TSSB-3M: Mining single statement bugs at massive scale - Richter, Cedric; Wehrheim, Heike (2022 IEEE/ACM 19th International Conference on Mining Software Repositories (MSR))

Bringing Structure to Structure-Preserving Signatures: Overview, Implementation and Comparison of Selected SPS Schemes - Siek, Hanna

On Transforming Lattice-Based Cryptography to the Ring Setting - Kramer, Paul

ADAGIO - Automated Data Augmentation of Knowledge Graphs Using Multi-expression Learning - Dreßler, Kevin; Sherif, Mohamed; Ngonga Ngomo, Axel-Cyrille (Proceedings of the 33rd ACM Conference on Hypertext and Hypermedia)
The creation of an RDF knowledge graph for a particular application commonly involves a pipeline of tools that transform a set ofinput data sources into an RDF knowledge graph in a process called dataset augmentation. The components of such augmentation pipelines often require extensive configuration to lead to satisfactory results. Thus, non-experts are often unable to use them. Wepresent an efficient supervised algorithm based on genetic programming for learning knowledge graph augmentation pipelines of arbitrary length. Our approach uses multi-expression learning to learn augmentation pipelines able to achieve a high F-measure on the training data. Our evaluation suggests that our approach can efficiently learn a larger class of RDF dataset augmentation tasks than the state of the art while using only a single training example. Even on the most complex augmentation problem we posed, our approach consistently achieves an average F1-measure of 99% in under 500 iterations with an average runtime of 16 seconds
Keywords: 2022 RAKI SFB901 deer dice kevin knowgraphs limes ngonga sherif simba

Practical Network Conditions for the Convergence of Distributed Optimization - Redder, Adrian; Ramaswamy, Arunselvan; Karl, Holger (IFAC-PapersOnLine)

XCS on Embedded Systems: An Analysis of Execution Profiles and Accelerated Classifier Deletion - Hansmeier, Tim; Brede, Mathis; Platzner, Marco (GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference Companion)

Analyzing Culture-Specific Argument Structures in Learner Essays - Chen, Wei-Fan; Chen, Mei-Hua; Mudgal, Garima; Wachsmuth, Henning (Proceedings of the 9th Workshop on Argument Mining (ArgMining 2022))

(In-)Approximability Results for Interval, Resource Restricted, and Low Rank Scheduling - Maack, Marten; Pukrop, Simon; Rasmussen, Anna Rodriguez (30th Annual European Symposium on Algorithms, ESA 2022, September 5-9, 2022, Berlin/Potsdam, Germany)

Distortion through modeling asymmetric bargaining power - Haake, Claus-Jochen; Streck, Thomas
We study the consequences of modeling asymmetric bargaining power in two-person bargaining problems. Comparing application of an asymmetric version of a bargaining solution to an upfront modification of the disagreement point, the resulting distortion crucially depends on the bargaining solution concept. While for the Kalai-Smorodinsky solution weaker players benefit from modifying the disagreement point, the situation is reversed for the Nash bargaining solution. There, weaker players are better off in the asymmetric bargaining solution. When comparing application of the asymmetric versions of the Nash and the Kalai-Smorodinsky solutions, we demonstrate that there is an upper bound for the weight of a player, so that she is better off with the Nash bargaining solution. This threshold is ultimately determined by the relative utilitarian bargaining solution. From a mechanism design perspective, our results provide valuable information for a social planner, when implementing a bargaining solution for unequally powerful players.
Keywords: Asymmetric bargaining power; Nash bargaining solution; Kalai-Smorodinsky bargaining solution

Knowledge Equity and Open Science in qualitative research – Practical research considerations - Steinhardt, Isabel; Kruschick, Felicitas (Research Ideas and Outcomes)
How can Knowledge In/Equity be addressed in qualitative research by taking the idea of Open Science into account? Two projects from the Open Science Fellows Programme by Wikimedia Deutschland will be used to illustrate how Open Science practices can succeed in qualitative research, thereby reducing In/Equity. In this context, In/Equity is considered as a fair and equal representation of people, their knowledge and insights and comprehends questions about how epistemic, structural, institutional and personal biases generate and shape knowledge as guidance. Three questions guide this approach: firstly, what do we understand by In/Equity in the context of knowledge production in these projects? Secondly, who will be involved in knowledge generation and to what extent will they be valued or unvalued? Thirdly, how can data be made accessible for re-use to enable true participation and sharing?
Keywords: Open Science; Knowledge Equity; Qualitative Methods

