Deutsch Intern
Chair of Computer Science II - Software Engineering

Publications

Publications of Software-Engineering Group / Descartes Research Group

This list contains dynamically generated, up-to-date list of publications with filtering possibilities.
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2024[ to top ]
  • Patient-Centered Chronic Wound Care Mobile Apps: Systematic Identification, Analysis, and Assessment. T. Dege; B. Glatzel; V. Borst; F. Grän; S. Goller; C. Glatzel; M. Goebeler; A. Schmieder; in JMIR mHealth and uHealth (2024). 12
  • Comprehensive Exploration of Synthetic Data Generation: A Survey. A. Bauer; S. and Trapp; M. and Stenger; R. and Leppich; S. and Kounev; M. and Leznik; K. and Chard; I. and Foster; in arXiv preprint (2024). 103.
    https://doi.org/10.48550/arXiv.2401.02524
  • Simulating Microservice-b...
    Simulating Microservice-based Architectures for Resilience Assessment Enriched by Authentic Container Orchestration. S. Frank; M. Straesser; L. Wagner; P. Haas; A. Hakamian; S. Kounev; A. Van Hoorn; in Software Engineering 2024 (2024).
  • A Data-Driven Model for Range Sensors. F. Spiess; N. Strobel; T. Kaupp; S. Kounev; in International Journal of Semantic Computing (2024). 1–18.
2023[ to top ]
  • A literature review of Io...
    A literature review of IoT and CPS—What they are, and what they are not. V. Lesch; M. Züfle; A. Bauer; L. Iffländer; C. Krupitzer; S. Kounev; in Journal of Systems and Software (2023). 111631.
  • Power to the Applications...
    Power to the Applications: The Vision of Continuous Decentralized Autoscaling. M. Straesser; S. Geißler; T. Hoßfeld; S. Kounev; in 2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing Workshops (CCGridW) (2023). 281–283.
  • Deep Neural Network Regression for Normalized Digital Surface Model Generation with Sentinel-2 Imagery. K. Müller; R. Leppich; C. Geiß; V. Borst; P. A. Pelizari; S. Kounev; in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2023). 1–14.
  • Performance Impact Analysis of Homomorphic Encryption: A Case Study Using Linear Regression as an Example. T. Prantl; S. Engel; L. Horn; D. Kaiser; L. Iffländer; A. Bauer; C. Krupitzer; S. Kounev; in Information Security Practice and Experience, W. Meng, Z. Yan, V. Piuri (Hrsg.) (2023). 284–298.
  • ExDe: Design space exploration of scheduler architectures and mechanisms for serverless data-processing. S. Talluri; N. Herbst; C. Abad; T. De Matteis; A. Iosup; in Future Generation Computer Systems (2023).
    https://www.sciencedirect.com/science/article/pii/S0167739X23004211
  • Challenges and Future Directions in Efficiency Benchmarking (Vision Paper). M. Meissner; K.-D. Lange; S. Sharma; J. Arnold; A. Cragin; P. Galizia; M. Petrich; B. Zhang; S. Kounev; in Companion of the 2023 ACM/SPEC International Conference on Performance Engineering (2023). 51–55.
  • Kubernetes-in-the-Loop: E...
    Kubernetes-in-the-Loop: Enriching Microservice Simulation Through Authentic Container Orchestration. M. Straesser; P. Haas; S. Frank; A. Hakamian; A. Van Hoorn; S. Kounev; in Performance Evaluation Methodologies and Tools (2023).
    In print.
  • Searching for the Ground ...
    Searching for the Ground Truth: Assessing the Similarity of Benchmarking Runs. A. Bauer; M. Straesser; M. Leznik; L. Beierlieb; M. Hadry; N. Hudson; K. Chard; S. Kounev; I. Foster; in Companion of the 2023 ACM/SPEC International Conference on Performance Engineering (2023). 95–99.
  • Autoscaler Evaluation and...
    Autoscaler Evaluation and Configuration: A Practitioner’s Guideline. M. Straesser; S. Eismann; J. von Kistowski; A. Bauer; S. Kounev; in Proceedings of the 2023 ACM/SPEC International Conference on Performance Engineering (2023). 31–41.
  • Performance Engineering o...
    Performance Engineering of Serverless Applications and Platforms. S. Eismann; Thesis; Universität Würzburg. (2023).
  • Towards a Cryptography Encyclopedia: A Survey on Attribute-Based Encryption. T. Prantl; T. Zeck; L. Horn; L. Iffländer; A. Bauer; A. Dmitrienko; C. Krupitzer; S. Kounev; in Journal of Surveillance, Security and Safety (2023).
  • An Empirical Study of Con...
    An Empirical Study of Container Image Configurations and Their Impact on Start Times. M. Straesser; A. Bauer; R. Leppich; N. Herbst; K. Chard; I. Foster; S. Kounev; in 2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid) (2023). 94–105.
  • Recommendation of Secure Group Communication Schemes using Multi Objective Optimization. T. Prantl; A. Bauer; L. Iffländer; C. Krupitzer; S. Kounev; in International Journal of Information Security (2023).
  • A Systematic Approach for...
