piwik-script

Deutsch Intern
    Chair of Computer Science II - Software Engineering

    Publications

    Publications of Chair of Software Engineering

    This list contains dynamically generated, up-to-date list of publications with filtering possibilities.
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    2023[ to top ]
    • Smarter Contracts: Detecting Vulnerabilities in Smart Contracts with Deep Transfer Learning C. Sendner; H. Chen; H. Fereidooni; L. Petzi; J. König; J. Stang; A. Dmitrienko; A.-R. Sadeghi; F. Koushanfar; in To appear at the Network and Distributed System Security Symposium (NDSS) (2023).
    • AuthentiSense: A Scalable Behavioral Biometrics Authentication Scheme using Few-Shot Learning for Mobile Platforms H. Fereidooni; J. König; P. Rieger; M. Chilese; M. Finke; B. Goekbakan; A. Dmitrienko; A.-R. Sadeghi; in To appear at the Network and Distributed System Security Symposium (NDSS) (2023).
    2022[ to top ]
    • 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).
    • 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). (Vol. 24) 179–179.
    • 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).
    • 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).
    • MiSim: A Simulator for Resilience Assessment of Microservice-based Architectures S. Frank; L. Wagner; A. Hakamian; M. Straesser; A. van Hoorn; in Proceedings of the IEEE 22nd International Conference on Software Quality, Reliability, and Security (QRS 2022) (2022).
      In print.
    • 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).
    • 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, eds.) (2022). ACM.
    • 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.
    • 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.
    • 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.
    • Leveraging Kubernetes Source Code for Performance Simulation M. Straesser; P. Haas; (2022).
    • 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.
    • Self-Aware Optimization of Adaptation Planning Strategies V. Lesch; M. Hadry; S. Kounev; C. Krupitzer; in ACM Transactions on Autonomous and Adaptive Systems (2022).
    • 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).
    • Digital Contact Tracing Solutions: Promises, Pitfalls and Challenges N. Thien Duc; M. Markus; D. Alexandra; S. Ahmad-Reza; V. Ivan; in ArXiv I arXiv 2202.06698v2 (2022).
    • Close the Gate: Detecting Backdoored Models in Federated Learning based on Client-Side Deep Layer Output Analysis P. Rieger; T. Krauß; M. Miettinen; A. Dmitrienko; A.-R. Sadeghi; in ArXiv | arXiv:2210.07714 (2022).
    • 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)
    • FedCRI: Federated Mobile Cyber-Risk Intelligence H. Fereidooni; A. Dmitrienko; F. Madlener; P. Rieger; M. Miettinen; A.-R. Sadeghi; in The Network and Distributed System Security Symposium (NDSS) (2022).
      (to appear)
    • 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).
    • 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
    • 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).
    • 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).
    • Self-Aware Optimization of Cyber-Physical Systems in Intelligent Transportation and Logistics Systems V. Lesch; Thesis; Universität Würzburg. (2022, April).
    • Contact Discovery in Mobile Messengers: Low-cost Attacks, Quantitative Analyses, and Efficient Mitigations C. Hagen; C. Weinert; C. Sendner; A. Dmitrienko; T. Schneider; in ACM Transactions on Privacy and Security (2022).
      (to appear)
    • 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.
    • 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).
    • 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).
    • 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, eds.) (2022). ACM.
    • SCRAPS: Scalable Collective Remote Attestation for Pub-Sub IoT Networks with Untrusted Proxy Verifier L. Petzi; A. E. Ben Yahya; A. Dmitrienko; G. Tsudik; T. Prantl; S. Kounev; (2022). (Vol. USENIX Security ’22)
      Coming Soon
    • Measurement, Modeling, and Emulation of Power Consumption of Distributed Systems N. Schmitt; (2022, June).
    • 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).
    • 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.
    • 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)
    • 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 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
    • Model Learning for Perfor...
      Model Learning for Performance Prediction of Cloud-native Microservice Applications J. Grohmann; Thesis; Universität Würzburg. (2022, March).
