Schulleitungen als Promotoren. Unterstützung digitalisierungsbezogener Schulentwicklungsprozesse durch Schulleitungen und deren Wahrnehmung durch Lehrpersonen. - Gerick, Julia; Kieseler, Janine; Herrmann, Daniel; Eickelmann, Birgit (MedienPädagogik (Occasional Papers))

On the repulsion effect of coupled Lamb wave modes - Nicolai, Marcel; Bulling, Jannis; Lugovtsova, Yevgeniya; Zeipert, Henning; Prager, Jens; Henning, Bernd (Fortschritte der Akustik - DAGA 2024)

Erinnerung als Formproblem. Feridun Zaimoglus Versuche, deutsche Geschichte ‚zu schreiben‘: „Führer“ (2021) und „Bewältigung“ (2022) - Eke, Norbert (Feridun Zaimoglu. Kasseler Grimm-Poetikprofessur 2023)

Zwischen Herrschaft und Utopie . Eine theologische Reflexion über die ambivalente Mensch-Tier-Beziehung - Herdramm, Henrike (Laudato)
Keywords: Tiertheologie; Tierethik; Psalm 104; Mensch-Tier-Beziehung

SootUp: A Redesign of the Soot Static Analysis Framework - Karakaya, Kadiray; Schott, Stefan; Klauke, Jonas; Bodden, Eric; Schmidt, Markus; Luo, Linghui; He, Dongjie (Tools and Algorithms for the Construction and Analysis of Systems)
Abstract Since its inception two decades ago, Soot has become one of the most widely used open-source static analysis frameworks. Over time it has been extended with the contributions of countless researchers. Yet, at the same time, the requirements for Soot have changed over the years and become increasingly at odds with some of the major design decisions that underlie it. In this work, we thus present SootUp , a complete reimplementation of Soot that seeks to fulfill these requirements with a novel design, while at the same time keeping elements that Soot users have grown accustomed to.

Detecting Security-Relevant Methods using Multi-label Machine Learning - Johnson, Oshando; Piskachev, Goran; Krishnamurthy, Ranjith; Bodden, Eric (Proceedings of the 46th International Conference on Software Engineering, IDE Workshop)
To detect security vulnerabilities, static analysis tools need to be configured with security-relevant methods. Current approaches can automatically identify such methods using binary relevance machine learning approaches. However, they ignore dependencies among security-relevant methods, over-generalize and perform poorly in practice. Additionally, users have to nevertheless manually configure static analysis tools using the detected methods. Based on feedback from users and our observations, the excessive manual steps can often be tedious, error-prone and counter-intuitive. In this paper, we present Dev-Assist, an IntelliJ IDEA plugin that detects security-relevant methods using a multi-label machine learning approach that considers dependencies among labels. The plugin can automatically generate configurations for static analysis tools, run the static analysis, and show the results in IntelliJ IDEA. Our experiments reveal that Dev-Assist's machine learning approach has a higher F1-Measure than related approaches. Moreover, the plugin reduces and simplifies the manual effort required when configuring and using static analysis tools.

UNav-Sim: A Visually Realistic Underwater Robotics Simulator and Synthetic Data-Generation Framework - Amer, Abdelhakim; Álvarez-Tuñón, Olaya; Uğurlu, Halil İbrahim; Le Fevre Sejersen, Jonas; Brodskiy, Yury; Kayacan, Erdal (2023 21st International Conference on Advanced Robotics (ICAR))

TypeEvalPy: A Micro-benchmarking Framework for Python Type Inference Tools - Shivarpatna Venkatesh, Ashwin Prasad; Sabu, Samkutty; Wang, Jiawei; Mir, Amir M.; Li, Li; Bodden, Eric (Proceedings of the 46th International Conference on Software Engineering, Tool Demo Track)

Modellierungen außerinstitutioneller Aneignungsprozesse digital-materieller Interfaces und (musik-)pädagogische Anschlüsse - Neuhausen, Timo; Ahlers, Michael (Musik – Digitalisierung – Bildung)

Singen auf TikTok und Co. Sind Gesangspraktiken in (post)digitaler Kultur (k)ein Thema für die Musikpädagogik? - Godau, Marc (Stimme, Medien, Umwelt. Kinder- und Jugendstimme)