    A Systematic Approach for Benchmarking of Container Orchestration Frameworks. M. Straesser; J. Mathiasch; A. Bauer; S. Kounev; in Proceedings of the 2023 ACM/SPEC International Conference on Performance Engineering (2023). 187–198.
  • Segmentierung und Verlauf...
    Segmentierung und Verlaufskontrolle chronischer Wunden durch künstliche Intelligenz mithilfe einer mobilen App (WUNDERKINT Studie). V. Borst; T. Dege; F. Grän; S. Hamrouni; D. Michel; V. Hager; M. Goebeler; R. Leppich; S. Kounev; A. Schmieder; in Allergologie. JDDG: Journal der Deutschen Dermatologischen Gesellschaft (2023). (Bd. 21) 28–177.
    Poster Abstract (No. P322, pp. 175-176)
  • BLOCSIE - Benchmark for LOCalization in a Simulated Industrial Environment. F. Spiess; D. Bluemm; N. Strobel; T. Kaupp; S. Kounev; in 2023 21st International Conference on Advanced Robotics (ICAR) (2023). 577–584.
  • De Bello Homomorphico: Investigation of the extensibility of the OpenFHE library with basic mathematical functions by means of common approaches using the example of the CKKS cryptosystem. T. Prantl; L. Horn; S. Engel; L. Iffländer; L. Beierlieb; C. Krupitzer; A. Bauer; M. Sakarvadia; I. Foster; S. Kounev; in International Journal of Information Security (2023).
  • Challenges in the development of the EO Exploitation Platform terrabyte. J. Eberle; M. Schwinger; J. Zeidler; in Big Data from Space, P. Soille, S. Lumnitz, S. Albani (Hrsg.) (2023). 97–100.
  • Self-Aware Optimization of Adaptation Planning Strategies. V. Lesch; M. Hadry; C. Krupitzer; S. Kounev; in ACM Transactions on Autonomous and Adaptive Systems (2023). 18(3)
  • Serverless Computing: Wha...
    Serverless Computing: What It Is, and What It Is Not?. S. Kounev; N. Herbst; C. L. Abad; A. Iosup; I. Foster; P. Shenoy; O. Rana; A. A. Chien; in Commun. ACM (2023). 66(9) 80–92.
  • MVNOCoreSim: A Digital Twin for Virtualized IoT-centric Mobile Core Networks. S. Geissler; F. Wamser; W. Bauer; S. Gebert; S. Kounev; T. Hossfeld; in IEEE Internet of Things (2023). 10(15) 13974–13987.
  • SPEC Research Group Newsl...
    SPEC Research Group Newsletter, Issue 12. S. Kounev; A. van Hoorn; M. Straesser; A. Bauer; (2023, April).
    Published by Standard Performance Evaluation Corporation (SPEC)
  • Optimizing storage assign...
    Optimizing storage assignment, order picking, and their interaction in mezzanine warehouses. V. Lesch; P. B. Müller; M. Krämer; M. Hadry; S. Kounev; C. Krupitzer; in Applied intelligence (2023). 25.
  • A Trace-driven Performanc...
    A Trace-driven Performance Evaluation of Hash-based Task Placement Algorithms for Cache-enabled Serverless Computing. S. Talluri; N. Herbst; C. Abad; A. Trivedi; A. Iosup; in 2023 ACM International Conference on Computing Frontiers (CF ’23) (2023).
  • Telescope: An Automated H...
    Telescope: An Automated Hybrid Forecasting Approach on a Level-Playing Field. A. Bauer; M. Leznik; M. Stenger; R. Leppich; N. Herbst; S. Kounev; I. Foster; (2023).
  • Association between Postoperative Atrial Fibrillation Recurrences and Interatrial Block by the Time of Open-Heart Surgery. S. Leiler; J. Kalisnik; R. Bernik; A. Bauer; V. Günzler; P. Sluet; S. Kounev; T. Fischlein; in The Thoracic and Cardiovascular Surgeon (2023). 71(S 01) DGTHG-V130.
2022[ to top ]
  • CortexVR: Immersive analy...
    CortexVR: Immersive analysis and training of cognitive executive functions of soccer players using virtual reality and machine learning. C. Krupitzer; J. Naber; J.-P. Stauffert; J. Mayer; J. Spielmann; P. Ehmann; N. Boci; M. Bürkle; A. Ho; C. Komorek; F. Heinickel; S. Kounev; C. Becker; M. E. Latoschik; in Frontiers in Psychology (2022). 5139.
  • Ransomware Detection in Databases through Dynamic Analysis of Query Sequences. C. Sendner; L. Iffländer; S. Schindler; M. Jobst; A. Dmitrienko; S. Kounev; in 2022 IEEE Conference on Communications and Network Security (CNS) (2022).
  • Investigating the Predictability of QoS Metrics in Cellular Networks. S. Herrnleben; J. Grohmann; V. Lesch; T. Prantl; F. Metzger; T. Hoßfeld; S. Kounev; in 2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS) (2022). 1–10.
  • Towards a Cryptography Benchmark: A View on Attribute Based Encryption Schemes. T. Prantl; T. Zeck; L. Iffländer; L. Beierlieb; A. Dmitrenko; C. Krupitzer; S. Kounev; in 2022 5th Conference on Cloud and Internet of Things (CIoT) (2022).
