especially in agile development processes.

In the longshot, my goal is to establish software quality analyses that are fast, cheap, reliable and require only little human expert interaction. Still, I strongly believe that final conclusions about the state of a system have to remain in the hands of experienced engineers due to the complexity of the system’s context.

Updates

Mar 28, 2023	Today was my last working day at TUM. While I enjoyed every day at the Chair of Software and Systems Engineering and will certainly miss all my colleagues there, I am now looking forward to the new chapter at msg Research!

Selected Publications

Human-Level Ordinal Maintainability Prediction Based on Static Code Metrics

Markus Schnappinger, Arnaud Fietzke, and Alexander Pretschner

In International Conference on Evaluation and Assessment in Software Engineering (EASE), 2021

Bib

@incollection{schnappinger2021human,
  title = {Human-Level Ordinal Maintainability Prediction Based on Static Code Metrics},
  author = {Schnappinger, Markus and Fietzke, Arnaud and Pretschner, Alexander},
  booktitle = {International Conference on Evaluation and Assessment in Software Engineering (EASE)},
  pages = {160--169},
  publisher = {ACM},
  year = {2021},
}

Software quality assessment in practice: a hypothesis-driven framework

Markus Schnappinger, Mohd Hafeez Osman, Alexander Pretschner, and 2 more authors

In Proceedings of the 12th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM), 2018

Bib

@inproceedings{schnappinger2018software,
  title = {Software quality assessment in practice: a hypothesis-driven framework},
  author = {Schnappinger, Markus and Osman, Mohd Hafeez and Pretschner, Alexander and Pizka, Markus and Fietzke, Arnaud},
  booktitle = {Proceedings of the 12th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)},
  pages = {40},
  year = {2018},
  organization = {ACM},
}

Defining a Software Maintainability Dataset: Collecting, Aggregating and Analysing Expert Evaluations of Software Maintainability

Markus Schnappinger, Arnaud Fietzke, and Alexander Pretschner

In 2020 IEEE International Conference on Software Maintenance and Evolution (ICSME), 2020

Bib

@inproceedings{schnappinger2020defining,
  title = {Defining a Software Maintainability Dataset: Collecting, Aggregating and Analysing Expert Evaluations of Software Maintainability},
  author = {Schnappinger, Markus and Fietzke, Arnaud and Pretschner, Alexander},
  booktitle = {2020 IEEE International Conference on Software Maintenance and Evolution (ICSME)},
  pages = {278--289},
  year = {2020},
  organization = {IEEE},
}