      Distinction
    • Proactive Critical Event Prediction based on Monitoring Data with Focus on Technical Systems M. Züfle; Thesis; Universität Würzburg. (2022).
    2021[ to top ]
    • 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).
    • Automatisierte Hybride Zeitreihenprognose A. Bauer; in Ausgezeichnete Informatikdissertationen 2020, S. Hölldobler (ed.) (2021). 29–38.
    • 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
    • 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
    • Automated Hybrid Time Series Forecasting: Design, Benchmarking, and Use Cases A. Bauer; Thesis; Universität Würzburg. (2021).
    • 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).
    • 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 (eds.) (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).
    • 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).
    • 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.
    • Attack-aware Security Fun...
      Attack-aware Security Function Management L. Iffländer; Thesis; Universität Würzburg. (2021, January).
    • 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, eds.) (2021). 9(4) 135–139.
    • 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).
    • 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.
    • Security and Privacy Aspects of Digital Contact Tracing F. Roos; Thesis; University of Würzburg. (2021, October).
    • A Case Study on Optimization of Warehouses V. Lesch; P. Müller; M. Krämer; S. Kounev; C. Krupitzer; in arXiv preprint arXiv:2112.12058 (2021).
    • 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 (eds.) (2021). 72–92.
    • A Case Study on Optimizat...
      A Case Study on Optimization of Warehouses V. Lesch; P. B. Müller; M. Krämer; S. Kounev; C. Krupitzer; (2021).
    • A Case Study of Vehicle R...
      A Case Study of Vehicle Route Optimization V. Lesch; M. König; S. Kounev; A. Stein; C. Krupitzer; (2021).
    • Container Start Times: Em...
      Container Start Times: Empirical Analysis and Predictability M. Straesser; (2021).
    • A Case Study on Optimizat...
      A Case Study on Optimization of Platooning Coordination V. Lesch; M. Hadry; S. Kounev; C. Krupitzer; (2021).
    • Vision: Challenges & Opportunities. M. Annaaram; N. Asokan; B. G. Atli; S. Avestimeh; F. Brasser; R. Cammarota; A. Dmitrienko; A. Dziedzic; T. Given-Wilson; L. J. Gunn; F. Kerschbaum; F. Koushanfar; A. Legay; M. Miettinen; T. D. Nguyen; N. Papernot; A.-R. Sadeghi; M. Schunter; R. Shokri; V. Smith; in Vision Paper of the Private AI Collaborative Research Institute (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.
    • 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)
    • 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
    • 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%
    • 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%
    • 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)
    • 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)
    • 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).
    • 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.
    • 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.
    • 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 (eds.) (2021). 513–532.
    • Remote Attestation for IoT with Smart Verifier L. Petzi; Thesis; University of Würzburg. (2021, January).
    • 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).
    • RIP StrandHogg: A Practical StrandHogg Attack Detection Method on Android J. Stang; A. Dmitrienko; S. Roth; in 14th ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec) (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).
    • 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.
    • 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).
    • 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)
    • ESCORT: Ethereum Smart COntRacTs Vulnerability Detection using Deep Neural Network and Transfer Learning O. Lutz; H. Chen; H. Fereidooni; C. Sendner; A. Dmitrienko; A. R. Sadeghi; F. Koushanfar; in ArXiv | arXiv:2103.12607v1 (2021).
    • All the Numbers are US: Large-scale Abuse of Contact Discovery in Mobile Messengers C. Hagen; C. Weinert; C. Sendner; A. Dmitrienko; T. Schneider; in Network and Distributed System Security Symposium (NDSS) (2021).
      (To Appear)
    • 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.
    • 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).
    • 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, eds.) (2021). 11(4) 34–93.
    • 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). (Vol. ICPE ’21) 175–178.
    • 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).
    • Increasing Security in Satellite Networks K. Schilling; A. Dmitrienko; in 72nd International Astronautical Congress (IAC) (2021).
    2020[ to top ]
    • 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).