  • Retrospektive Analyse ausgewählter Belastungs-und Beanspruchungsparameter einer professionellen Fußball-mannschaft vor und während coronabedingter Kontakt-beschränkungen in der Spielsaison 2019/20. P. Kunz; P. Düking; R. Leppich; J. Lachmann; B. Sperlich; in Leipziger Sportwissenschaftliche Beiträge Jahrgang 63 (2022 Heft 1 (2022). 75.
  • ICPE ’22: ACM/SPEC International Conference on Performance Engineering, Bejing, China, April 9 - 13, 2022, Companion Volume D. Feng; S. Becker; N. Herbst; P. Leitner; (D. Feng; S. Becker; N. Herbst; P. Leitner, Hrsg.) (2022). ACM.
  • The State of Serverless A...
    The State of Serverless Applications: Collection, Characterization, and Community Consensus. S. Eismann; J. Scheuner; E. van Eyk; M. Schwinger; J. Grohmann; N. Herbst; C. Abad; A. Iosup; in Transactions on Software Engineering (2022). 48(10) 4152–4166.
  • Accuracy and Systematic Biases of Heart Rate Measurements by Consumer-Grade Fitness Trackers in Postoperative Patients: Prospective Clinical Trial. P. Helmer; S. Hottenrott; P. Rodemers; R. Leppich; M. Helwich; R. Pryss; P. Kranke; P. Meybohm; B. E. Winkler; M. Sammeth; in Journal of Medical Internet Research (2022). 24(12) e42359.
  • Same, Same, but Dissimila...
    Same, Same, but Dissimilar: Exploring Measurements for Workload Time-Series Similarity. M. Leznik; J. Grohmann; N. Kliche; A. Bauer; D. Seybold; S. Eismann; S. Kounev; J. Domaschka; in Proceedings of the 2022 ACM/SPEC on International Conference on Performance Engineering (2022). 89–96.
  • A data-driven Sensor Model for LIDAR Range Measurements used for Mobile Robot Navigation. F. Spiess; N. Strobel; T. Kaupp; S. Kounev; in Proceedings of the IEEE IRC 2022 Conference (2022).
  • ICPE ’22: ACM/SPEC International Conference on Performance Engineering, Bejing, China, April 9 - 13, 2022 D. Feng; S. Becker; N. Herbst; P. Leitner; (D. Feng; S. Becker; N. Herbst; P. Leitner, Hrsg.) (2022). ACM.
  • MiSim: A Simulator for Resilience Assessment of Microservice-based Architectures. S. Frank; L. Wagner; A. Hakamian; M. Straesser; A. van Hoorn; in 2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS) (2022). 1014–1025.
  • A Survey on Secure Group Communication Schemes with Focus on IoT Communication. T. Prantl; T. Zeck; A. Bauer; P. Ten; D. Prantl; A. E. Ben Yahya; L. Iffländer; A. Dmitrienko; C. Krupitzer; S. Kounev; in IEEE Access (2022).
    Accepted but not yet published
  • Retrospective Analysis of Training Intensity Distribution Based on Race Pace Versus Physiological Benchmarks in Highly Trained Sprint Kayakers. M. Matzka; R. Leppich; B. Sperlich; C. Zinner; in Sports Medicine-Open (2022). 8(1) 1–12.
  • Proactive Critical Event ...
    Proactive Critical Event Prediction based on Monitoring Data with Focus on Technical Systems. M. O. Züfle; Thesis; Universität Würzburg. (2022).
  • Why Is It Not Solved Yet?...
    Why Is It Not Solved Yet? Challenges for Production-Ready Autoscaling. M. Straesser; J. Grohmann; J. von Kistowski; S. Eismann; A. Bauer; S. Kounev; in Proceedings of the 2022 ACM/SPEC on International Conference on Performance Engineering (2022). 105–115.
  • A literature review on op...
    A literature review on optimization techniques for adaptation planning in adaptive systems: State of the art and research directions. E. Henrichs; V. Lesch; M. Straesser; S. Kounev; C. Krupitzer; in Information and Software Technology (2022). 149 106940.
  • Identification of clinically distinct and prognostically important phenogroups in patients with acute heart failure by a machine learning approach. J. J. Albert; R. Leppich; V. Borst; F. Sahiti; N. Scholz; V. Cejka; C. Morbach; G. Ertl; C. Angermann; S. Frantz; others; in EUROPEAN JOURNAL OF HEART FAILURE (2022). (Bd. 24) 179–179.
  • Self-Aware Optimization of Cyber-Physical Systems in Intelligent Transportation and Logistics Systems. V. Lesch; Thesis; Universität Würzburg. (2022, April).
  • A case study on the stabi...
    A case study on the stability of performance tests for serverless applications. S. Eismann; D. Costa; L. Liao; C.-P. Bezemer; W. Shang; A. van Hoorn; S. Kounev; in Journal of Systems and Software (JSS) (2022). 189
  • Measurement, Modeling, and Emulation of Power Consumption of Distributed Systems. N. Schmitt; (2022, Juni).
  • SPEC Research Group Newsl...
