Real Arithmetic in TLAPM
Ovini V.W. Gunasekera, Andrew Sogokon, Antonios Gouglidis, and Neeraj Suri
Proc. of NFM, 2024
Muhammad Waseem, Teerath Das, Aakash Ahmad, Mahdi Fehmideh, Peng Liang, Tommi Mikkonen (2024) ChatGPT as a Software Development Bot: A Project-based Study. In: 19th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE’2024) (accepted)
Muhammad Waseem, Teerath Das, Aakash Ahmad, Peng Liang, Tommi Mikkonen 2024) Issues and Their Causes in WebAssembly Applications: An Empirical Study. In: International Conference on Evaluation and Assessment in Software Engineering (EASE) (accepted)
Moussa, A. M., Abdou, S., Elsayed, K. M., Rashwan, M., Asif, A., Khatoon, S., Alshamari, M. A. (2024). Enhanced Arabic disaster data classification using domain adaptation. PLoS one, 19(4), e0301255.
Krishnendu Chatterjee, Amir Kafshdar Goharshady, Tobias Meggendorfer, and Đorđe Žikelić (2024) Quantitative Bounds on Resource Usage of Probabilistic Programs (OOPSLA)
Roman Andriushchenko, Alexander Bork, Carlos E. Budde, Milan Češka, Ernst Moritz Hahn, Arnd Hartmanns, Bryant Israelsen, Nils Jansen, Joshua Jeppson, Sebastian Junges, Maximilian A. Köhl, Bettina Könighofer, Jan Křetínský, Tobias Meggendorfer, David Parker, Stefan Pranger, Tim Quatmann, Enno Ruijters, Landon Taylor, Matthias Volk, Maximilian Weininger, and Zhen Zhang (2023) Tools at the Frontiers of Quantitative Verification: QComp 2023 Competition Report. In: TOOLympics
David Georg Reichelt, Lubomir Bulej, Reiner Jung and André van Hoorn (2024) Overhead Comparison of Instrumentation Frameworks. In: Companion of the International Conference on Performance Engineering
UNICAD: A Unified Approach for Attack Detection, Noise Reduction and Novel Class Identification
Alvaro Lopez Pellcier, Kittipos Giatgong, Yi Li, Neeraj Suri, Plamen Angelov
Proc. of IJCNN, 2024
Lerch, P., Scheller, F., Reichelt, D. G., Menzel, K., & Bruckner, T. (2024). Electricity cost and CO2 savings potential for chlor-alkali electrolysis plants: Benefits of electricity price dependent demand response. Applied Energy, 355, 122263.
Hu-Bolz, J., Reed, M., Zhang, K., Liu, Z., & Hu, J. (2024). Federated data acquisition market: Architecture and a mean-field based data pricing strategy. High-Confidence Computing, 100232.
Kukushkin, M., Bogdan, M., Schmid, T. (2024) BiMAE – A Bimodal Masked Autoencoder Architecture for Single-Label Hyperspectral Image Classification. In: Perception Beyond the Visible Spectrum workshop series (IEEE PBVS) (accepted)
Boer, M.H.T., Smit, Q.T.S., Meyer-Vitali, A., Bekkum, M.A., Schmid, T. (2024) Modular Design Patterns for Generative Neuro-Symbolic Systems. In: Generative Neuro-Symbolic AI Workshop, ESWC 2024 (accepted)
Schuering, B., Schmid, T. (2024) What Can Computers Do Now? Dreyfus Revisited for the 3rd Wave of Artificial intelligence. In: AAAI 2024 Spring Symposium on Empowering Machine Learning and Large Language Models with Domain and Commonsense Knowledge (AAAI-MAKE 2024), Stanford University, Palo Alto, California, USA, 2024. (in press)
Enabling Multi-Layer Threat Analysis in Dynamic Cloud Environments
Salman Manzoor, Antonios Gouglidis, Matthew Bradbury and Neeraj Suri
IEEE Transactions of Cloud Computing, 2024
Error Propagation Analysis for Multithreaded Programs: An Empirical Approach