    • Aggregatable Remote Attestation for IoT V. Alistarov; Thesis; University of Würzburg. (2020, December).
    • 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 (eds.) (2020). (Vol. 1269) 228–240.
    • 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%
    • 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, ed.) (2020). 9(12) 1532–1540.
    • 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 (eds.) (2020). 319–340.
    • 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.
    • Detection of Software Vulnerabilities in Smart Contracts using Deep Learning O. Lutz; Thesis; University of Würzburg. (2020, October).
    • Testbed for Security Testing of Smart Contracts L. Denk; Thesis; University of Würzburg. (2020, November).
    • Understanding UI attacks on Android S. Jasper; (2020, December).
    • Contact Tracing by Giant Data Collectors: Opening Pandora’s Box of Threats to Privacy, Sovereignty and National Security A. Boutet; C. Castelluccia; M. Cunche; A. Dmitrienko; V. Iovino; M. Miettinen; T. D. Nguyen; V. Roca; A.-R. Sadeghi; S. Vaudenay; I. Visconti; M. Vuagnoux; (2020).
    • Systems Benchmarking S. Kounev; K.-D. Lange; J. von Kistowski; (2020). (1st ed.) Springer International Publishing.
    • 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
    • All the Numbers are US: Large-scale Abuse of Contact Discovery in Mobile Messengers C. Hagen; C. Weinert; C. Sendner; A. Dmitrienko; T. Schneider; in Cryptology ePrint Archive, Report 2020/1119 (2020).
    • Predicting Performance De...
      Predicting Performance Degradations of Black-box Microservice Applications M. Straesser; (2020).
    • 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).
    • 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).
    • Strategies for the Security Assessment of IoT Devices by Certification Authorities M. A. Finke; Thesis; University of Würzburg; Am Hubland, Informatikgebäude, 97074 Würzburg, Germany. (2020, May).
    • 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).
    • Evaluating the Privacy of Contact Discovery C. Sendner; Thesis; University of Würzburg. (2020, July).
    • LegIoT: Ledgered Trust Management Platform for IoT J. Neureither; A. Dmitrienko; D. Koisser; F. Brasser; A.-R. Sadeghi; in European Symposium on Research in Computer Security (ESORICS) (2020).
    • Mind the GAP: Security & Privacy Risks of Contact Tracing Apps L. Baumgärtner; A. Dmitrienko; B. Freisleben; A. Gruler; J. Höchst; J. Kühlberg; M. Mezini; M. Miettinen; A. Muhamedagic; T. D. Nguyen; A. Penning; D. F. Pustelnik; F. Roos; A.-R. Sadeghi; M. Schwarz; C. Uhl; in ArXiv (2020).
    • Mind the GAP: Security & Privacy Risks of Contact Tracing Apps L. Baumgärtner; A. Dmitrienko; B. Freisleben; J. Höchst; M. Mezini; M. Miettinen; T. D. Nguyen; A. Penning; F. Roos; A.-R. Sadeghi; M. Schwarz; C. Uhl; (2020).
      Accepted to TrustCom 2020, Security Track
    • 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).
    • An Automated Forecasting ...
      An Automated Forecasting Framework based on Method Recommendation for Seasonal Time Series A. Bauer; M. Züfle; J. Grohmann; N. Schmitt; N. Herbst; S. Kounev; in Proceedings of the ACM/SPEC International Conference on Performance Engineering (2020). 48–55.
    • 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).
    • 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).
    • 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.
    • 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).
    • 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.
    • 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.
    • 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).
    • 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%
    • Towards a Self-Aware Prediction of Critical States M. Züfle; in Organic Computing: Doctoral Dissertation Colloquium 2020, S. Tomforde, C. Krupitzer (eds.) (2020).
      (to appear)
    • Model-based Performance P...
      Model-based Performance Predictions for SDN-based Networks: A Case Study S. Herrnleben; P. Rygielski; J. Grohmann; S. Eismann; T. Hossfeld; S. Kounev; in Proceedings of the 20th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems (2020).