    SPEC Research Group Newsletter, Issue 11. S. Kounev; A. van Hoorn; M. Straesser; A. Bauer; (2022, April).
    Published by Standard Performance Evaluation Corporation (SPEC)
  • Automated Triage of Perfo...
    Automated Triage of Performance Change Points Using Time Series Analysis and Machine Learning. A. Bauer; M. Straesser; L. Beierlieb; M. Meissner; S. Kounev; in Proceedings of the 2022 ACM/SPEC on International Conference on Performance Engineering (2022).
  • FADE: Towards Flexible an...
    FADE: Towards Flexible and Adaptive Distance Estimation Considering Obstacles. M. Hadry; V. Lesch; S. Kounev; in Companion of the 13th ACM/SPEC International Conference on Performance Engineering (ICPE 2022) (2022).
  • SPEC Research - Introduci...
    SPEC Research - Introducing the Predictive Data Analytics Working Group. A. Bauer; M. Leznik; D. Seybold; I. Trubin; B. Erb; J. Domaschka; P. Jamshidi; in Companion of the 2022 ACM/SPEC on International Conference on Performance Engineering (2022).
  • SPEC Research - Introducing the Predictive Data Analytics Working Group. A. Bauer; M. Leznik; D. Seybold; I. Trubin; B. Erb; J. Domaschka; P. Jamshidi; in Companion of the 2022 ACM/SPEC International Conference on Performance Engineering (2022).
  • Change Point Detection for MongoDB Time Series Performance Regression. M. Leznik; M. S. Iqbal; I. A. Trubin; A. Lochner; P. Jamshidi; A. Bauer; in Proceedings of the 2022 ACM/SPEC on International Conference on Performance Engineering (2022).
  • Experience and Guidelines for Sorting Algorithm Choices and Their Energy Efficiency. M. Meissner; S. Kamthania; N. Rawtani; J. Bucek; K.-D. Lange; S. Kounev; in Companion of the 2022 ACM/SPEC International Conference on Performance Engineering (2022).
  • SPEC Efficiency Benchmark...
    SPEC Efficiency Benchmark Development: How to Contribute to the Future of Energy Conservation. M. Meissner; K.-D. Lange; J. Arnold; S. Sharma; R. Tipley; N. Rawtani; D. Reiner; M. Petrich; A. Cragin; in Companion of the 2022 ACM/SPEC International Conference on Performance Engineering (2022).
  • Model Learning for Perfor...
    Model Learning for Performance Prediction of Cloud-native Microservice Applications. J. Grohmann; Thesis; Universität Würzburg. (2022, März).
    Distinction
  • Edge Workload Trace Gathering and Analysis for Benchmarking. K. Toczé; N. Schmitt; U. Kargén; A. Aral; I. Brandi’c; in 2022 IEEE 6th International Conference on Fog and Edge Computing (ICFEC) (2022). 34–41.
  • Towards Forecasting Future Snow Cover Dynamics in the European Alps - The Potential of Long Optical Remote-Sensing Time Series. J. Koehler; A. Bauer; A. J. Dietz; C. Kuenzer; in Remote Sensing (2022). 14(18)
  • The Relationship Between the Distribution of Training Intensity and Performance of Kayak and Canoe Sprinters: A Retrospective Observational Analysis of One Season of Competition. M. Matzka; R. Leppich; H.-C. Holmberg; B. Sperlich; C. Zinner; in Frontiers in Sports and Active Living (2022). 3 788108.
  • An Experience Report on the Suitability of a Distributed Group Encryption Scheme for an IoT Use Case. T. Prantl; S. Engel; A. Bauer; A. E. Ben Yahya; S. Herrnleben; L. Iffländer; A. Dmitrienko; S. Kounev; in 2022 IEEE 95th Vehicular Technology Conference (VTC2022) (2022).
2021[ to top ]
  • Machine Learning Model Update Strategies for Hard Disk Drive Failure Prediction. M. Züfle; F. Erhard; S. Kounev; in 20th IEEE International Conference on Machine Learning and Applications (ICMLA) (2021).
    (to appear)
  • Recommendations for Data-Driven Degradation Estimation with Case Studies from Manufacturing and Dry-Bulk Shipping. N. Finke; M. Mohr; A. Lontke; M. Züfle; S. Kounev; R. Möller; in Research Challenges in Information Science (RCIS) (2021). 189–204.
  • A Machine Learning-based Workflow for Automatic Detection of Anomalies in Machine Tools. M. Züfle; F. Moog; V. Lesch; C. Krupitzer; S. Kounev; in ISA Transactions: The Journal of Automation (2021).
    (in press)
  • A Case Study on Optimizat...
    A Case Study on Optimization of Platooning Coordination V. Lesch; M. Hadry; S. Kounev; C. Krupitzer; (2021).
  • Tackling the Rich Vehicle Routing Problem with Nature-Inspired Algorithms. V. Lesch; M. König; S. Kounev; A. Stein; C. Krupitzer; in Applied Intelligence (2021). 52 9476–9500.
  • An Overview on Approaches...
    An Overview on Approaches for Coordination of Platoons. V. Lesch; M. Breitbach; M. Segata; C. Becker; S. Kounev; C. Krupitzer; in IEEE Transactions on Intelligent Transportation Systems (2021).
