@article{60377,
  abstract     = {{<jats:p>We present a guaranteed quality mesh generation algorithm for the curvilinear triangulation of planar domains with piecewise polynomial boundary. The resulting mesh consists of higher-order triangular elements which are not only regular (i.e., with injective geometric map) but respect strict bounds on quality measures like scaled Jacobian and MIPS distortion. This also implies that the curved triangles' inner angles are bounded from above and below. These are key quality criteria, for instance, in the field of finite element analysis. The domain boundary is reproduced exactly, without geometric approximation error. The central idea is to transform the curvilinear meshing problem into a linear meshing problem via a carefully constructed transformation of bounded distortion, enabling us to leverage key results on guaranteed-quality straight-edge triangulation. The transformation is based on a simple yet general construction and observations about convergence properties of curves under subdivision. Our algorithm can handle arbitrary polynomial order, arbitrarily sharp corners, feature and interface curves, and can be executed using rational arithmetic for strict reliability.</jats:p>}},
  author       = {{Mandad, Manish and Campen, Marcel}},
  issn         = {{0730-0301}},
  journal      = {{ACM Transactions on Graphics}},
  number       = {{4}},
  pages        = {{1--14}},
  publisher    = {{Association for Computing Machinery (ACM)}},
  title        = {{{Guaranteed-quality higher-order triangular meshing of 2D domains}}},
  doi          = {{10.1145/3450626.3459673}},
  volume       = {{40}},
  year         = {{2021}},
}

@article{60378,
  abstract     = {{<jats:p>We describe an efficient algorithm to compute a discrete metric with prescribed Gaussian curvature at all interior vertices and prescribed geodesic curvature along the boundary of a mesh. The metric is (discretely) conformally equivalent to the input metric. Its construction is based on theory developed in [Gu et al. 2018b] and [Springborn 2020], relying on results on hyperbolic ideal Delaunay triangulations. Generality is achieved by considering the surface's intrinsic triangulation as a degree of freedom, and particular attention is paid to the proper treatment of surface boundaries. While via a double cover approach the case with boundary can be reduced to the case without boundary quite naturally, the implied symmetry of the setting causes additional challenges related to stable Delaunay-critical configurations that we address explicitly. We furthermore explore the numerical limits of the approach and derive continuous maps from the discrete metrics.</jats:p>}},
  author       = {{Campen, Marcel and Capouellez, Ryan and Shen, Hanxiao and Zhu, Leyi and Panozzo, Daniele and Zorin, Denis}},
  issn         = {{0730-0301}},
  journal      = {{ACM Transactions on Graphics}},
  number       = {{6}},
  pages        = {{1--16}},
  publisher    = {{Association for Computing Machinery (ACM)}},
  title        = {{{Efficient and robust discrete conformal equivalence with boundary}}},
  doi          = {{10.1145/3478513.3480557}},
  volume       = {{40}},
  year         = {{2021}},
}

@article{60376,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>A homeomorphism between two surfaces not only defines a (continuous and bijective) geometric correspondence of points but also (by implication) an identification of topological features, i.e. handles and tunnels, and how the map twists around them. However, in practice, surface maps are often encoded via sparse correspondences or fuzzy representations that merely approximate a homeomorphism and are therefore inherently ambiguous about map topology. In this work, we show a way to infer topological information from an imperfect input map between two shapes. In particular, we compute a homology map, a linear map that transports homology classes of cycles from one surface to the other, subject to a global consistency constraint. Our inference robustly handles imperfect (e.g., partial, sparse, fuzzy, noisy, outlier‐ridden, non‐injective) input maps and is guaranteed to produce homology maps that are compatible with true homeomorphisms between the input shapes. Homology maps inferred by our method can be directly used to transfer homological information between shapes, or serve as foundation for the construction of a proper homeomorphism guided by the input map, e.g., via compatible surface decomposition.</jats:p>}},
  author       = {{Born, Janis and Schmidt, Patrick and Campen, Marcel and Kobbelt, Leif}},
  issn         = {{0167-7055}},
  journal      = {{Computer Graphics Forum}},
  number       = {{5}},
  pages        = {{193--204}},
  publisher    = {{Wiley}},
  title        = {{{Surface Map Homology Inference}}},
  doi          = {{10.1111/cgf.14367}},
  volume       = {{40}},
  year         = {{2021}},
}