    • SPEC Research Group Newsl...
      SPEC Research Group Newsletter, vol. 3 no. 1 S. Kounev; A. van Hoorn; A. Bauer; N. Herbst; (2020, April).
      Published by Standard Performance Evaluation Corporation (SPEC)
    • Predicting the Costs of S...
      Predicting the Costs of Serverless Workflows S. Eismann; J. Grohmann; E. van Eyk; N. Herbst; S. Kounev; in Proceedings of the 2020 ACM/SPEC International Conference on Performance Engineering (ICPE) (2020). 265–276.
      Acceptance Rate: 23.4% (15/64)
    • Toward a Framework for Self-Learning Adaptation Planning through Optimization V. Lesch; in Organic Computing: Doctoral Dissertation Colloquium 2020 (2020).
    • Telescope: An Automatic F...
      Telescope: An Automatic Feature Extraction and Transformation Approach for Time Series Forecasting on a Level-Playing Field A. Bauer; M. Züfle; N. Herbst; S. Kounev; V. Curtef; in Proceedings of the 36th International Conference on Data Engineering (ICDE) (2020).
    • 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).
    • 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
    • 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).
    • 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 (eds.) (2020). (Vol. P-300) 93–94.
    • 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.
    • 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.
    • 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.
    • 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).
    • 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).
    • To Fail Or Not To Fail: P...
      To Fail Or Not To Fail: Predicting Hard Disk Drive Failure Time Windows M. Züfle; C. Krupitzer; F. Erhard; J. Grohmann; S. Kounev; in Proceedings of the 20th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems (2020). 19–36.
    • Strategies for the Security Assessment of IoT Devices by Certification Authorities M. A. Finke; Thesis; University of Würzburg; Am Hubland, Informatikgebäude, 97074 Würzburg, Germany. (2020, May).
    2019[ to top ]
    • On Learning Parametric De...
      On Learning Parametric Dependencies from Monitoring Data J. Grohmann; S. Eismann; S. Kounev; in Proceedings of the 10th Symposium on Software Performance 2019 (SSP’19) (2019).
    • WheelShare: Crowd-sensed ...
      WheelShare: Crowd-sensed Surface Classification for Accessible Routing J. Edinger; V. Raychoudhury; A. Hofmann; A. Wachner; C. Becker; C. Krupitzer; in Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) (2019).
    • Chamulteon: Coordinated A...
      Chamulteon: Coordinated Auto-Scaling of Micro-Services A. Bauer; V. Lesch; L. Versluis; A. Ilyushkin; N. Herbst; S. Kounev; in Proceedings of the 39th IEEE International Conference on Distributed Computing Systems (ICDCS) (2019).
    • Systematic Search for Opt...
      Systematic Search for Optimal Resource Configurations of Distributed Applications A. Bauer; S. Eismann; J. Grohmann; N. Herbst; S. Kounev; in 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W) (2019). 120–125.
    • Performance Influence of ...
      Performance Influence of Security Function Chain Ordering L. Iffländer; N. Fella; in Companion of the 2019 ACM/SPEC International Conference on Performance Engineering (2019). 45–46.
    • Online Power Consumption ...
      Online Power Consumption Estimation for Functions in Cloud Applications N. Schmitt; L. Iffländer; A. Bauer; S. Kounev; in Proceedings of the 16th IEEE International Conference on Autonomic Computing (ICAC) (2019).
    • Hands Off my Database: Ransomware Detection in Databases through Dynamic Analysis of Query Sequences L. Iffländer; A. Dmitrienko; C. Hagen; M. Jobst; S. Kounev; in ArXiv | arXiv:1907.06775v1 (2019).
    • A Modular Simulation Fram...
      A Modular Simulation Framework for Analyzing Platooning Coordination C. Krupitzer; V. Lesch; M. Pfannemüller; C. Becker; M. Segata; in Proceedings of the 1st ACM Workshop on Technologies, mOdels, and Protocols for Cooperative Connected Cars (TOP-Cars), Colocated with ACM MobiHoc 2019 (2019).
