@article{FeldRochGaboretal., author = {Feld, Sebastian and Roch, Christoph and Gabor, Thomas and Seidel, Christian and Neukart, Florian and Galter, Isabella and Mauerer, Wolfgang and Linnhoff-Popien, Claudia}, title = {A Hybrid Solution Method for the Capacitated Vehicle Routing Problem Using a Quantum Annealer}, series = {Frontiers in ICT}, volume = {6}, journal = {Frontiers in ICT}, publisher = {Frontiers}, doi = {10.3389/fict.2019.00013}, pages = {1 -- 13}, abstract = {he Capacitated Vehicle Routing Problem (CVRP) is an NP-optimization problem (NPO) that has been of great interest for decades for both, science and industry. The CVRP is a variant of the vehicle routing problem characterized by capacity constrained vehicles. The aim is to plan tours for vehicles to supply a given number of customers as efficiently as possible. The problem is the combinatorial explosion of possible solutions, which increases superexponentially with the number of customers. Classical solutions provide good approximations to the globally optimal solution. D-Wave's quantum annealer is a machine designed to solve optimization problems. This machine uses quantum effects to speed up computation time compared to classic computers. The problem on solving the CVRP on the quantum annealer is the particular formulation of the optimization problem. For this, it has to be mapped onto a quadratic unconstrained binary optimization (QUBO) problem. Complex optimization problems such as the CVRP can be translated to smaller subproblems and thus enable a sequential solution of the partitioned problem. This work presents a quantum-classic hybrid solution method for the CVRP. It clarifies whether the implementation of such a method pays off in comparison to existing classical solution methods regarding computation time and solution quality. Several approaches to solving the CVRP are elaborated, the arising problems are discussed, and the results are evaluated in terms of solution quality and computation time.}, language = {en} } @inproceedings{RamsauerBulwahnLohmannetal., author = {Ramsauer, Ralf and Bulwahn, Lukas and Lohmann, Daniel and Mauerer, Wolfgang}, title = {The Sound of Silence : Mining Security Vulnerabilities from Secret Integration Channels in Open-Source Projects}, series = {Proceedings of the 2020 ACM SIGSAC Conference on Cloud Computing Security Workshop: 09.11.2020, virtual event}, booktitle = {Proceedings of the 2020 ACM SIGSAC Conference on Cloud Computing Security Workshop: 09.11.2020, virtual event}, editor = {Zhang, Yinqian and Sion, Radu}, publisher = {ACM}, address = {New York, NY, USA}, isbn = {9781450380843}, doi = {10.1145/3411495.3421360}, pages = {147 -- 157}, abstract = {Public development processes are a key characteristic of open source projects. However, fixes for vulnerabilities are usually discussed privately among a small group of trusted maintainers, and integrated without prior public involvement. This is supposed to prevent early disclosure, and cope with embargo and non-disclosure agreement (NDA) rules. While regular development activities leave publicly available traces, fixes for vulnerabilities that bypass the standard process do not. We present a data-mining based approach to detect code fragments that arise from such infringements of the standard process. By systematically mapping public development artefacts to source code repositories, we can exclude regular process activities, and infer irregularities that stem from non-public integration channels. For the Linux kernel, the most crucial component of many systems, we apply our method to a period of seven months before the release of Linux 5.4. We find 29 commits that address 12 vulnerabilities. For these vulnerabilities, our approach provides a temporal advantage of 2 to 179 days to design exploits before public disclosure takes place, and fixes are rolled out. Established responsible disclosure approaches in open development processes are supposed to limit premature visibility of security vulnerabilities. However, our approach shows that, instead, they open additional possibilities to uncover such changes that thwart the very premise. We conclude by discussing implications and partial countermeasures.