Self-Tuning Resource Demand Estimation. - Johannes Grohmann; Nikolas Herbst; Simon Spinner; Samuel Kounev (ICAC, 2017)

Using Machine Learning for Recommending Service Demand Estimation Approaches - Position Paper. - Johannes Grohmann; Nikolas Herbst; Simon Spinner; Samuel Kounev (CLOSER, 2018)

The Vision of Self-Aware Performance Models. - Johannes Grohmann; Simon Eismann; Samuel Kounev (ICSA Companion, 2018)

On the Value of Service Demand Estimation for Auto-scaling. - André Bauer 001; Johannes Grohmann; Nikolas Herbst; Samuel Kounev (MMB, 2018)

Blackbox Learning of Parametric Dependencies for Performance Models. - Vanessa Ackermann; Johannes Grohmann; Simon Eismann; Samuel Kounev (MoDELS (Workshops), 2018)

TeaStore: A Micro-Service Reference Application for Cloud Researchers. - Simon Eismann; Jóakim von Kistowski; Johannes Grohmann; André Bauer 001; Norbert Schmitt; Nikolas Herbst; Samuel Kounev (UCC Companion, 2018)

A SPEC RG Cloud Group's Vision on the Performance Challenges of FaaS Cloud Architectures. - Erwin Van Eyk; Alexandru Iosup; Cristina L. Abad; Johannes Grohmann; Simon Eismann (ICPE Companion, 2018)

Tools for Declarative Performance Engineering. - Jürgen Walter; Simon Eismann; Johannes Grohmann; Dusan Okanovic; Samuel Kounev (ICPE Companion, 2018)

How is Performance Addressed in DevOps? A Survey on Industrial Practices. - Cor-Paul Bezemer; Simon Eismann; Vincenzo Ferme; Johannes Grohmann; Robert Heinrich; Pooyan Jamshidi; Weiyi Shang; André van Hoorn; Mónica Villavicencio; Jürgen Walter; Felix Willnecker (CoRR, 2018)

Integrating Statistical Response Time Models in Architectural Performance Models. - Simon Eismann; Johannes Grohmann; Jürgen Walter; Jóakim von Kistowski; Samuel Kounev (ICSA, 2019)

On learning in collective self-adaptive systems: state of practice and a 3D framework. - Mirko D'Angelo; Simos Gerasimou; Sona Ghahremani; Johannes Grohmann; Ingrid Nunes; Evangelos Pournaras; Sven Tomforde (SEAMS@ICSE, 2019)

Detecting Parametric Dependencies for Performance Models Using Feature Selection Techniques. - Johannes Grohmann; Simon Eismann; Sven Elflein; Jóakim von Kistowski; Samuel Kounev; Manar Mazkatli (MASCOTS, 2019)

Monitorless: Predicting Performance Degradation in Cloud Applications with Machine Learning. - Johannes Grohmann; Patrick K. Nicholson; Jesús Omana Iglesias; Samuel Kounev; Diego Lugones (Middleware, 2019)

Systematic Search for Optimal Resource Configurations of Distributed Applications. - André Bauer 001; Simon Eismann; Johannes Grohmann; Nikolas Herbst; Samuel Kounev (FAS*W@SASO/ICAC, 2019)

TeaStore - A Micro-Service Reference Application. - Simon Eismann; Jóakim von Kistowski; Johannes Grohmann; André Bauer 001; Norbert Schmitt; Samuel Kounev (FAS*W@SASO/ICAC, 2019)

Utilizing Clustering to Optimize Resource Demand Estimation Approaches. - Johannes Grohmann; Simon Eismann; André Bauer 001; Marwin Züfle; Nikolas Herbst; Samuel Kounev (FAS*W@SASO/ICAC, 2019)

TeaStore: A Micro-Service Reference Application for Benchmarking, Modeling and Resource Management Research. - Jóakim von Kistowski; Simon Eismann; Norbert Schmitt; André Bauer 001; Johannes Grohmann; Samuel Kounev (SE/SWM, 2019)