@article{60374,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>We present a robust and fast method for the creation of conforming quad layouts on surfaces. Our algorithm is based on the quantization of a T‐mesh, i.e. an assignment of integer lengths to the sides of a non‐conforming rectangular partition of the surface. This representation has the benefit of being able to encode an infinite number of layout connectivity options in a finite manner, which guarantees that a valid layout can always be found. We carefully construct the T‐mesh from a given seamless parametrization such that the algorithm can provide guarantees on the results' quality. In particular, the user can specify a bound on the angular deviation of layout edges from prescribed directions. We solve an integer linear program (ILP) to find a coarse quad layout adhering to that maximal deviation. Our algorithm is guaranteed to yield a conforming quad layout free of T‐junctions together with bounded angle distortion. Our results show that the presented method is fast, reliable, and achieves high quality layouts.</jats:p>}},
  author       = {{Lyon, Max and Campen, Marcel and Kobbelt, Leif}},
  issn         = {{0167-7055}},
  journal      = {{Computer Graphics Forum}},
  number       = {{2}},
  pages        = {{305--314}},
  publisher    = {{Wiley}},
  title        = {{{Quad Layouts via Constrained T‐Mesh Quantization}}},
  doi          = {{10.1111/cgf.142634}},
  volume       = {{40}},
  year         = {{2021}},
}

@article{60375,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>A common approach to automatic quad layout generation on surfaces is to, in a first stage, decide on the positioning of irregular layout vertices, followed by finding sensible layout edges connecting these vertices and partitioning the surface into quadrilateral patches in a second stage. While this two‐step approach reduces the problem's complexity, this separation also limits the result quality. In the worst case, the set of layout vertices fixed in the first stage without consideration of the second may not even permit a valid quad layout. We propose an algorithm for the creation of quad layouts in which the initial layout vertices can be adjusted in the second stage. Whenever beneficial for layout quality or even validity, these vertices may be moved within a prescribed radius or even be removed. Our algorithm is based on a robust quantization strategy, turning a continuous T‐mesh structure into a discrete layout. We show the effectiveness of our algorithm on a variety of inputs.</jats:p>}},
  author       = {{Lyon, Max and Campen, Marcel and Kobbelt, Leif}},
  issn         = {{0167-7055}},
  journal      = {{Computer Graphics Forum}},
  number       = {{5}},
  pages        = {{169--180}},
  publisher    = {{Wiley}},
  title        = {{{Simpler Quad Layouts using Relaxed Singularities}}},
  doi          = {{10.1111/cgf.14365}},
  volume       = {{40}},
  year         = {{2021}},
}

@article{25212,
  abstract     = {{Finding a good query plan is key to the optimization of query runtime. This holds in particular for cost-based federation
engines, which make use of cardinality estimations to achieve this goal. A number of studies compare SPARQL federation engines across different performance metrics, including query runtime, result set completeness and correctness, number of sources selected and number of requests sent. Albeit informative, these metrics are generic and unable to quantify and evaluate the accuracy of the cardinality estimators of cost-based federation engines. To thoroughly evaluate cost-based federation engines, the effect of estimated cardinality errors on the overall query runtime performance must be measured. In this paper, we address this challenge by presenting novel evaluation metrics targeted at a fine-grained benchmarking of cost-based federated SPARQL query engines. We evaluate five cost-based federated SPARQL query engines using existing as well as novel evaluation metrics by using LargeRDFBench queries. Our results provide a detailed analysis of the experimental outcomes that reveal novel insights, useful for the development of future cost-based federated SPARQL query processing engines.}},
  author       = {{Qudus, Umair and Saleem, Muhammad and Ngonga Ngomo, Axel-Cyrille and Lee, Young-Koo}},
  issn         = {{2210-4968}},
  journal      = {{Semantic Web}},
  keywords     = {{SPARQL, benchmarking, cost-based, cost-free, federated, querying}},
  number       = {{6}},
  pages        = {{843--868}},
  publisher    = {{ISO Press}},
  title        = {{{An Empirical Evaluation of Cost-based Federated SPARQL Query Processing Engines}}},
  doi          = {{10.3233/SW-200420}},
  volume       = {{12}},
  year         = {{2021}},
}