    Early Access on IEEE Xplore
  • ComBench: A Benchmarking...
    ComBench: A Benchmarking Framework for Publish/Subscribe Communication Protocols Under Network Limitations. S. Herrnleben; M. Leidinger; V. Lesch; T. Prantl; J. Grohmann; C. Krupitzer; S. Kounev; in Performance Evaluation Methodologies and Tools, Q. Zhao, L. Xia (Hrsg.) (2021). 72–92.
  • Teaching Software Testing Using Automated Grading. L. Beierlieb; L. Iffländer; T. Schneider; T. Prantl; S. Kounev; in Proceedings of the Fifth Workshop "Automatische Bewertung von Programmieraufgaben" (ABP 2021),virtual event, October 28-29, 2021, A. Greubel, S. Strickroth, M. Striewe (Hrsg.) (2021).
  • Automatisierte Hybride Zeitreihenprognose. A. Bauer; in Ausgezeichnete Informatikdissertationen 2020, S. Hölldobler (Hrsg.) (2021). 29–38.
  • Auswirkungen der COVID-19-Pandemie auf Sportlerinnen und Sportler in Deutschland. C. Zinner; M. Matzka; R. Leppich; S. Kounev; H.-C. Holmberg; B. Sperlich; in 53. asp Jahrestagung (2021).
  • The integration of training and off-training activities substantially alters training volume and load analysis in elite rowers. G. Treff; R. Leppich; K. Winkert; J. M. Steinacker; B. Mayer; B. Sperlich; in Scientific reports (2021). 11(1) 1–10.
  • Establishing a cardiac training group for patients with heart failure: the “HIP-in-Würzburg” study. G. Güder; J. Wilkesmann; N. Scholz; R. Leppich; P. Düking; B. Sperlich; C. Rost; S. Frantz; C. Morbach; F. Sahiti; others; in Clinical Research in Cardiology (2021). 1–10.
  • Benchmarking of Pre- and Post-Quantum Group Encryption Schemes with Focus on IoT. T. Prantl; D. Prantl; A. Bauer; L. Iffländer; A. Dmitrenko; C. Krupitzer; S. Kounev; in 2021 IEEE 40th International Performance Computing and Communications Conference (IPCCC) (2021).
  • A Case Study on Optimizat...
    A Case Study on Optimization of Warehouses V. Lesch; P. B. Müller; M. Krämer; S. Kounev; C. Krupitzer; (2021).
  • Serverless Computing (Dagstuhl Seminar 21201). C. Abad; I. T. Foster; N. Herbst; A. Iosup; in Dagstuhl Reports, (C. Abad; I. T. Foster; N. Herbst; A. Iosup, Hrsg.) (2021). 11(4) 34–93.
  • A Case Study of Vehicle R...
    A Case Study of Vehicle Route Optimization V. Lesch; M. König; S. Kounev; A. Stein; C. Krupitzer; (2021).
  • Software Testing Strategies for Detecting Hypercall Handlerstextquotesingle Aging-related Bugs. L. Beierlieb; A. Avritzer; L. Ifflander; N. Antunes; A. Milenkoski; S. Kounev; in 2021 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW) (2021).
  • A Case Study on Optimization of Warehouses. V. Lesch; P. Müller; M. Krämer; S. Kounev; C. Krupitzer; in arXiv preprint arXiv:2112.12058 (2021).
  • Automated Hybrid Time Series Forecasting: Design, Benchmarking, and Use Cases. A. Bauer; Thesis; Universität Würzburg. (2021).
  • Performance Evaluation of a Post-Quantum Public-Key Cryptosystem. T. Prantl; D. Prantl; L. Beierlieb; L. Iffländer; A. Dmitrienko; C. Krupitzer; S. Kounev; in 2021 IEEE 40th International Performance Computing and Communications Conference (IPCCC) (2021).
  • Towards Situation-Aware M...
    Towards Situation-Aware Meta-Optimization of Adaptation Planning Strategies. V. Lesch; T. Noack; J. Hefter; S. Kounev; C. Krupitzer; in Proceedings of the 2nd IEEE International Conference on Autonomic Computing and Self-Organizing Systems - ACSOS 2021 (2021).
    Best Paper Award Runner Up, Full Paper Acceptance Ratio: 25%
  • Serverless Applications:W...
    Serverless Applications:Why, When, and How?. S. Eismann; S. Joel; E. van Eyk; M. Schwinger; J. Grohmann; N. Herbst; C. Abad; A. Iosup; in IEEE Software (2021). 38(1) 32–39.
  • Buzzy: Towards Realistic ...
    Buzzy: Towards Realistic DBMS Benchmarking via Tailored, Representative, Synthetic Workloads. J. Domaschka; S. Eismann; M. Leznik; J. Grohmann; S. Kounev; D. Seybold; in Companion of the ACM/SPEC International Conference on Performance Engineering (2021). (Bd. ICPE ’21) 175–178.
  • Scalable Processing Of Copernicus Sentinel satellite Images Using Argo Workflows. F. W. Fichtner; N. Mandery; M. Schwinger; J. Eberle; M. Nolde; T. Riedlinger; in Big Data from Space 2021 (2021). 77–80.