Stefan Winter, Abraham Chan, Habib Saissi, Karthik Pattabiraman, Neeraj Suri
arXiv, 2024
An Empirical Study of Reflection Attacks Using NetFlow Data
Edward Chuah, Neeraj Suri
Cybersecurity, Springer Open, 2024
Self-Supervised Representation Learning for Adversarial Attack Detection
Yi Li , Plamen Angelov, Neeraj Suri
Proc. of ECCV, 2024
Investigating Location-Aware Advertisements in Anycast IP Networks
Savvas Kastanakis, Ioana Livadariu, Vasileios Giotsas, Neeraj Suri
Proc. of ANRW, 2024
Rethinking Self-Supervised Learning for Cross-Domain Adversarial Sample Recovery
Yi Li, Plamen Angelov, Neeraj Suri
Proc. of IJCNN, 2024
Federated Adversarial Learning for Robust Autonomous Landing Runway Detection
Yi Li, Plamen Angelov, Zhengxin Yu, Alvaro Lopez Pellicer, Neeraj Suri
Proc. of ICANN, 2024
Erichsmeier, F., Kukushkin, M., Fiedler, J., Enders, M., Goertz, S., Bogdan, M., Schmid, T., & Kaschuba, R. (2024) Automating the Purity Analysis of Oilseed Rape Through Usage of Hyperspectral Imaging. Proceedings of SPIE Photonics West 2024, San Francisco, USA
Real Arithmetic in TLAPM
Ovini V.W. Gunasekera, Andrew Sogokon, Antonios Gouglidis, and Neeraj Suri
Proc. of NFM, 2024
Cloud Security Requirement Based Threat Analysis
Ahmed Taha, Alexander Lawall, and Neeraj Suri
Proc. of IEEE ICNC, 2023
David Georg Reichelt, Reiner Jung, André van Hoorn (2023) More is Less in Kieker? The Paradox of No Logging Being Slower Than Logging. Symposium on Software Performance
Kukushkin, M., Bogdan, M., Schmid, T. (2023) On Optimizing Morphological Neural Networks for Hyperspectral Image Classification. Proceedings of the 17th International Conference on Machine Vision (ICMV), Yerevan, Armenia
Hildesheim, H., Holoyad, T., Schmid, T. (2023) Machine Learning in AI Factories – Five Theses for Developing, Managing and Maintaining Data-driven Artificial Intelligence at Large Scale. Information Technology 65(4-5):218–227
Zhang, B., Liang, P., Zhou, X., Ahmad, A., Waseem, M. (2023) Demystifying Practices, Challenges and Expected Features of Using GitHub Copilot. International Journal of Software Engineering and Knowledge Engineering (2023):1-20
Aljedaani, B., Ahmad, A., Zahedi, M., Babar, M. A. (2023). An empirical study on secure usage of mobile health apps: The attack simulation approach. Information and Software Technology, 163, 107285.
Khan, A. A., Ahmad, A., Waseem, M., Liang, P., Fahmideh, M., Mikkonen, T., Abrahamsson, P. (2023). Software architecture for quantum computing systems—A systematic review. Journal of Systems and Software, 201, 111682.
Khan, A. A., Akbar, M. A., Fahmideh, M., Liang, P., Waseem, M., Ahmad, A., Niazi, M., Abrahamsson, P. (2023). AI ethics: an empirical study on the views of practitioners and lawmakers. IEEE Transactions on Computational Social Systems.
Ahmad, A., Waseem, M., Liang, P., Fahmideh, M., Aktar, M. S., Mikkonen, T. (2023). Towards human-bot collaborative software architecting with ChatGPT. 27th International Conference on Evaluation and Assessment in Software Engineering, pp. 279-285
Khan, A. A., Ahmad, A., Waseem, M., Liang, P., Fahmideh, M., Mikkonen, T., Abrahamsson, P. (2023). Software architecture for quantum computing systems—A systematic review. Journal of Systems and Software, 201, 111682.