AI Assisted Interference Classification to Improve EMC Troubleshooting in Electronic System Development - Maalouly, Jad; Hemker, Dennis; Hedayat, Christian; Rückert, Christian; Kaufmann, Ivan; Olbrich, Marcel; Lange, Sven; Mathis, Harald (2022 Kleinheubach Conference)
In this paper, machine learning techniques will be used to classify different PCB layouts given their electromagnetic frequency spectra. These spectra result from a simulated near-field measurement of electric field strengths at different locations. Measured values consist of real and imaginary parts (amplitude and phase) in X, Y and Z directions. Training data was obtained in the time domain by varying transmission line geometries (size, distance and signaling). It was then transformed into the frequency domain and used as deep neural network input. Principal component analysis was applied to reduce the sample dimension. The results show that classifying different designs is possible with high accuracy based on synthetic data. Future work comprises measurements of real, custom-made PCB with varying parameters to adapt the simulation model and also test the neural network. Finally, the trained model could be used to give hints about the error’s cause when overshooting EMC limits.
Keywords: emc; pcb; electronic system development; machine learning; neural network

Die „dritte Wissensdimension“. Eine Epistemologie für eine neue Wissenswelt - Hagengruber, Ruth Edith (Sitzungsberichte der Leibniz-Sozietät der Wissenschaften 150/151, Jahrgang 2022: „Cyberscience – Wissenschaftsforschung und Informatik. Digitale Medien und die Zukunft der Kultur wissenschaftlicher Tätigkeit. Arbeitskreis „Emergente Systeme/Informatik und Gesellschaft“ der Leibniz-Sozietät der Wissenschaften zu Berlin in Kooperation mit der Gesellschaft für Wissenschaftsforschung“)

Chatbot-Enhanced Requirements Resolution for Automated Service Compositions - Kersting, Joschka; Ahmed, Mobeen; Geierhos, Michaela (HCI International 2022 Posters)
This work addresses the automatic resolution of software requirements. In the vision of On-The-Fly Computing, software services should be composed on demand, based solely on natural language input from human users. To enable this, we build a chatbot solution that works with human-in-the-loop support to receive, analyze, correct, and complete their software requirements. The chatbot is equipped with a natural language processing pipeline and a large knowledge base, as well as sophisticated dialogue management skills to enhance the user experience. Previous solutions have focused on analyzing software requirements to point out errors such as vagueness, ambiguity, or incompleteness. Our work shows how apps can collaborate with users to efficiently produce correct requirements. We developed and compared three different chatbot apps that can work with built-in knowledge. We rely on ChatterBot, DialoGPT and Rasa for this purpose. While DialoGPT provides its own knowledge base, Rasa is the best system to combine the text mining and knowledge solutions at our disposal. The evaluation shows that users accept 73% of the suggested answers from Rasa, while they accept only 63% from DialoGPT or even 36% from ChatterBot.
Keywords: On-The-Fly Computing; Chatbot; Knowledge Base

Methodenentwicklung zur Verbesserung der Schädigungsmodellierung in der numerischen 3D-Belastungssimulation mechanischer Fügeverfahren unter Berücksichtigung der fügeinduzierten Vorbeanspruchung - Otroshi, Mortaza; Meschut, Gerson

Microinverter PV Systems: New Efficiency Rankings and Formula for Energy Yield Assessment for any PV Panel Size at different Microinverter types - Krauter, Stefan; Bendfeld, Jörg (Proceedings of the 8th World Conference on Photovoltaik Energy Conversion)

Optimal Design of a Semi Grid-Connected PV System for a Site in Lwak, Kenya Using HOMER - Kakande, Josephine Nakato; Philipo, Godiana Hagile; Krauter, Stefan (Proceedings of the 8th World Conference on Photovoltaik Energy Conversion)