  • People Detection with Depth Silhouettes and Convolutional Neural Networks on a Mobile Robot. F. Spiess; L. Reinhart; N. Strobel; D. Kaiser; S. Kounev; T. Kaupp; in Journal of Image and Graphics, (J. of Image; Graphics, Hrsg.) (2021). 9(4) 135–139.
  • Towards a Mobile Robot Localization Benchmark with Challenging Sensordata in an Industrial Environment. F. Spiess; J. Friesslich; D. Bluemm; F. Mast; D. Vinokour; S. Kounev; T. Kaupp; N. Strobel; in 2021 20th International Conference on Advanced Robotics (ICAR) (2021). 857–864.
  • Towards Splitting Monolithic Workflows into Serverless Functions and Estimating Their Run-Time in the Earth Observation Domain. D. Kaiser; B. Dovhan; A. Bauer; S. Kounev; in Proceedings of the 12th Symposium on Software Performance (SSP) (2021).
    Extended Abstract
  • Measuring the Performance Impact of Branching Instructions. L. Beierlieb; L. Iffländer; A. Milenkoski; T. Prantl; S. Kounev; in Proceedings of the 12th Symposium on Software Performance 2021 (SSP’21) (2021).
  • A Simulation-based Optimi...
    A Simulation-based Optimization Framework for Online Adaptation of Networks. S. Herrnleben; J. Grohmann; P. Rygielski; V. Lesch; C. Krupitzer; S. Kounev; in Proceedings of the 12th EAI International Conference on Simulation Tools and Techniques (SIMUtools), H. Song, D. Jiang (Hrsg.) (2021). 513–532.
  • A Predictive Maintenance ...
    A Predictive Maintenance Methodology: Predicting the Time-to-Failure of Machines in Industry 4.0. M. Züfle; J. Agne; J. Grohmann; I. Dörtoluk; S. Kounev; in Proceedings of the 21st IEEE IES International Conference on Industrial Informatics (2021).
  • SARDE: A Framework for Co...
    SARDE: A Framework for Continuous and Self-Adaptive Resource Demand Estimation. J. Grohmann; S. Eismann; A. Bauer; S. Spinner; J. Blum; N. Herbst; S. Kounev; in ACM Transactions on Autonomous and Adaptive Systems (2021). 15(2)
  • Towards Scientific and Interoperable Earth Observation Exploitation Platforms. J. Eberle; M. Schwinger; H. Zwenzner; in Proceedings of the 2021 conference on Big Data from Space, P. Soille, S. Loekken, M. Albani (Hrsg.) (2021). 89–92.
  • Energy-Efficiency Comparison of Common Sorting Algorithms. N. Schmitt; S. Kamthania; N. Rawtani; L. Mendoza; K.-D. Lange; S. Kounev; in 2021 29th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS) (2021). 1–8.
  • SPEC - Spotlight on the International Standards Group (ISG). N. Schmitt; K.-D. Lange; S. Sharma; A. Cragin; D. Reiner; S. Kounev; in Companion of the ACM/SPEC International Conference on Performance Engineering (2021).
  • Utility-based Vehicle Rou...
    Utility-based Vehicle Routing Integrating User Preferences. V. Lesch; M. Hadry; S. Kounev; C. Krupitzer; in Proceedings of 3rd International Workshop on Pervasive Computing for Vehicular Systems (PerVehicle), 2021 (2021).
  • Libra: A Benchmark for Ti...
    Libra: A Benchmark for Time Series Forecasting Methods. A. Bauer; M. Züfle; S. Eismann; J. Grohmann; N. Herbst; S. Kounev; in Proceedings of the 12th ACM/SPEC International Conference on Performance Engineering (ICPE) (2021).
  • Sizeless: Predicting the ...
    Sizeless: Predicting the Optimal Size of Serverless Functions. S. Eismann; L. Bui; J. Grohmann; C. Abad; N. Herbst; S. Kounev; in Proceedings of the 22nd International MIDDLEWARE Conference (2021). 248–259.
    Best Student Paper Award, ACM Artifacts Evaluated — Functional
  • A Comparison of Mechanism...
    A Comparison of Mechanisms for Compensating Negative Impacts of System Integration. V. Lesch; C. Krupitzer; K. Stubenrauch; N. Keil; C. Becker; S. Kounev; M. Segata; in Future Generation Computer Systems (2021). 116 117–131.
  • Attack-aware Security Fun...
    Attack-aware Security Function Management. L. Iffländer; Thesis; Universität Würzburg. (2021, Januar).
  • SuanMing: Explainable Pre...
    SuanMing: Explainable Prediction of Performance Degradations in Microservice Applications. J. Grohmann; M. Straesser; A. Chalbani; S. Eismann; Y. Arian; N. Herbst; N. Peretz; S. Kounev; in Proceedings of the 12th ACM/SPEC International Conference on Performance Engineering (ICPE) (2021).
    Acceptance Rate: 29%
  • SPEC Research Group Newsl...
    SPEC Research Group Newsletter, vol. 3 no. 2. S. Kounev; A. van Hoorn; A. Bauer; (2021, April).
