Software quality assessment in practice: a hypothesis-driven framework. - Markus Schnappinger; Mohd Hafeez Osman; Alexander Pretschner; Markus Pizka; Arnaud Fietzke (ESEM, 2018)

Learning a classifier for prediction of maintainability based on static analysis tools. - Markus Schnappinger; Mohd Hafeez Osman; Alexander Pretschner; Arnaud Fietzke (ICPC, 2019)

Defining a Software Maintainability Dataset: Collecting, Aggregating and Analysing Expert Evaluations of Software Maintainability. - Markus Schnappinger; Arnaud Fietzke; Alexander Pretschner (ICSME, 2020)

Human-level Ordinal Maintainability Prediction Based on Static Code Metrics. - Markus Schnappinger; Arnaud Fietzke; Alexander Pretschner (EASE, 2021)

Efficient Platform Migration of a Mainframe Legacy System Using Custom Transpilation. - Markus Schnappinger; Jonathan Streit (ICSME, 2021)

Probe-based Syscall Tracing for Efficient and Practical File-level Test Traces. - Daniel Elsner; Roland Wuersching; Markus Schnappinger; Alexander Pretschner (AST@ICSE, 2022)

Build System Aware Multi-language Regression Test Selection in Continuous Integration. - Daniel Elsner; Roland Wuersching; Markus Schnappinger; Alexander Pretschner; Maria Graber; René Dammer; Silke Reimer (ICSE (SEIP), 2022)

A Preliminary Study on Using Text- and Image-Based Machine Learning to Predict Software Maintainability. - Markus Schnappinger; Simon Zachau; Arnaud Fietzke; Alexander Pretschner (SWQD, 2022)

Revisiting Inter-Class Maintainability Indicators. - Lena Gregor; Markus Schnappinger; Alexander Pretschner (SANER, 2023)

On Machine Learning Assisted Software Maintainability Assessments. - Markus Schnappinger (2023)