Aljedaani, B., Ahmad, A., Zahedi, M., Babar, M. A. (2023). End-users’ knowledge and perception about security of clinical mobile health apps: A case study with two Saudi Arabian mHealth providers. Journal of Systems and Software, 195, 111519.
Khan, A. A., Akbar, M. A., Ahmad, A., Fahmideh, M., Shameem, M., Lahtinen, V., Waseem, M., Mikkonen, T. (2023). Agile Practices for Quantum Software Development: Practitioners’ Perspectives. 2023 IEEE International Conference on Quantum Software (QSW) (pp. 9-20).
Khan, A. A., Akbar, M. A., Fahmideh, M., Liang, P., Waseem, M., Ahmad, A., Niazi, M., Abrahamsson, P. (2023). AI ethics: an empirical study on the views of practitioners and lawmakers. IEEE Transactions on Computational Social Systems.
Alghareeb, M., Albesher, A. S., Asif, A. (2023). Studying users’ perceptions of COVID-19 mobile applications in Saudi Arabia. Sustainability, 15(2), 956.
Caminati, M. B., Bowles, J. K. F. (2023). Representation Theorems Obtained by Miningacross Web Sources for Hints. Proceedings of the 6th International Conference on Information and Computer Technologies (ICICT), Raleigh, NC, USA, pp. 203-210
Caminati, M. B. (2023). Isabelle Formalisation of Original Representation Theorems. In: Dubois, C. & Kerber M. (Eds.) Intelligent Computer Mathematics, Springer Nature, Switzerland, ISBN 978-3-031-42753-4, pp. 98-112
Al-Naday, M., Thomos, N., Hu, J., Volckaert, B., de Turck, F., Reed, M. J. (2023). Service-Based, Multi-Provider, Fog Ecosystem With Joint Optimization of Request Mapping and Response Routing, IEEE Transactions on Services Computing, 16(3):2203-2214
Nalon, C., Hustadt, U., Papacchini, F., Dixon, C. (2023). Buy One Get 14 Free: Evaluating Local Reductions for Modal Logic. In: Pientka, B., Tinelli, C. (eds) Automated Deduction – CADE 29. CADE 2023. Lecture Notes in Computer Science, vol 14132. Springer, Cham.
Reichelt, D. G., Kühne, S., Hasselbring, W. (2023). Towards Solving the Challenge of Minimal Overhead Monitoring. In Companion of the 2023 ACM/SPEC International Conference on Performance Engineering, pp. 381-388.
Mendikowski, M., Schindler, B., Schmid, T., Möller, R., & Hartwig, M. (2023). Improved Techniques for Training Tabular GANs Using Cramer’s V Statistics. Proceedings of the Canadian Conference on Artificial Intelligence.
Horokh, O., Böhm, M., Schmid, T. (2023) A Parallelized Genitor II Implementation For Training Semiring Neural Networks. Proceedings of the Companion Conference on Genetic and Evolutionary Computation, pp. 287-290.
Schmid, T. (2023). A Systematic and Efficient Approach to the Design of Modular Hybrid AI Systems. Proceedings of the AAAI 2023 Spring Symposium on Challenges Requiring the Combination of Machine Learning and Knowledge Engineering (AAAI-MAKE 2023).
Walton, S. P., Vincalek, J., Rahat, A. A. M., Stovold, J., Evans, B.J. (2023) Genetic Car Designer: A Large-Scale User Study of a Mixed-Initiative Design Tool, Proceedings of the AISB Convention 2023, ISBN 978-1-908187-85-7, pp.115-121
Stovold, J. (2023) Neural Cellular Automata Can Respond to Signals. Proceedings of ALIFE 2023: Ghost in the Machine, 2023 Artificial Life Conference. pp. 5-14, Sapporo, Japan
Robotics – Special Issue on Agents and Robots for Reliable Engineered Autonomy 2023. Guest Editors: Ferrando, A., Cardoso, R. C., Papacchini, F., Askarpour, M., Dennis, L. A.
Schmid, T.. Constructivist Machine Learning. In: Pascal Hitzler, Md Kamruzzaman Sarker, Aaron Eberhart (Eds.) Compendium of Neuro-Symbolic Artificial Intelligence. IOS Press, pp.