    • Towards Edge Benchmarking: A Methodology for Characterizing Edge Workloads K. Tocze; N. Schmitt; I. Brandic; A. Aral; S. Nadjm-Tehrani; in Proceedings of Workshop on Hot Topics in Cloud Computing Performance (HotCloudPerf) as part of FAS*(IEEE ICAC/SASO) conferences companion (2019).
    • On Learning in Collective...
      On Learning in Collective Self-Adaptive Systems: State of Practice and a 3D Framework M. D’Angelo; S. Gerasimou; S. Ghahremani; J. Grohmann; I. Nunes; E. Pournaras; S. Tomforde; in Proceedings of the 14th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (2019). 13–24.
    • A Concept for an Adaptive...
      A Concept for an Adaptive Communication Middleware for Car-2-Cloud Applications S. Herrnleben; (2019, April).
    • Multi-objective Optimisat...
      Multi-objective Optimisation in Hybrid Collaborating Adaptive Systems V. Lesch; C. Krupitzer; S. Tomforde; in Proceedings of the 7th edition in the Series on Autonomously Learning and Optimising Systems (SAOS), co-located with 32nd GI/ITG ARCS 2019 (2019).
    • Emerging Self-Integration...
      Emerging Self-Integration through Coordination of Autonomous Adaptive Systems V. Lesch; C. Krupitzer; S. Tomforde; in Proceedings of the 4th IEEE International Workshops on Foundations and Applications of Self* Systems, FAS*W@ICAC/SASO 2019 (2019).
    • Please Obey My Plan: How ...
      Please Obey My Plan: How to Optimise Decentralised Self-Adaptive Systems V. Lesch; C. Krupitzer; S. Tomforde; (2019, April).
    • Artificial Intelligence in Medicine - From Data Collection to Prediction M. Züfle; R. Leppich; (2019, November).
    • Best Practices for Time S...
      Best Practices for Time Series Forecasting A. Bauer; M. Züfle; N. Herbst; S. Kounev; in 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W) (2019).
    • Exploring the Limitations of Statistical Response Time Models in Architectural Performance Models S. Trapp; Thesis; University of Würzburg; Am Hubland, Informatikgebäude, 97074 Würzburg, Germany. (2019, December).
    • Planning as Optimization:...
      Planning as Optimization: Dynamically Discovering Optimal Configurations for Runtime Situations E. M. Fredericks; I. Gerostathopoulos; C. Krupitzer; T. Vogel; in Proceedings of the 13th IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2019 (2019).
    • A survey on adaptive auth...
      A survey on adaptive authentication P. Arias-Cabarcos; C. Krupitzer; C. Becker; in ACM Computing Surveys (2019). 52 Art. 80.
    • Beyond position-awareness...
      Beyond position-awareness -- Extending a self-adaptive fall detection system C. Krupitzer; T. Sztyler; J. Edinger; M. Breitbach; H. Stuckenschmidt; C. Becker; in Pervasive and Mobile Computing (2019). 58
    • The Organic Computing Doctoral Dissertation Colloquium: Status and Overview in 2019 C. Krupitzer; S. Tomforde; in Proceedings of the INFORMATIK 2019 (Workshop-Beitr{ä}ge) (2019).
    • Towards a QoS-aware Cyber...
      Towards a QoS-aware Cyber Physical Networking Middleware Architecture M. Brinkschulte; C. Becker; C. Krupitzer; in 1st International Workshop on Middleware for Lightweight, Spontaneous Environments (MISE) @ ACM/IFIP/USENIX International Middleware Conference (2019).
    • DR.SGX: Automated and Adjustable Side-Channel Protection for SGX using Data Location Randomization F. Brasser; S. Capkun; A. Dmitrienko; T. Frassetto; K. Kostiainen; A.-R. Sadeghi; (2019, December).