@inbook{54587,
  abstract     = {{<jats:p>With significant growth in RDF datasets, application developers demand online availability of these datasets to meet the end users’ expectations. Various interfaces are available for querying RDF data using SPARQL query language. Studies show that SPARQL end-points may provide high query runtime performance at the cost of low availability. For example, it has been observed that only 32.2% of public endpoints have a monthly uptime of 99–100%. One possible reason for this low availability is the high workload experienced by these SPARQL endpoints. As complete query execution is performed at server side (i.e., SPARQL endpoint), this high query processing workload may result in performance degradation or even a service shutdown. We performed extensive experiments to show the query processing capabilities of well-known triple stores by using their SPARQL endpoints. In particular, we stressed these triple stores with multiple parallel requests from different querying agents. Our experiments revealed the maximum query processing capabilities of these triple stores after which point they lead to service shutdowns. We hope this analysis will help triple store developers to design workload-aware RDF engines to improve the availability of their public endpoints with high throughput.</jats:p>}},
  author       = {{Khan, Hashim and Manzoor, Ali and Ngonga Ngomo, Axel-Cyrille and Saleem, Muhammad}},
  booktitle    = {{Studies on the Semantic Web}},
  issn         = {{1868-1158}},
  publisher    = {{IOS Press}},
  title        = {{{When is the Peak Performance Reached? An Analysis of RDF Triple Stores}}},
  doi          = {{10.3233/ssw210042}},
  year         = {{2021}},
}

@article{31132,
  author       = {{Dann, Andreas Peter and Plate, Henrik and Hermann, Ben and Ponta, Serena Elisa and Bodden, Eric}},
  issn         = {{0098-5589}},
  journal      = {{IEEE Transactions on Software Engineering}},
  keywords     = {{Software}},
  pages        = {{1--1}},
  publisher    = {{Institute of Electrical and Electronics Engineers (IEEE)}},
  title        = {{{Identifying Challenges for OSS Vulnerability Scanners - A Study &amp; Test Suite}}},
  doi          = {{10.1109/tse.2021.3101739}},
  year         = {{2021}},
}

@inproceedings{26405,
  author       = {{Schubert, Philipp and Sattler, Florian and Schiebel, Fabian Benedikt and Hermann, Ben and Bodden, Eric}},
  booktitle    = {{2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM)}},
  title        = {{{Modeling the Effects of Global Variables in Data-Flow Analysis for C/C++}}},
  year         = {{2021}},
}

@inproceedings{25334,
  author       = {{Fiterau-Brostean, Paul and Jonsson, Bengt and Merget, Robert and de Ruiter, Joeri and Sagonas, Konstantinos and Somorovsky, Juraj}},
  booktitle    = {{29th {USENIX} Security Symposium ({USENIX} Security 20)}},
  isbn         = {{978-1-939133-17-5}},
  pages        = {{2523--2540}},
  publisher    = {{{USENIX} Association}},
  title        = {{{Analysis of DTLS Implementations Using Protocol State Fuzzing}}},
  year         = {{2020}},
}

@inbook{19521,
  author       = {{Pfannschmidt, Karlson and Hüllermeier, Eyke}},
  booktitle    = {{Lecture Notes in Computer Science}},
  isbn         = {{9783030582845}},
  issn         = {{0302-9743}},
  title        = {{{Learning Choice Functions via Pareto-Embeddings}}},
  doi          = {{10.1007/978-3-030-58285-2_30}},
  year         = {{2020}},
}

@inproceedings{19606,
  abstract     = {{Mobile shopping apps have been using Augmented Reality (AR) in the last years to place their products in the environment of the customer. While this is possible with atomic 3D objects, there is is still a lack in the runtime conﬁguration of 3D object compositions based on user needs and environmental constraints. For this, we previously developed an approach for model-based AR-assisted product conﬁguration based on the concept of Dynamic Software Product Lines. In this demonstration paper, we present the corresponding tool support ProConAR in the form of a Product Modeler and a Product Conﬁgurator. While the Product Modeler is an Angular web app that splits products (e.g. table) up into atomic parts (e.g. tabletop, table legs, funnier) and saves it within a conﬁguration model, the Product Conﬁgurator is an Android client that uses the conﬁguration model to place diﬀerent product conﬁgurations within the environment of the customer. We show technical details of our ready to use tool-chain ProConAR by describing its implementation and usage as well as pointing out future research directions.}},
  author       = {{Gottschalk, Sebastian and Yigitbas, Enes and Schmidt, Eugen and Engels, Gregor}},
  booktitle    = {{Human-Centered Software Engineering. HCSE 2020}},
  editor       = {{Bernhaupt, Regina and Ardito, Carmelo and Sauer, Stefan}},
  keywords     = {{Product Configuration, Augmented Reality, Model-based, Tool Support}},
  location     = {{Eindhoven}},
  publisher    = {{Springer}},
  title        = {{{ProConAR: A Tool Support for Model-based AR Product Configuration}}},
  doi          = {{10.1007/978-3-030-64266-2_14}},
  volume       = {{12481}},
  year         = {{2020}},
}