Schädigungsmodellierung von Hilfsfügeelementen beim mechanischen Fügen von Stahlwerkstoffen - Otroshi, Mortaza; Meschut, Gerson

Hardware Trojans in Reconfigurable Computing - Ahmed, Qazi Arbab
Wettstreit zwischen der Entwicklung neuer Hardwaretrojaner und entsprechender Gegenmaßnahmen beschreiten Widersacher immer raffiniertere Wege um Schaltungsentwürfe zu infizieren und dabei selbst fortgeschrittene Test- und Verifikationsmethoden zu überlisten. Abgesehen von den konventionellen Methoden um einen Trojaner in eine Schaltung für ein Field-programmable Gate Array (FPGA) einzuschleusen, können auch die Entwurfswerkzeuge heimlich kompromittiert werden um einen Angreifer dabei zu unterstützen einen erfolgreichen Angriff durchzuführen, der zum Beispiel Fehlfunktionen oder ungewollte Informationsabflüsse bewirken kann. Diese Dissertation beschäftigt sich hauptsächlich mit den beiden Blickwinkeln auf Hardwaretrojaner in rekonfigurierbaren Systemen, einerseits der Perspektive des Verteidigers mit einer Methode zur Erkennung von Trojanern auf der Bitstromebene, und andererseits derjenigen des Angreifers mit einer neuartigen Angriffsmethode für FPGA Trojaner. Für die Verteidigung gegen den Trojaner ``Heimtückische LUT'' stellen wir die allererste erfolgreiche Gegenmaßnahme vor, die durch Verifikation mittels Proof-carrying Hardware (PCH) auf der Bitstromebene direkt vor der Konfiguration der Hardware angewendet werden kann, und präsentieren ein vollständiges Schema für den Entwurf und die Verifikation von Schaltungen für iCE40 FPGAs. Für die Gegenseite führen wir einen neuen Angriff ein, welcher bösartiges Routing im eingefügten Trojaner ausnutzt um selbst im fertigen Bitstrom in einem inaktiven Zustand zu verbleiben: Hierdurch kann dieser neuartige Angriff zur Zeit weder von herkömmlichen Test- und Verifikationsmethoden, noch von unserer vorher vorgestellten Verifikation auf der Bitstromebene entdeckt werden.
Keywords: FPGA Security; Hardware Trojans; Bitstream-level Trojans; Bitstream Verification

Evaluation Criteria in Product Idea Selection Decisions - Gräßler, Iris; Koch, Anna-Sophie (XXXIII Proceedings of the ISPIM Innovation Conference)
Within innovation management, choosing the best fitting product idea is the most important decision point. The future existence and success of the organization is depending on selected product ideas. To find the best fitting idea for an organization, it needs evaluation criteria representing the organizations mission Therefore, this study focuses on a holistic overview about evaluation criteria and on supporting organizations in the process to select its individual evaluation criteria. Based on a literature study, existing approaches regarding evaluation criteria in product idea selection are identified and a list of evaluation criteria is reworked. Using the list of evaluation criteria, a prioritization method is created. Within an interview with experts in innovation management, the method is discussed regarding usability and the level of assistance in product idea selection. The developed criteria can be used directly by innovation manager and industrial practitioners to evaluate potential product ideas.
Keywords: innovation management; evaluation criteria; idea selection; idea evaluation; meta-study

Implicit Statements in Healthcare Reviews: A Challenge for Sentiment Analysis - Kersting, Joschka; Bäumer, Frederik Simon (Proceedings of the Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications)
This paper aims at discussing past limitations set in sentiment analysis research regarding explicit and implicit mentions of opinions. Previous studies have regularly neglected this question in favor of methodical research on standard-datasets. Furthermore, they were limited to linguistically less-diverse domains, such as commercial product reviews. We face this issue by annotating a German-language physician review dataset that contains numerous implicit, long, and complex statements that indicate aspect ratings, such as the physician’s friendliness. We discuss the nature of implicit statements and present various samples to illustrate the challenge described.
Keywords: Sentiment analysis; Natural language processing; Aspect phrase extraction