114–124, 2023.
Schmid, T., Hildesheim, W., Holoyad, T (2023) Künstliche Intelligenz managen und verstehen – Der Praxis-Wegweiser für Entscheidungsträger, Entwickler und Regulierer. 1st Ed., Beuth
Publishers, Berlin.
Waseem, M., Das, T., Ahmad, A., Liang, P., Mikkonen, T. (2023). Understanding the Issues and Causes in WebAssembly Application Development: A Mining-based Study. arXiv preprint arXiv:2311.00646.
Waseem, M., Das, T., Ahmad, A., Fehmideh, M., Liang, P., Mikkonen, T. (2023). Using ChatGPT throughout the Software Development Life Cycle by Novice Developers. arXiv preprint arXiv:2310.13648.
Zhang, B., Liang, P., Zhou, X., Ahmad, A., Waseem, M. (2023). Demystifying Practices, Challenges and Expected Features of Using GitHub Copilot. arXiv preprint arXiv:2309.05687.
Ahmad, A., Altamimi, A. B., Aqib, J. (2023). A Reference Architecture for Quantum Computing as a Service. arXiv preprint arXiv:2306.04578.
Ahmad, A., Waseem, M., Liang, P., Fehmideh, M., Khan, A. A., Reichelt, D. G., Mikkonen, T. (2023). Engineering Software Systems for Quantum Computing as a Service: A Mapping
Study. arXiv preprint arXiv:2303.14713.
Waseem, M., Liang, P., Ahmad, A., Khan, A. A., Shahin, M., Abrahamsson, P., Rezaei Nasab,A., Mikkonen, T. (2023). Understanding the Issues, Their Causes and Solutions in
Microservices Systems: An Empirical Study. arXiv preprint arXiv:2302.01894.
Waseem, M., Ahmad, A., Liang, P., Fehmideh, M., Abrahamsson, P., Mikkonen, T. (2023).
Conducting Systematic Literature Reviews with ChatGPT. arXiv preprint arXiv:4777098
Hu-Bolz, J.; Farrahi, K.; Cebrian, M. (2023). Beyond the Surface of Digital Contact Tracing: Delving into the Interconnected World of Technology, Individuals, and Society. TechRxiv.
Security Challenges When Space Merges With Cyberspace
Vijay Varadharajan, Neeraj Suri
ELSEVIER Space Policy, 2023
Privacy-preserving Decentralized Federated Learning over Time-varying Communication Graph
Yang Lu, Zhengxin Yu, and Neeraj Suri
ACM Transactions on Privacy and Security, 2023
Compilation as a Defense: Enhancing DL Model Attack Robustness via Tensor Optimization.
Stefan Trawicki, William Hackett, Lewis Birch, Neeraj Suri, Peter Garraghan
Proc. of CAMLIS, 2023
Model Leeching: An Extraction Attack Targeting LLMs.
Lewis Birch, William Hackett, Stefan Trawicki, Neeraj Suri, Peter Garraghan
Proc. of CAMLIS, 2023
Fuzzy Detectors Against Adversarial Attacks.
Yi Li, Plamen Angelov, Neeraj Suri
Proc. of IEEE SSCI, 2023
20 Years of Inferring Inter-domain Routing Policies.
Savvas Kastanakis, Vasileios Giotsas, Ioana Livadariu, Neeraj Suri
Proc. of ACM IMC, 2023
Federated Meta Learning for Visual Navigation in GPS-denied Urban Airspace.
Burak Yuksek, Zhengxin Yu, Neeraj Suri, Gokhan Inalhan
Proc. of DASC, 2023
RAFL: A Robust and Adaptive Federated Meta-Learning Framework Against Adversaries.
Zhengxin Yu, Yang Lu, and Neeraj Suri
Proc. of IEEE MASS, 2023
Domain Generalization and Feature Fusion for Cross-domain Imperceptible Adversarial Attack Detection.