    Published by Standard Performance Evaluation Corporation (SPEC)
  • Performance Impact Analysis of Securing MQTT Using TLS. T. Prantl; L. Iffländer; S. Herrnleben; S. Engel; S. Kounev; C. Krupitzer; in 2021 ACM/SPEC International Conference on Performance Engineering (ICPE) (2021).
  • Towards a Group Encryption Scheme Benchmark: A View on Centralized Schemes with focus on IoT. T. Prantl; P. Ten; L. Iffländer; S. Herrnleben; A. Dmitrenko; S. Kounev; C. Krupitzer; in 2021 ACM/SPEC International Conference on Performance Engineering (ICPE) (2021).
2020[ to top ]
  • Predicting Failures by Means of Machine Learning Methods on the Example of an Industrial Press. J. Agne; Thesis; University of Würzburg; Am Hubland, Informatikgebäude, 97074 Würzburg, Germany. (2020, Februar).
  • Introduction to the Speci...
    Introduction to the Special Issue ``Applications in Self-Aware Computing Systems and their Evaluation’’. C. Krupitzer; B. Eberhardinger; I. Gerostathopoulos; C. Raibulet; (2020).
  • Towards Self-Aware Multir...
    Towards Self-Aware Multirotor Formations. D. Kaiser; V. Lesch; J. Rothe; M. Strohmeier; F. Spiess; C. Krupitzer; S. Montenegro; S. Kounev; in Computers (2020). 9(7)
    Special Issue on Self-Aware Computing
  • Elasticity of Cloud Platforms. N. Herbst; A. Bauer; S. Kounev; in Systems Benchmarking: For Scientists and Engineers, S. Kounev, K.-D. Lange, J. von Kistowski (Hrsg.) (2020). 319–340.
  • A Taxonomy of Techniques for SLO Failure Prediction in Software Systems. J. Grohmann; N. Herbst; A. Chalbani; Y. Arian; N. Peretz; S. Kounev; in Computers (2020). 9(1) 10.
  • Systems Benchmarking S. Kounev; K.-D. Lange; J. von Kistowski; (2020). (1. Aufl.) Springer International Publishing.
  • REACT: A Model-Based Runt...
    REACT: A Model-Based Runtime Environment for Adapting Communication Systems. M. Pfannemüller; M. Breitbach; C. Krupitzer; M. Weckesser; C. Becker; B. Schmerl; A. Schürr; in Proceedings of the IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS 2020) (2020).
  • Beyond Microbenchmarks: T...
    Beyond Microbenchmarks: The SPEC-RG Vision for A Comprehensive Serverless Benchmark. E. van Eyk; J. Scheuner; S. Eismann; C. Abad; A. Iosup; in Companion of the 2020 ACM/SPEC International Conference on Performance Engineering (2020).
  • SIMPL: Secure IoT Managem...
    SIMPL: Secure IoT Management Platform. T. Prantl; A. E. Ben Yahya; A. Dmitrienko; S. Kounev; F. Lipp; D. Hock; C. Rathfelder; M. Hofherr; in ITG Workshop on IT Security (ITSec) (2020).
  • An Overview of Design Pat...
    An Overview of Design Patterns for Self-Adaptive Systems in the Context of the Internet of Things. C. Krupitzer; T. Temizer; T. Prantl; C. Raibulet; in IEEE Access (2020).
  • Intra-individual physiological response of recreational runners to different training mesocycles: a randomized cross-over study. P. Düking; H.-C. Holmberg; P. Kunz; R. Leppich; B. Sperlich; in European Journal of Applied Physiology (2020). 1–9.
  • Toward a Framework for Self-Learning Adaptation Planning through Optimization. V. Lesch; in Organic Computing: Doctoral Dissertation Colloquium 2020 (2020).
  • Quantifying measurement q...
    Quantifying measurement quality and load distribution in Tor. A. Greubel; S. Pohl; S. Kounev; in Proceedings of the 36th Annual Computer Security Applications Conference (ACSAC 2020) (2020).
  • Learning to Learn in Coll...
    Learning to Learn in Collective Adaptive Systems: Mining Design Pattern for Data-driven Reasoning. M. D’Angelo; S. Ghahremani; S. Gerasimou; J. Grohmann; I. Nunes; S. Tomforde; E. Pournaras; in 2020 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C) (2020). 121–126.
  • The impact of the German strategy for containment of Coronavirus SARS-CoV-2 on the training characteristics, physical activity, sleep of highly trained kayakers and canoeists: A retrospective observational study. C. Zinner; M. Matzka; R. Leppich; S. Kounev; H. Holmberg; B. Sperlich; in Frontiers in Sports and Active Living (2020). 2 127.
  • Methodological Principles...
    Methodological Principles for Reproducible Performance Evaluation in Cloud Computing. A. V. Papadopoulos; L. Versluis; A. Bauer; N. Herbst; J. von Kistowski; A. Ali-Eldin; C. L. Abad; J. N. Amaral; P. Tuma; A. Iosup; in Software Engineering 2020, Fachtagung des GI-Fachbereichs Softwaretechnik, 24.-28. Februar 2020, Innsbruck, Austria, M. Felderer, W. Hasselbring, R. Rabiser, R. Jung (Hrsg.) (2020). (Bd. P-300) 93–94.