How is Performance Addressed in DevOps? - Cor-Paul Bezemer; Simon Eismann; Vincenzo Ferme; Johannes Grohmann; Robert Heinrich; Pooyan Jamshidi; Weiyi Shang; André van Hoorn; Mónica Villavicencio; Jürgen Walter; Felix Willnecker (ICPE, 2019)

TeaStore - A Micro-Service Reference Application for Performance Engineers. - Jóakim von Kistowski; Simon Eismann; Johannes Grohmann; Norbert Schmitt; André Bauer 001; Samuel Kounev (ICPE Companion, 2019)

Predicting Server Power Consumption from Standard Rating Results. - Jóakim von Kistowski; Johannes Grohmann; Norbert Schmitt; Samuel Kounev (ICPE, 2019)

The SPEC-RG Reference Architecture for FaaS: From Microservices and Containers to Serverless Platforms. - Erwin Van Eyk; Alexandru Iosup; Johannes Grohmann; Simon Eismann; André Bauer 001; Laurens Versluis; Lucian Toader; Norbert Schmitt; Nikolas Herbst; Cristina L. Abad (IEEE Internet Comput., 2019)

Online model learning for self-aware computing infrastructures. - Simon Spinner; Johannes Grohmann; Simon Eismann; Samuel Kounev (J. Syst. Softw., 2019)

On Learning Parametric Dependencies from Monitoring Data. - Johannes Grohmann; Simon Eismann; Samuel Kounev (Softwaretechnik-Trends, 2019)

Learning to Learn in Collective Adaptive Systems: Mining Design Patterns for Data-driven Reasoning. - Mirko D'Angelo; Sona Ghahremani; Simos Gerasimou; Johannes Grohmann; Ingrid Nunes; Sven Tomforde; Evangelos Pournaras (ACSOS Companion, 2020)

Optimizing Parametric Dependencies for Incremental Performance Model Extraction. - Sonya Voneva; Manar Mazkatli; Johannes Grohmann; Anne Koziolek (ECSA Companion, 2020)

Incremental Calibration of Architectural Performance Models with Parametric Dependencies. - Manar Mazkatli; David Monschein; Johannes Grohmann; Anne Koziolek (ICSA, 2020)

Baloo: Measuring and Modeling the Performance Configurations of Distributed DBMS. - Johannes Grohmann; Daniel Seybold; Simon Eismann; Mark Leznik; Samuel Kounev; Jörg Domaschka (MASCOTS, 2020)

Model-Based Performance Predictions for SDN-Based Networks: A Case Study. - Stefan Herrnleben; Piotr Rygielski; Johannes Grohmann; Simon Eismann; Tobias Hoßfeld; Samuel Kounev (MMB, 2020)

To Fail or Not to Fail: Predicting Hard Disk Drive Failure Time Windows. - Marwin Züfle; Christian Krupitzer; Florian Erhard; Johannes Grohmann; Samuel Kounev (MMB, 2020)

An IoT Network Emulator for Analyzing the Influence of Varying Network Quality. - Stefan Herrnleben; Rudy Ailabouni; Johannes Grohmann; Thomas Prantl; Christian Krupitzer; Samuel Kounev (SimuTools (2), 2020)

A Simulation-Based Optimization Framework for Online Adaptation of Networks. - Stefan Herrnleben; Johannes Grohmann; Piotr Rygielski; Veronika Lesch; Christian Krupitzer; Samuel Kounev (SimuTools (1), 2020)

An Automated Forecasting Framework based on Method Recommendation for Seasonal Time Series. - André Bauer 001; Marwin Züfle; Johannes Grohmann; Norbert Schmitt; Nikolas Herbst; Samuel Kounev (ICPE, 2020)

Predicting the Costs of Serverless Workflows. - Simon Eismann; Johannes Grohmann; Erwin Van Eyk; Nikolas Herbst; Samuel Kounev (ICPE, 2020)

A Taxonomy of Techniques for SLO Failure Prediction in Software Systems. - Johannes Grohmann; Nikolas Herbst; Avi Chalbani; Yair Arian; Noam Peretz; Samuel Kounev (Comput., 2020)