Yi Li, Yang Lu, Plamen Angelov and Neeraj Suri
Proc. of IEEE IJCNN, 2023
A Survey of Log-Correlation Tools for Failure Diagnosis and Prediction in Cluster Systems
Edward Chuah, Arshad Jhumka, Miroslaw Malek and Neeraj Suri
IEEE Access, 2022
PPFM: An Adaptive and Hierarchical Peer-to-Peer Federated Meta-Learning Framework.
Zhengxin Yu, Yang Lu, Plamen Angelov and Neeraj Suri
Proc. of IEEE MSN, 2022
Effectiveness of Moving Target Defense Techniques to
Disrupt Attacks in the Cloud.
Salman Manzoor, Antonios Gouglidis Matthew Bradbury and Neeraj Suri
Proc. of ACM CCS (Poster), 2022
Multi-Layer Threat Analysis of the Cloud
Salman Manzoor, Antonios Gouglidis Matthew Bradbury and Neeraj Suri
Proc. of ACM CCS (Poster), 2022
Understanding the confounding factors of inter-domain routing modeling
Savvas Kastanakis, Vasilios Giotsas and Neeraj Suri
Proc. of ACM IMC (Poster), 2022
Similarity-based Deep Neural Network to Detect Imperceptible Adversarial Attacks
Eduardo Soares, Plamen Angelov and Neeraj Suri
Proc. of IEEE CIDUE/SSCI, 2022
Towards Effective Performance Fuzzing
Yiqun Chen, Matthew Bradbury and Neeraj Suri
Proc. of ISSRE (FA), 2022
SlowCoach: Mutating Code to Simulate Performance Bugs
Yiqun Chen, Oliver Schwahn, Roberto Natella, Matthew Bradbury and Neeraj Suri
Proc. of ISSRE, 2022
Fahmideh, M., Grundy, J., Ahmad, A., Shen, J., Yan, J., Mougouei, D., Wang, P., Ghose, A. Gunawardana, A., Aickelin, U., Abedin. B. (2022). Engineering Blockchain-based Software Systems: Foundations, Survey, and Future Directions. ACM Comput. Surv. 55(6).
Anjum, N., Alibakhshikenari, M., Rashid, J., Jabeen, F., Asif, A., Mohamed, E. M., & Falcone, F. (2022). IoT-Based COVID-19 Diagnosing and Monitoring Systems: A Survey. IEEE Access, 10, 87168-87181.
Reichelt, D. G., Kühne, S., Hasselbring, W. (2022) Automated Identification of Performance Changes at Code Level. Proceedings of 2022 IEEE 22nd International Conference on Software Quality, Reliability and Security (QRS), Guangzhou, China, pp. 916-925
Reichelt, D. G., Krauß, H., Kühne, S., Hasselbring, W. (2022) Generic Performance Measurement in CI: The GeoMap Case Study. Proceedings of 13th Symposium on Software Performance, Stuttgart, Germany
Schindler, B., Günzel, D., Schmid, T. (2022) Neural Noise Module: Automated Error Modeling using Adversarial Neural Networks. Intern. Conference on Bioelectromagnetism, Electrical Bioimpedance, and Electrical Impedance Tomography, pp. 191-194.
Ferrando, A., Cardoso, R. C., Farrell, M., Luckcuck, M., Papacchini, F., Fisher, M., & Mascardi, V. (2022). Bridging the gap between single-and multi-model predictive runtime verification. Formal Methods in System Design, 1-33.
Cardoso, R. C., Ferrando, A., Papacchini, F., Askarpour, M., & Dennis, L. A. (2022). Proceedings of the Second Workshop on Agents and Robots for reliable Engineered Autonomy. arXiv preprint arXiv:2207.09058.
Papacchini, F., Nalon, C., Hustadt, U., & Dixon, C. (2022). Local is Best: Efficient Reductions to Modal Logic K. Journal of Automated Reasoning, 1-28.
Nalon, C., Hustadt, U., Papacchini, F., & Dixon, C. (2022). Local Reductions for the Modal Cube. In International Joint Conference on Automated Reasoning (pp. 486-505). Springer, Cham.