@inproceedings{19607,
  abstract     = {{Modern services consist of modular, interconnected
components, e.g., microservices forming a service mesh. To
dynamically adjust to ever-changing service demands, service
components have to be instantiated on nodes across the network.
Incoming flows requesting a service then need to be routed
through the deployed instances while considering node and link
capacities. Ultimately, the goal is to maximize the successfully
served flows and Quality of Service (QoS) through online service
coordination. Current approaches for service coordination are
usually centralized, assuming up-to-date global knowledge and
making global decisions for all nodes in the network. Such global
knowledge and centralized decisions are not realistic in practical
large-scale networks.

To solve this problem, we propose two algorithms for fully
distributed service coordination. The proposed algorithms can be
executed individually at each node in parallel and require only
very limited global knowledge. We compare and evaluate both
algorithms with a state-of-the-art centralized approach in extensive
simulations on a large-scale, real-world network topology.
Our results indicate that the two algorithms can compete with
centralized approaches in terms of solution quality but require
less global knowledge and are magnitudes faster (more than
100x).}},
  author       = {{Schneider, Stefan Balthasar and Klenner, Lars Dietrich and Karl, Holger}},
  booktitle    = {{IEEE International Conference on Network and Service Management (CNSM)}},
  keywords     = {{distributed management, service coordination, network coordination, nfv, softwarization, orchestration}},
  publisher    = {{IEEE}},
  title        = {{{Every Node for Itself: Fully Distributed Service Coordination}}},
  year         = {{2020}},
}

@inproceedings{19609,
  abstract     = {{Modern services comprise interconnected components,
e.g., microservices in a service mesh, that can scale and
run on multiple nodes across the network on demand. To process
incoming traffic, service components have to be instantiated and
traffic assigned to these instances, taking capacities and changing
demands into account. This challenge is usually solved with
custom approaches designed by experts. While this typically
works well for the considered scenario, the models often rely
on unrealistic assumptions or on knowledge that is not available
in practice (e.g., a priori knowledge).

We propose a novel deep reinforcement learning approach that
learns how to best coordinate services and is geared towards
realistic assumptions. It interacts with the network and relies on
available, possibly delayed monitoring information. Rather than
defining a complex model or an algorithm how to achieve an
objective, our model-free approach adapts to various objectives
and traffic patterns. An agent is trained offline without expert
knowledge and then applied online with minimal overhead. Compared
to a state-of-the-art heuristic, it significantly improves flow
throughput and overall network utility on real-world network
topologies and traffic traces. It also learns to optimize different
objectives, generalizes to scenarios with unseen, stochastic traffic
patterns, and scales to large real-world networks.}},
  author       = {{Schneider, Stefan Balthasar and Manzoor, Adnan and Qarawlus, Haydar and Schellenberg, Rafael and Karl, Holger and Khalili, Ramin and Hecker, Artur}},
  booktitle    = {{IEEE International Conference on Network and Service Management (CNSM)}},
  keywords     = {{self-driving networks, self-learning, network coordination, service coordination, reinforcement learning, deep learning, nfv}},
  publisher    = {{IEEE}},
  title        = {{{Self-Driving Network and Service Coordination Using Deep Reinforcement Learning}}},
  year         = {{2020}},
}

@inproceedings{19632,
  author       = {{Jovanovikj, Ivan and Yigitbas, Enes and Sauer, Stefan and Engels, Gregor}},
  booktitle    = {{Proceedings of the 8th International Working Conference on Human-Centered Software Engineering (HCSE'20)}},
  pages        = {{216--224}},
  publisher    = {{Springer}},
  title        = {{{Augmented and Virtual Reality Object Repository for Rapid Prototyping }}},
  year         = {{2020}},
}

@inproceedings{19656,
  author       = {{Sharma, Arnab and Wehrheim, Heike}},
  booktitle    = {{Proceedings of the 32th IFIP International Conference on Testing Software and Systems (ICTSS)}},
  publisher    = {{Springer}},
  title        = {{{Automatic Fairness Testing of Machine Learning Models}}},
  year         = {{2020}},
}

