@inproceedings{Mauerer, author = {Mauerer, Wolfgang}, title = {Are any big brothers watching you, and if yes, what can they tell about Debian}, series = {DebConf18 Hsinchu, Taiwan}, booktitle = {DebConf18 Hsinchu, Taiwan}, abstract = {Debian, as a collection of software packages and components, is known to be one of the largest software projects in the history of mankind. Combined with a traceable history over many years, the artefacts created by Debian developers and users make it one of science's favourite targets to quantitatively or qualitatively understand how real-world software development works (or does not), how people collaborate, and many other other related questions. Unfortunately, while scientists make ample use of the resources and artefacts created by FLOSS and friends, the exchange of insights and ideas does not seem to extend in both directions: Developers, users and integrators are often unaware of results obtained in science. This talk will introduce the Debian community to a selection the most important results obtained by scientific (software engineering) research, with a special focus on large-scale socio-technical analysis of projects like Debian, and the possible implications and improvements these may bring to Debian development itself.}, language = {en} } @misc{MauererRamsauer, author = {Mauerer, Wolfgang and Ramsauer, Ralf}, title = {Torturing Git for Fun and Profit}, series = {Microsoft Developer Meetup Regensburg 02.04.2019}, journal = {Microsoft Developer Meetup Regensburg 02.04.2019}, abstract = {In diesem Talk blicken Prof. Dr. Wolfgang Mauerer und Ralf Ramsauer unter die Haube des verteilten Versionskontrollsystems Git. Neben einer genauen Beschreibung der Strukturen und Plumbing APIs, mit denen Git intern Commits erzeugt und verkn{\"u}pft, gehen die Vortragenden auch auf n{\"u}tzliche Features und Standards ein, welche die Kollaborition in großen Open-Source Projekten erleichtern.}, language = {en} } @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} } @unpublished{ThelenSafiMauerer, author = {Thelen, Simon and Safi, Hila and Mauerer, Wolfgang}, title = {Approximating under the Influence of Quantum Noise and Compute Power}, series = {Proceedings of WIHPQC@IEEE QCE}, journal = {Proceedings of WIHPQC@IEEE QCE}, abstract = {The quantum approximate optimisation algorithm (QAOA) is at the core of many scenarios that aim to combine the power of quantum computers and classical high-performance computing appliances for combinatorial optimisation. Several obstacles challenge concrete benefits now and in the foreseeable future: Imperfections quickly degrade algorithmic performance below practical utility; overheads arising from alternating between classical and quantum primitives can counter any advantage; and the choice of parameters or algorithmic variant can substantially influence runtime and result quality. Selecting the optimal combination is a non-trivial issue, as it not only depends on user requirements, but also on details of the hardware and software stack. Appropriate automation can lift the burden of choosing optimal combinations for end-users: They should not be required to understand technicalities like differences between QAOA variants, required number of QAOA layers, or necessary measurement samples. Yet, they should receive best-possible satisfaction of their non-functional requirements, be it performance or other. We determine factors that affect solution quality and temporal behaviour of four QAOA variants using comprehensive density-matrix-based simulations targeting three widely studied optimisation problems. Our simulations consider ideal quantum computation, and a continuum of scenarios troubled by realistic imperfections. Our quantitative results, accompanied by a comprehensive reproduction package, show strong differences between QAOA variants that can be pinpointed to narrow and specific effects. We identify influential co-variables and relevant non-functional quality goals that, we argue, mark the relevant ingredients for designing appropriate software engineering abstraction mechanisms and automated tool-chains for devising quantum solutions from high-level problem specifications.