Hu, J., Reed, M., Thomos, N., Al-Naday, M. F., & Yang, K. (2022). A Dynamic Service Trading in a DLT-Assisted Industrial IoT Marketplace. IEEE Transactions on Network and Service Management.
Schmid, T., Grosse, F. (2022) Extracting Knowledge with Constructivist Machine Learning: Conceptual and Procedural Models. In: Proceedings of the AAAI 2022 Spring Symposium on Combining Machine Learning and Knowledge Engineering (AAAI-MAKE 2022), Stanford University, Palo Alto, California, USA.
Schindler, B., Günzel, D., Schmid, T. (2022) Neural Noise Module: Automated Error Modeling using Adversarial Neural Networks. In: Proceedings of the International Conference of Bioelectromagnetism, Electrical Bioimpedance, and Electrical Impedance Tomography (ICBEM) (2022)
PCaaD: Towards automated determination and exploitation of industrial systems
Benjamin Green, Richard Derbyshire, MarinaKrotofil, William Knowles, Daniel Prince, Neeraj Suri
Journal of Computers & Security, 2021
Failure Diagnosis for Cluster Systems using Partial Correlations
Edward Chuah, Arshad Jhumka, Samantha Alt, Todd Evans, Neeraj Suri
Proc. of ISPA, 2021
Challenges in Identifying Network Attacks Using Netflow Data
Edward Chuah, Neeraj Suri, Arshad Jhumka and Samantha Alt
Proc. of NCA, 2021
Fast Kernel Error Propagation Analysis in Virtualized Environments
Nicolas Coppik, Oliver Schwahn and Neeraj Suri
Proc. of ICST, 2021
Basu, A., Stapleton, G., Linker, S., Legg, C., Manalo, E., & Viana, P. (Eds.). (2021). Diagrammatic Representation and Inference: 12th International Conference, Diagrams 2021, Virtual, September 28–30, 2021, Proceedings (Vol. 12909). Springer Nature.
Linker, S. (2021, September). Natural Deduction for Intuitionistic Euler-Venn Diagrams. In International Conference on Theory and Application of Diagrams (pp. 529-533). Springer, Cham.
Basu, A., Stapleton, G., Linker, S., Legg, C., Manalo, E., & Viana, P. (Eds.). (2021). Diagrammatic Representation and Inference: 12th International Conference, Diagrams 2021, Virtual, September 28–30, 2021, Proceedings (Vol. 12909). Springer Nature.
Linker, S., Papacchini, F., & Sevegnani, M. (2021). Finite Models for a Spatial Logic with Discrete and Topological Path Operators. Leibniz International Proceedings in Informatics, LIPIcs, 202.
Cardoso, R. C., Ferrando, A., Papacchini, F., Luckcuck, M., Linker, S., & Payne, T. R. (2021). MLFC: From 10 to 50 Planners in the Multi-Agent Programming Contest. In Multi-Agent Progamming Contest (pp. 82-107). Springer, Cham.
Schindler, B., Günzel, B., Schmid, T. (2021) Transcending Two-Path Impedance Spectroscopy with Machine Learning: A Computational Study on Modeling and Quantifying Electric Bipolarity of Epithelia. International Journal on Advances in Life Sciences 13(3-4), pp. 134-148
Böhm, M., Schmid, T. (2021) An Algorithmic Approach to Establish a Lower Bound for the Size of Semiring Neural Networks. Proceedings of the 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), pp. 311–316,
Schmid, T., Hildesheim, W., Holoyad, T., Schumacher, K. (2021) The AI Methods, Capabilities and Criticality Grid – A Three-Dimensional Classification Scheme for Artificial Intelligence Applications. Künstliche Intelligenz. https://doi.org/10.1007/s13218-021-00736-4
Schmid, T. (2021) Batch-like Online Learning for More Robust Hybrid Artificial Intelligence: Deconstruction as a Machine Learning Process. Proceedings of the AAAI 2021 Spring Symposium on Combining Machine Learning and Knowledge Engineering (AAAI-MAKE 2021). Stanford University, Palo Alto, California, USA, March 22-24, 2021.