@article{19864,
  author       = {{Meyer, Maurice and Frank, Maximilian and Massmann, Melina and Dumitrescu, Roman}},
  journal      = {{Proceedings of The 11th International Multi-Conference on Complexity, Informatics and Cybernetics (IMCIC 2020)}},
  title        = {{{Research and Consulting in Data-Driven Strategic Product Planning}}},
  year         = {{2020}},
}

@article{19866,
  author       = {{Meyer, Maurice and Frank, Maximilian and Massmann, Melina and Dumitrescu, Roman}},
  journal      = {{Journal of Systemics, Cybernetics and Informatics}},
  number       = {{2}},
  pages        = {{55--61}},
  title        = {{{Research and Consulting in Data-Driven Strategic Product Planning}}},
  volume       = {{18}},
  year         = {{2020}},
}

@inproceedings{19899,
  abstract     = {{Most existing robot formation problems seek a target formation of a certain
minimal and, thus, efficient structure. Examples include the Gathering
and the Chain-Formation problem. In this work, we study formation problems that
try to reach a maximal structure, supporting for example an efficient
coverage in exploration scenarios. A recent example is the NASA Shapeshifter
project, which describes how the robots form a relay chain along which gathered
data from extraterrestrial cave explorations may be sent to a home base.
  As a first step towards understanding such maximization tasks, we introduce
and study the Max-Chain-Formation problem, where $n$ robots are ordered along a
winding, potentially self-intersecting chain and must form a connected,
straight line of maximal length connecting its two endpoints. We propose and
analyze strategies in a discrete and in a continuous time model. In the
discrete case, we give a complete analysis if all robots are initially
collinear, showing that the worst-case time to reach an
$\varepsilon$-approximation is upper bounded by $\mathcal{O}(n^2 \cdot \log
(n/\varepsilon))$ and lower bounded by $\Omega(n^2 \cdot~\log
(1/\varepsilon))$. If one endpoint of the chain remains stationary, this result
can be extended to the non-collinear case. If both endpoints move, we identify
a family of instances whose runtime is unbounded. For the continuous model, we
give a strategy with an optimal runtime bound of $\Theta(n)$. Avoiding an
unbounded runtime similar to the discrete case relies crucially on a
counter-intuitive aspect of the strategy: slowing down the endpoints while all
other robots move at full speed. Surprisingly, we can show that a similar trick
does not work in the discrete model.}},
  author       = {{Castenow, Jannik and Kling, Peter and Knollmann, Till and Meyer auf der Heide, Friedhelm}},
  booktitle    = {{Stabilization, Safety, and Security of Distributed Systems - 22nd International Symposium, SSS 2020, Austin, Texas, USA, November 18-21, 2020, Proceedings}},
  editor       = {{Devismes , Stéphane  and Mittal, Neeraj }},
  isbn         = {{978-3-030-64347-8}},
  pages        = {{65--80}},
  publisher    = {{Springer}},
  title        = {{{A Discrete and Continuous Study of the Max-Chain-Formation Problem – Slow Down to Speed Up}}},
  doi          = {{10.1007/978-3-030-64348-5_6}},
  volume       = {{12514}},
  year         = {{2020}},
}

@inproceedings{19953,
  abstract     = {{Current GNN architectures use a vertex neighborhood aggregation scheme, which limits their discriminative power to that of the 1-dimensional Weisfeiler-Lehman (WL) graph isomorphism test. Here, we propose a novel graph convolution operator that is based on the 2-dimensional WL test. We formally show that the resulting 2-WL-GNN architecture is more discriminative than existing GNN approaches. This theoretical result is complemented by experimental studies using synthetic and real data. On multiple common graph classification benchmarks, we demonstrate that the proposed model is competitive with state-of-the-art graph kernels and GNNs.}},
  author       = {{Damke, Clemens and Melnikov, Vitaly and Hüllermeier, Eyke}},
  booktitle    = {{Proceedings of the 12th Asian Conference on Machine Learning (ACML 2020)}},
  editor       = {{Jialin Pan, Sinno and Sugiyama, Masashi}},
  keywords     = {{graph neural networks, Weisfeiler-Lehman test, cycle detection}},
  location     = {{Bangkok, Thailand}},
  pages        = {{49--64}},
  publisher    = {{PMLR}},
  title        = {{{A Novel Higher-order Weisfeiler-Lehman Graph Convolution}}},
  volume       = {{129}},
  year         = {{2020}},
}