A Review of Serverless Use Cases and their Characteristics. - Simon Eismann; Joel Scheuner; Erwin Van Eyk; Maximilian Schwinger; Johannes Grohmann; Nikolas Herbst; Cristina L. Abad; Alexandru Iosup (CoRR, 2020)

Serverless Applications: Why, When, and How? - Simon Eismann; Joel Scheuner; Erwin Van Eyk; Maximilian Schwinger; Johannes Grohmann; Cristina L. Abad; Alexandru Iosup (CoRR, 2020)

A Predictive Maintenance Methodology: Predicting the Time-to-Failure of Machines in Industry 4.0. - Marwin Züfle; Joachim Agne; Johannes Grohmann; Ibrahim Dörtoluk; Samuel Kounev (INDIN, 2021)

Sizeless: predicting the optimal size of serverless functions. - Simon Eismann; Long Bui; Johannes Grohmann; Cristina L. Abad; Nikolas Herbst; Samuel Kounev (Middleware, 2021)

ComBench: A Benchmarking Framework for Publish/Subscribe Communication Protocols Under Network Limitations. - Stefan Herrnleben; Maximilian Leidinger; Veronika Lesch; Thomas Prantl; Johannes Grohmann; Christian Krupitzer; Samuel Kounev (VALUETOOLS, 2021)

Libra: A Benchmark for Time Series Forecasting Methods. - André Bauer 001; Marwin Züfle; Simon Eismann; Johannes Grohmann; Nikolas Herbst; Samuel Kounev (ICPE, 2021)

Buzzy: Towards Realistic DBMS Benchmarking via Tailored, Representative, Synthetic Workloads: Vision Paper. - Jörg Domaschka; Mark Leznik; Daniel Seybold; Simon Eismann; Johannes Grohmann; Samuel Kounev (ICPE (Companion), 2021)

SuanMing: Explainable Prediction of Performance Degradations in Microservice Applications. - Johannes Grohmann; Martin Straesser; Avi Chalbani; Simon Eismann; Yair Arian; Nikolas Herbst; Noam Peretz; Samuel Kounev (ICPE, 2021)

Serverless Applications: Why, When, and How? - Simon Eismann; Joel Scheuner; Erwin Van Eyk; Maximilian Schwinger; Johannes Grohmann; Nikolas Herbst; Cristina L. Abad; Alexandru Iosup (IEEE Softw., 2021)

SARDE: A Framework for Continuous and Self-Adaptive Resource Demand Estimation. - Johannes Grohmann; Simon Eismann; André Bauer 001; Simon Spinner; Johannes Blum 001; Nikolas Herbst; Samuel Kounev (ACM Trans. Auton. Adapt. Syst., 2021)

Investigating the Predictability of QoS Metrics in Cellular Networks. - Stefan Herrnleben; Johannes Grohmann; Veronika Lesch; Thomas Prantl; Florian Metzger; Tobias Hoßfeld; Samuel Kounev (IWQoS, 2022)

Same, Same, but Dissimilar: Exploring Measurements for Workload Time-series Similarity. - Mark Leznik; Johannes Grohmann; Nina Kliche; André Bauer 001; Daniel Seybold; Simon Eismann; Samuel Kounev; Jörg Domaschka (ICPE, 2022)

Why Is It Not Solved Yet?: Challenges for Production-Ready Autoscaling. - Martin Straesser; Johannes Grohmann; Jóakim von Kistowski; Simon Eismann; André Bauer 001; Samuel Kounev (ICPE, 2022)

The State of Serverless Applications: Collection, Characterization, and Community Consensus. - Simon Eismann; Joel Scheuner; Erwin Van Eyk; Maximilian Schwinger; Johannes Grohmann; Nikolas Herbst; Cristina L. Abad; Alexandru Iosup (IEEE Trans. Software Eng., 2022)

Model Learning for Performance Prediction of Cloud-native Microservice Applications. - Johannes Grohmann (2022)