Markus Schnappinger

According to our database1, Markus Schnappinger authored at least 11 papers between 2018 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Improving the Quality of GitHub Copilot Generated Unit Tests.
Proceedings of the Software Architecture as the Backbone of Software Quality, 2026

2023
On Machine Learning Assisted Software Maintainability Assessments.
PhD thesis, 2023

Revisiting Inter-Class Maintainability Indicators.
Proceedings of the IEEE International Conference on Software Analysis, 2023

2022
A Preliminary Study on Using Text- and Image-Based Machine Learning to Predict Software Maintainability.
Proceedings of the Software Quality: The Next Big Thing in Software Engineering and Quality, 2022

Build System Aware Multi-language Regression Test Selection in Continuous Integration.
Proceedings of the 44th IEEE/ACM International Conference on Software Engineering: Software Engineering in Practice, 2022

Probe-based Syscall Tracing for Efficient and Practical File-level Test Traces.
Proceedings of the IEEE/ACM International Conference on Automation of Software Test, 2022

2021
Efficient Platform Migration of a Mainframe Legacy System Using Custom Transpilation.
Proceedings of the IEEE International Conference on Software Maintenance and Evolution, 2021

Human-level Ordinal Maintainability Prediction Based on Static Code Metrics.
Proceedings of the EASE 2021: Evaluation and Assessment in Software Engineering, 2021

2020
Defining a Software Maintainability Dataset: Collecting, Aggregating and Analysing Expert Evaluations of Software Maintainability.
Proceedings of the IEEE International Conference on Software Maintenance and Evolution, 2020

2019
Learning a classifier for prediction of maintainability based on static analysis tools.
Proceedings of the 27th International Conference on Program Comprehension, 2019

2018
Software quality assessment in practice: a hypothesis-driven framework.
Proceedings of the 12th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, 2018


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