}, language = {en} } @unpublished{PeriyasamyPlingeMutschleretal., author = {Periyasamy, Maniraman and Plinge, Axel and Mutschler, Christopher and Scherer, Daniel D. and Mauerer, Wolfgang}, title = {Guided-SPSA: Simultaneous Perturbation Stochastic Approximation assisted by the Parameter Shift Rule}, abstract = {The study of variational quantum algorithms (VQCs) has received significant attention from the quantum computing community in recent years. These hybrid algorithms, utilizing both classical and quantum components, are well-suited for noisy intermediate-scale quantum devices. Though estimating exact gradients using the parameter-shift rule to optimize the VQCs is realizable in NISQ devices, they do not scale well for larger problem sizes. The computational complexity, in terms of the number of circuit evaluations required for gradient estimation by the parameter-shift rule, scales linearly with the number of parameters in VQCs. On the other hand, techniques that approximate the gradients of the VQCs, such as the simultaneous perturbation stochastic approximation (SPSA), do not scale with the number of parameters but struggle with instability and often attain suboptimal solutions. In this work, we introduce a novel gradient estimation approach called Guided-SPSA, which meaningfully combines the parameter-shift rule and SPSA-based gradient approximation. The Guided-SPSA results in a 15\% to 25\% reduction in the number of circuit evaluations required during training for a similar or better optimality of the solution found compared to the parameter-shift rule. The Guided-SPSA outperforms standard SPSA in all scenarios and outperforms the parameter-shift rule in scenarios such as suboptimal initialization of the parameters. We demonstrate numerically the performance of Guided-SPSA on different paradigms of quantum machine learning, such as regression, classification, and reinforcement learning.}, language = {en} } @inproceedings{ZwingelKediliogluReitelshoeferetal., author = {Zwingel, Maximilian and Kedilioglu, Oguz and Reitelsh{\"o}fer, Sebastian and Mauerer, Wolfgang}, title = {Optimization Problems in Production and Planning: Approaches and Limitations in View of Possible Quantum Superiority}, series = {Annals of Scientific Society for Assembly, Handling and Industrial Robotics 2023}, booktitle = {Annals of Scientific Society for Assembly, Handling and Industrial Robotics 2023}, publisher = {Springer Nature}, isbn = {9783031740091}, language = {en} } @inproceedings{TrespUdluftHeinetal., author = {Tresp, Volker and Udluft, Steffen and Hein, Daniel and Hauptmann, Werner and Leib, Martin and Mutschler, Christopher and Scherer, Daniel D. and Mauerer, Wolfgang}, title = {Workshop Summary: Quantum Machine Learning}, series = {2023 IEEE International Conference on Quantum Computing and Engineering, Bellevue, WA, United States, September 17-22, 2023}, booktitle = {2023 IEEE International Conference on Quantum Computing and Engineering, Bellevue, WA, United States, September 17-22, 2023}, publisher = {IEEE}, doi = {10.1109/QCE57702.2023.10174}, language = {en} } @inproceedings{GogeisslSafiMauerer, author = {Gogeißl, Martin and Safi, Hila and Mauerer, Wolfgang}, title = {Quantum Data Encoding Patterns and their Consequences}, series = {Q-Data '24: Proceedings of the 1st Workshop on Quantum Computing and Quantum-Inspired Technology for Data-Intensive Systems and Applications, June 9 - 15, 2024, Santiago AA Chile}, booktitle = {Q-Data '24: Proceedings of the 1st Workshop on Quantum Computing and Quantum-Inspired Technology for Data-Intensive Systems and Applications, June 9 - 15, 2024, Santiago AA Chile}, publisher = {ACM}, isbn = {979-8-4007-0553-3}, doi = {10.1145/3665225.3665446}, pages = {27 -- 37}, abstract = {The use of quantum processing units (QPUs) promises speed-ups for solving computational problems, in particular for discrete optimisation. While a few groundbreaking algorithmic approaches are known that can provably outperform classical computers, we observe a scarcity of programming abstractions for constructing efficient quantum algorithms. A good fraction of the literature that addresses solving concrete problems related to database management concentrates on casting them as quadratic unconstrained binary optimisation problems (QUBOs), which can then, among others, be processed on gate-based machines (using the quantum approximate optimisation algorithm), or quantum annealers. A critical aspect that affects efficiency and scalability of either of these approaches is how classical data are loaded into qubits, respectively how problems are encoded into QUBO representation. The effectiveness of encodings is known to be of crucial importance for quantum computers, especially since the amount of available qubits is strongly limited in the era of noisy, intermediate-size quantum computers. In this paper, we present three encoding patterns, discuss their impact on scalability, and their ease of use. We consider the recreational (yet computationally challenging) Sudoku problem and its reduction to graph colouring as an illustrative example to discuss their individual benefits and disadvantages. Our aim is enable database researchers to choose an appropriate encoding scheme for their purpose without having to acquire in-depth knowledge on quantum peculiarities, thus easing the path towards applying quantum acceleration on data management systems.