}, language = {en} } @inproceedings{MauererSilberhorn, author = {Mauerer, Wolfgang and Silberhorn, Christine}, title = {Numerical Analysis of Parametric Downconversion}, series = {AIP Conference Proceedings}, volume = {1110}, booktitle = {AIP Conference Proceedings}, number = {1}, publisher = {AIP Publishing}, doi = {10.1063/1.3131312}, abstract = {Parametric downconversion (PDC) is a popular technique to produce twin beams of photons that are entangled in multiple degrees of freedom. The generated states form the basis for numerous applications that require entanglement. An exact quantification of this resource is therefore essential, for instance for quantum cryptography that relies on a complete knowledge of the correlation contained in the state. While the determination of an entanglement monotone for the PDC process is only possible analytically in special cases, an exact calculation must usually be performed numerically. Recent work by Mikhailova et al. [2] analyses a certain class of PDC states for which the concurrence entanglement measure can be obtained by an analytical approximation. In this contribution, we analyse the validity of the approximation by comparison with exact numerical methods.}, language = {en} } @misc{Mauerer, author = {Mauerer, Wolfgang}, title = {OSS Community, Health and Ecosystem Research: Theory and, or Theory versus Practice?}, series = {2nd International Workshop on Software Health (SoHEAL@ICSE, Montr{\´e}al), 2019}, journal = {2nd International Workshop on Software Health (SoHEAL@ICSE, Montr{\´e}al), 2019}, language = {en} } @inproceedings{RamsauerLohmannMauerer, author = {Ramsauer, Ralf and Lohmann, Daniel and Mauerer, Wolfgang}, title = {System Software for Manufacturing Systems}, series = {Proc. First European Advances in Digital Transformation Conference, (2018)}, booktitle = {Proc. First European Advances in Digital Transformation Conference, (2018)}, language = {en} } @inproceedings{Mauerer, author = {Mauerer, Wolfgang}, title = {A Virtual Computing Platform for the Internet of Things}, series = {Embedded Linux Conference (San Diego), 2016}, booktitle = {Embedded Linux Conference (San Diego), 2016}, language = {de} } @inproceedings{WinterspergerSafiMauerer, author = {Wintersperger, Karen and Safi, Hila and Mauerer, Wolfgang}, title = {QPU-System Co-Design for Quantum HPC Accelerators?}, series = {Architecture of Computing Systems: 35th International Conference, ARCS 2022, Heilbronn, Germany, September 13-15, 2022, Proceedings}, booktitle = {Architecture of Computing Systems: 35th International Conference, ARCS 2022, Heilbronn, Germany, September 13-15, 2022, Proceedings}, publisher = {Springer}, isbn = {978-3-031-21866-8}, doi = {10.1007/978-3-031-21867-5_7}, pages = {100 -- 114}, abstract = {The use of quantum processing units (QPUs) promises speed-ups for solving computational problems, but the quantum devices currently available possess only a very limited number of qubits and suffer from considerable imperfections. One possibility to progress towards practical utility is to use a co-design approach: Problem formulation and algorithm, but also the physical QPU properties are tailored to the specific application. Since QPUs will likely be used as accelerators for classical computers, details of systemic integration into existing architectures are another lever to influence and improve the practical utility of QPUs. In this work, we investigate the influence of different parameters on the runtime of quantum programs on tailored hybrid CPU-QPU-systems. We study the influence of communication times between CPU and QPU, how adapting QPU designs influences quantum and overall execution performance, and how these factors interact. Using a simple model that allows for estimating which design choices should be subjected to optimisation for a given task, we provide an intuition to the HPC community on potentials and limitations of co-design approaches. We also discuss physical limitations for implementing the proposed changes on real quantum hardware devices.}, language = {en} } @unpublished{MurrMauerer, author = {Murr, Florian and Mauerer, Wolfgang}, title = {McFSM: Near Turing-Complete Finite-State Based Programming}, pages = {11}, abstract = {Finite state machines (FSMs) are an appealing mechanism for simple practical computations: They lend themselves to very effcient and deterministic implementation, are easy to understand, and allow for formally proving many properties of interest. Unfortunately, their computational power is deemed insuffcient for many tasks, and their usefulness has been further hampered by the state space explosion problem and other issues when na{\"i}vely trying to scale them to sizes large enough for many real-life applications. This paper expounds on theory and implementation of multiple coupled fnite state machines (McFSMs), a novel mechanism that combines benefits of FSMs with near Turing-complete, practical computing power, and that was designed from the ground up to support static analysis and reasoning. We develop an elaborate category-theoretical foundation based on non-deterministic Mealy machines, which gives a suitable algebraic description for novel ways of blending di\#erent computing models. Our experience is based on a domain specific language and an integrated development environment that can compile McFSM models to multiple target languages, applying it to use-cases based on industrial scenarios. We discuss properties and advantages of McFSMs, explain how the mechanism can interact with real-world systems and existing code without sacrificing provability, determinism or performance. We discuss how McFSMs can be used to replace and improve on commonly employed programming patterns, and show how their effcient handling of large state spaces enables them to be used as core building blocks for distributed, safety critical, and real-time systems of industrial complexity, which contributes to the longdesired goal of providing executable specifications.