  • A Survey on Human Machine...
    A Survey on Human Machine Interaction in Industry 4.0 C. Krupitzer; S. Müller; V. Lesch; M. Züfle; J. Edinger; A. Lemken; D. Schäfer; S. Kounev; C. Becker; (2020).
  • A Concept for Crowd-sensed Prediction of Mobile Network Connectivity. S. Herrnleben; B. Zeidler; M. Züfle; C. Krupitzer; S. Kounev; in GI/ITG Workshop on Machine Learning in the Context of Communication Networks 2020 (2020).
  • Microservices: A Performa...
    Microservices: A Performance Tester’s Dream or Nightmare?. S. Eismann; C.-P. Bezemer; W. Shang; D. Okanovic; A. van Hoorn; in Proceedings of the 2020 ACM/SPEC International Conference on Performance Engineering (ICPE) (2020).
    Acceptance Rate: 23.4% (15/64), ACM Artifacts Evaluated — Functional
  • A Survey on Predictive Ma...
    A Survey on Predictive Maintenance for Industry 4.0 C. Krupitzer; T. Wagenhals; M. Züfle; V. Lesch; D. Schäfer; A. Mozaffarin; J. Edinger; C. Becker; S. Kounev; (2020).
  • Towards a Self-Aware Prediction of Critical States. M. Züfle; in Organic Computing: Doctoral Dissertation Colloquium 2020, S. Tomforde, C. Krupitzer (Hrsg.) (2020).
    (to appear)
  • Survey and Experimental Comparison of RGB-D Indoor Robot Navigation Methods Supported by ROS and Their Expansion via Fusion with Wheel Odometry and IMU Data. F. Spiess; J. Friesslich; K. Tobias; S. Kounev; N. Strobel; in International Journal of Mechanical Engineering and Robotics Research (IJMERR), (P. R. (Chunhui) Yang, Hrsg.) (2020). 9(12) 1532–1540.
  • Performance, Power, and Energy-Efficiency Impact Analysis of Compiler Optimizations on the SPEC CPU 2017 Benchmark Suite. N. Schmitt; J. Bucek; J. Beckett; A. Cragin; K.-D. Lange; S. Kounev; in 2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC) (2020). 292–301.
  • Evaluating the Performance of a State-of-the-Art Group-oriented Encryption Scheme for Dynamic Groups in an IoT Scenario. T. Prantl; P. Ten; L. Iffländer; A. Dmitrenko; S. Kounev; C. Krupitzer; in 2020 IEEE 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS) (2020).
    Acceptance Rate: 27%
  • Baloo: Measuring and Mode...
    Baloo: Measuring and Modeling the Performance Configurations of Distributed DBMS. J. Grohmann; D. Seybold; S. Eismann; M. Leznik; S. Kounev; J. Domaschka; in 2020 28th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS) (2020). 1–8.
    Acceptance Rate: 27%
  • Incremental Calibration o...
    Incremental Calibration of Architectural Performance Models with Parametric Dependencies. M. Mazkatli; D. Monschein; J. Grohmann; A. Koziolek; in 2020 IEEE International Conference on Software Architecture (ICSA 2020) (2020). 23–34.
  • A Framework for Time Seri...
    A Framework for Time Series Preprocessing and History-based Forecasting Method Recommendation. M. Züfle; S. Kounev; in Proceedings of the 15th Conference on Computer Science and Information Systems (FedCSIS): Data Mining Competition of the International Symposium on Advanced Artificial Intelligence in Applications (2020).
  • An IoT Network Emulator f...
    An IoT Network Emulator for Analyzing the Influence of Varying Network Quality. S. Herrnleben; R. Ailabouni; J. Grohmann; T. Prantl; C. Krupitzer; S. Kounev; in Proceedings of the 12th EAI International Conference on Simulation Tools and Techniques (SIMUtools) (2020).
  • Time Series Forecasting for Self-Aware Systems. A. Bauer; M. Züfle; N. Herbst; A. Zehe; A. Hotho; S. Kounev; in Proceedings of the IEEE (2020). 108(7) 1068–1093.
  • Optimizing Parametric Dep...
    Optimizing Parametric Dependencies for Incremental Performance Model Extraction. S. Voneva; M. Mazkatli; J. Grohmann; A. Koziolek; in Companion of the 14th European Conference Software Architecture (ECSA 2020), H. Muccini, P. Avgeriou, B. Buhnova, J. Cámara, M. Caporuscio, M. Franzago, A. Koziolek, P. Scandurra, C. Trubiani, D. Weyns, U. Zdun (Hrsg.) (2020). (Bd. 1269) 228–240.
  • A Review of Serverless Us...
    A Review of Serverless Use Cases and their Characteristics S. Eismann; J. Scheuner; E. van Eyk; M. Schwinger; J. Grohmann; N. Herbst; C. Abad; A. Iosup; (2020).
  • Energy Efficiency Analysi...
    Energy Efficiency Analysis of Compiler Optimizations on the SPEC CPU 2017 Benchmark Suite. N. Schmitt; J. Bucek; K.-D. Lange; S. Kounev; in Proceedings of the 11th ACM/SPEC International Conference on Performance Engineering (ICPE 2020) (2020).