}, language = {en} } @unpublished{JungKrumkeSchrothetal., author = {Jung, Matthias and Krumke, Sven O. and Schroth, Christof and Lobe, Elisabeth and Mauerer, Wolfgang}, title = {QCEDA: Using Quantum Computers for EDA}, abstract = {The field of Electronic Design Automation (EDA) is crucial for microelectronics, but the increasing complexity of Integrated Circuits (ICs) poses challenges for conventional EDA: Corresponding problems are often NP-hard and are therefore in general solved by heuristics, not guaranteeing optimal solutions. Quantum computers may offer better solutions due to their potential for optimization through entanglement, superposition, and interference. Most of the works in the area of EDA and quantum computers focus on how to use EDA for building quantum circuits. However, almost no research focuses on exploiting quantum computers for solving EDA problems. Therefore, this paper investigates the feasibility and potential of quantum computing for a typical EDA optimization problem broken down to the Min-k-Union problem. The problem is mathematically transformed into a Quadratic Unconstrained Binary Optimization (QUBO) problem, which was successfully solved on an IBM quantum computer and a D-Wave quantum annealer.}, language = {en} } @incollection{Mauerer, author = {Mauerer, Wolfgang}, title = {Superoperators for Quantum Software Engineering}, series = {Quantum Software: Aspects of Theory and System Design}, booktitle = {Quantum Software: Aspects of Theory and System Design}, editor = {Exman, Iaakov and Perez-Castillo, Ricardo and Piattini, Mario and Felderer, Michael}, publisher = {Springer Nature}, issn = {978-3-031-64136-7}, doi = {10.1007/978-3-031-64136-7_3}, abstract = {As implementations of quantum computers grow in size and maturity, the question of how to program this new class of machines is attracting increasing attention in the software engineering domain. Yet, many questions from how to design expressible quantum languages augmented with formal semantics via implementing appropriate optimizing compilers to abstracting details of machine properties in software systems remain challenging. Performing research at this intersection of quantum computing and software engineering requires sufficient knowledge of the physical processes underlying quantum computations, and how to model these. In this chapter, we review a superoperator-based approach to quantum dynamics, as it can provide means that are sufficiently abstract, yet concrete enough to be useful in quantum software and systems engineering, and outline how it is used in several important applications in the field.}, language = {en} } @inproceedings{SafiWinterspergerMauerer, author = {Safi, Hila and Wintersperger, Karen and Mauerer, Wolfgang}, title = {Influence of HW-SW-Co-Design on Quantum Computing Scalability}, series = {2023 IEEE International Conference on Quantum Software (QSW), Chicago, IL, USA, 02-08 July 2023}, booktitle = {2023 IEEE International Conference on Quantum Software (QSW), Chicago, IL, USA, 02-08 July 2023}, publisher = {IEEE}, isbn = {979-8-3503-0479-4}, doi = {10.1109/QSW59989.2023.00022}, pages = {104 -- 115}, abstract = {The use of quantum processing units (QPUs) promises speed-ups for solving computational problems. Yet, current devices are limited by the number of qubits and suffer from significant imperfections, which prevents achieving quantum advantage. To step towards practical utility, one approach is to apply hardware-software co-design methods. This can involve tailoring problem formulations and algorithms to the quantum execution environment, but also entails the possibility of adapting physical properties of the QPU to specific applications. In this work, we follow the latter path, and investigate how key figures— circuit depth and gate count—required to solve four cornerstone NP-complete problems vary with tailored hardware properties. Our results reveal that achieving near-optimal performance and properties does not necessarily require optimal quantum hardware, but can be satisfied with much simpler structures that can potentially be realised for many hardware approaches.m Using statistical analysis techniques, we additionally identify an underlying general model that applies to all subject problems. This suggests that our results may be universally applicable to other algorithms and problem domains, and tailored QPUs can find utility outside their initially envisaged problem domains. The substantial possible improvements nonetheless highlight the importance of QPU tailoring to progress towards practical deployment and scalability of quantum software.}, language = {en} }