Research Challenges of Industry 4.0 for Quality Management. - Harald Foidl; Michael Felderer (ERP Future, 2015)

Data Science Challenges to Improve Quality Assurance of Internet of Things Applications. - Harald Foidl; Michael Felderer (ISoLA (2), 2016)

Integrating software quality models into risk-based testing. - Harald Foidl; Michael Felderer (Softw. Qual. J., 2018)

Technical Debt in Data-Intensive Software Systems. - Harald Foidl; Michael Felderer; Stefan Biffl (SEAA, 2019)

Risk-based data validation in machine learning-based software systems. - Harald Foidl; Michael Felderer (MaLTeSQuE@ESEC/SIGSOFT FSE, 2019)

Data smells: categories, causes and consequences, and detection of suspicious data in AI-based systems. - Harald Foidl; Michael Felderer; Rudolf Ramler (CAIN, 2022)

Preliminary findings on the occurrence and causes of data smells in a real-world business travel data processing pipeline. - Valentina Golendukhina; Harald Foidl; Michael Felderer; Rudolf Ramler (SEA4DQ@ESEC/SIGSOFT FSE, 2022)

An approach for assessing industrial IoT data sources to determine their data trustworthiness. - Harald Foidl; Michael Felderer (Internet Things, 2023)

Data pipeline quality: Influencing factors, root causes of data-related issues, and processing problem areas for developers. - Harald Foidl; Valentina Golendukhina; Rudolf Ramler; Michael Felderer (J. Syst. Softw., 2024)

A Catalog of Consumer IoT Device Characteristics for Data Quality Estimation. - Valentina Golendukhina; Harald Foidl; Daniel Hörl; Michael Felderer (ACM J. Data Inf. Qual., 2024)