    • Discrete-Time Analysis of the Blockchain Distributed Ledger Technology S. Geissler; T. Prantl; S. Lange; F. Wamser; T. Hossfeld; in Proceedings of the 31st International Teletraffic Congress (ITC) (2019).
    • Improving the Energy Effi...
      Improving the Energy Efficiency of IoT-Systems and its Software N. Schmitt; in Organic Computing: Doctoral Dissertation Colloquium 2018, S. Tomforde, B. Sick (eds.) (2019).
    • Challenges and Approaches...
      Challenges and Approaches: Forecasting for Autonomic Computing A. Bauer; in Organic Computing: Doctoral Dissertation Colloquium 2018, S. Tomforde, B. Sick (eds.) (2019).
    • DR.SGX: Automated and Adjustable Side-Channel Protection for SGX using Data Location Randomization F. Brasser; S. Capkun; A. Dmitrienko; T. Frassetto; K. Kostiainen; A.-R. Sadeghi; in Annual Computer Security Applications Conference (ACSAC) (2019).
    • Chameleon: A Hybrid, Proa...
      Chameleon: A Hybrid, Proactive Auto-Scaling Mechanism on a Level-Playing Field A. Bauer; (2019, June).
    • SPEC Research Group Newsl...
      SPEC Research Group Newsletter, vol. 2 no. 4 S. Kounev; A. van Hoorn; A. Bauer; N. Herbst; (2019, April).
      Published by Standard Performance Evaluation Corporation (SPEC)
    • Online model learning for...
      Online model learning for self-aware computing infrastructures S. Spinner; J. Grohmann; S. Eismann; S. Kounev; in Journal of Systems and Software (2019). 147 1–16.
    • Towards Testing the Perfo...
      Towards Testing the Performance Influence of Hypervisor Hypercall Interface Behavior L. Beierlieb; L. Iffländer; S. Kounev; A. Milenkoski; in Proceedings of the 10th Symposium on Software Performance 2019 (SSP’19) (2019).
    • Hands Off my Database: Ra...
      Hands Off my Database: Ransomware Detection in Databases through Dynamic Analysis of Query Sequences L. Iffländer; A. Dmitrienko; C. Hagen; M. Jobst; S. Kounev; (2019).
    • Towards Testing the Softw...
      Towards Testing the Software Aging Behavior of Hypervisor Hypercall Interfaces L. Beierlieb; L. Iffländer; A. Milenkoski; C. F. Goncalves; N. Antunes; S. Kounev; in 2019 IEEE International Symposium on Software Reliability Engineering Workshops ({ISSREW}) (2019).
    • Detecting Parametric Depe...
      Detecting Parametric Dependencies for Performance Models Using Feature Selection Techniques J. Grohmann; S. Eismann; S. Elflein; M. Mazkatli; J. von Kistowski; S. Kounev; in 2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS) (2019). 309–322.
      Acceptance Rate: 23.8% (29/122)
    • From the Internet-of-Things to the Internet-of-Thinking-Things S. Kounev; (2019, July).
    • Measuring and Rating the Energy-Efficiency of Servers J. von Kistowski; K.-D. Lange; J. A. Arnold; J. Beckett; H. Block; M. Tricker; S. Sharma; J. Pais; S. Kounev; in Future Generation Computer Systems (2019). 100 579–589.
    • Monitorless: Predicting P...
      Monitorless: Predicting Performance Degradation in Cloud Applications with Machine Learning J. Grohmann; P. K. Nicholson; J. O. Iglesias; S. Kounev; D. Lugones; in Proceedings of the 20th International Middleware Conference (2019). 149–162.
    • Der Weg vom Internet-der-Dinge zum Internet-der-denkenden-Dinge S. Kounev; (2019, June).
    • 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. Abad; J. N. Amaral; P. Tuma; A. Iosup; in IEEE Transactions on Software Engineering (2019). 47(8) 1528–1543.
    • Agile Scalability Engineering: The ScrumScale Method G. Brataas; G. Hanssen; N. Herbst; A. van Hoorn; in IEEE Software (2019). 37(5) 77–85.
      to appear