}, language = {en} } @inproceedings{MauererKlessingerScherzinger, author = {Mauerer, Wolfgang and Klessinger, Stefan and Scherzinger, Stefanie}, title = {Beyond the badge: reproducibility engineering as a lifetime skill}, series = {Proceedings 4th International Workshop on Software Engineering Education for the Next Generation SEENG 2022, 17 May 2022, Pittsburgh, PA, USA}, booktitle = {Proceedings 4th International Workshop on Software Engineering Education for the Next Generation SEENG 2022, 17 May 2022, Pittsburgh, PA, USA}, publisher = {ACM}, address = {New York, NY, USA}, isbn = {9781450393362}, doi = {10.1145/3528231.3528359}, pages = {1 -- 4}, abstract = {Ascertaining reproducibility of scientific experiments is receiving increased attention across disciplines. We argue that the necessary skills are important beyond pure scientific utility, and that they should be taught as part of software engineering (SWE) education. They serve a dual purpose: Apart from acquiring the coveted badges assigned to reproducible research, reproducibility engineering is a lifetime skill for a professional industrial career in computer science. SWE curricula seem an ideal fit for conveying such capabilities, yet they require some extensions, especially given that even at flagship conferences like ICSE, only slightly more than one-third of the technical papers (at the 2021 edition) receive recognition for artefact reusability. Knowledge and capabilities in setting up engineering environments that allow for reproducing artefacts and results over decades (a standard requirement in many traditional engineering disciplines), writing semi-literate commit messages that document crucial steps of a decision-making process and that are tightly coupled with code, or sustainably taming dynamic, quickly changing software dependencies, to name a few: They all contribute to solving the scientific reproducibility crisis, and enable software engineers to build sustainable, long-term maintainable, software-intensive, industrial systems. We propose to teach these skills at the undergraduate level, on par with traditional SWE topics.}, language = {en} } @inproceedings{WinkerGroppeUotilaetal., author = {Winker, Tobias and Groppe, Sven and Uotila, Valter Johan Edvard and Yan, Zhengtong and Lu, Jiaheng and Maja, Franz and Mauerer, Wolfgang}, title = {Quantum Machine Learning: Foundation, New Techniques, and Opportunities for Database Research}, series = {SIGMOD '23, proceedings of the 2023 International Conference on Management of Data: June 18-23, 2023, Seattle, WA, USA}, booktitle = {SIGMOD '23, proceedings of the 2023 International Conference on Management of Data: June 18-23, 2023, Seattle, WA, USA}, publisher = {ACM}, address = {New York}, doi = {10.1145/3555041.3589404}, pages = {8}, abstract = {In the last few years, the field of quantum computing has experienced remarkable progress. The prototypes of quantum computers already exist and have been made available to users through cloud services (e.g., IBM Q experience, Google quantum AI, or Xanadu quantum cloud). While fault-tolerant and large-scale quantum computers are not available yet (and may not be for a long time, if ever), the potential of this new technology is undeniable. Quantum algorithms havethe proven ability to either outperform classical approaches for several tasks, or are impossible to be efficiently simulated by classical means under reasonable complexity-theoretic assumptions. Even imperfect current-day technology is speculated to exhibit computational advantages over classical systems. Recent research is using quantum computers to solve machine learning tasks. Meanwhile, the database community already successfully applied various machine learning algorithms for data management tasks, so combining the fields seems to be a promising endeavour. However, quantum machine learning is a new research field for most database researchers. In this tutorial, we provide a fundamental introduction to quantum computing and quantum machine learning and show the potential benefits and applications for database research. In addition, we demonstrate how to apply quantum machine learning to the optimization of join order problem for databases.}, language = {en} }