Forschung und Innovation

Angewandte Forschung für Best-in-Class Applikationen der Zukunft

Um exzellenter Digitalisierungspartner sein und bleiben zu können, investiert XITASO in Forschung und Innovation. Unser Ansatz ist es, Zukunftsthemen gemeinsam mit Partnern aus Wissenschaft und Wirtschaft intensiv zu beleuchten und mögliche Anwendungen für uns und unsere Partner herauszuarbeiten. Dabei lassen wir uns von Herausforderungen aus der Praxis inspirieren, denen wir in unserer täglichen Arbeit mit unseren Kunden begegnen. So bieten wir den Raum für bestmögliche anwendungsnahe Forschung und einen Bezug zu heutigen und zukünftigen Märkten.

Wissenschaftliche Exzellenz sowie nationaler und internationaler Austausch mit der Wissenschafts-Community gehören zur Forschung bei XITASO ebenso wie selbstorganisiertes Arbeiten in einem agilen, firmenübergreifenden Forschungsteam. Wir sind überzeugt: So kann Forschung von heute Innovationen von morgen erzeugen.

Was uns antreibt

Unsere Technologiebereiche

Mensch-zentriertes Software Engineering

Das Ziel unserer Forschung ist, werthaltige und nachhaltige Software-Systeme besser entwickeln zu können. Dies erfordert auch die beständige Weiterentwicklung von Methoden, Werkzeugen und Prinzipien des Software Engineering.

KI und Optimierung

Der Einsatz und die Kombination verschiedener KI- und Optimierungstechnologien hat großes Potenzial zur Verbesserung von technischen Systemen, aber auch des Software Engineering selbst. Ein Fokus in diesem Bereich ist es, vorhandenes Domänenwissen und Modelle mit datenbasierten Methoden zu integrieren und deren Anwendungspotential zu erforschen.

IoT und 5G

IoT-Architekturen und -Technologien sind eine wesentliche Grundlage für künftige Prozessverbesserungen und neue Wertschöpfungsmodelle. Zukünftige Kommunikationsinfrastrukturen wie 5G ermöglichen in diesem Zusammenhang neue Entwurfs- und Interaktionsmuster für softwareintensive Systeme, deren Potential wir untersuchen und vorantreiben.

Autonome Systeme

Wir sind in immer mehr Lebensbereichen von autonomen Systemen umgeben, beispielsweise Roboter oder autonom fahrende Autos. Bei XITASO untersuchen wir daher, wie Softwarelösungen für sichere, erwartungskonforme und nutzerfreundliche autonome Systeme aussehen müssen.

Icon Security

Security by Design

Durchgehende Vernetzung erfordert die Neubetrachtung von Angriffssicherheit technischer Systeme und bedarf geeigneter Methoden und Technologien zur Konstruktion sicherer Software-Lösungen.

Unsere Forschungsprojekte

Eine Auswahl unserer Stellenausschreibungen

Eine Auswahl unserer Veröffentlichungen

2024
  • Migrating Software Systems towards Post-Quantum-Cryptography – A Systematic Literature Review
    Christian Näther, Daniel Herzinger, Stefan-Lukas Gazdag, Jan-Philipp Steghöfer, Simon Daum, Daniel Loebenberger
    April 2024
    Hier lesen
  • A Closer Look at Length-niching Selection and Spatial Crossover in Variable-length Evolutionary Rule Set
    David Pätzel, Richard Nordsieck, Jörg Hähner
    Learning, International Workshop on Evolutionary Rule-based Machine Learning @ GECCO 2024
    Mehr Infos

  • Measuring Similarities in Model Structure of Metaheuristic Rule Set Learners
    David Pätzel, Richard Nordsieck, Jörg Hähner
    EvoAPPS 2024

  • Tracking assets in source code with Security Annotations
    Daniel Haak, Raphael Mayr, Jan-Philipp Steghöfer, Alexandra Teynor, Phillip Heidegger
    ICSE 2024 Poster Track

  • Where Requirements and Agility Meet: No Man’s Land or a Land of Opportunity? 
    Fabiano Dalpiaz, Jan-Philipp Steghöfer
    To appear in IEEE Software
    Hier lesen

  • Combining Requirements Enigneering Techniques for the Analysis of a Legacy System
    Jessica Friedline, Jan-Philipp Steghöfer

    Joint Proceedings of REFSQ-2024 Workshops, Doctoral Symposium, Posters & Tools Track and Education and Training Track. Co-located with REFSQ 2024. Winterthur, Switzerland, April 8, 2024
    PDF-Download

2023
  • Contrastive pretraining of regression tasks in reliability forecasting of automotive electronics.
    Emilio Zarbali, Alwin Hoffmann, Jonas Hepp
    22nd International Conference on Machine Learning and Applications (ICMLA 2023), Jacksonville, Florida, USA, Dez. 2023.
  • FeatRacer: Locating Features Through Assisted Traceability
    Mukelabai Mukelabai, Kevin Hermann, Thorsten Berger, Jan-Philipp Steghöfer
    IEEE Transactions on Software Engineering, 2023
    Hier lesen

  • Processes, Methods, and Tools in Model-based Engineering — A Qualitative Multiple-Case Study
    Jörg Holtmann, Grischa Liebel, Jan-Philipp Steghöfer
    Journal of Software and Systems, 2023
    PDF-Download

  • Blended modeling in commercial and open-source model-driven software engineering tools: A systematic study.
    Istvan David, Malvina Latifaj, Jakob Pietron, Weixing Zhang, Federico Ciccozzi, Ivano Malavolta, Alexander Raschke, Jan-Philipp Steghöfer, Regina Hebig
    Softw. Syst. Model.22(1): 415-447 (2023)
    Hier lesen

  • CASCADE: An Asset-driven Approach to Build Security Assurance Cases for Automotive Systems.
    Mazen Mohamad, Rodi Jolak, Örjan Askerdal, Jan-Philipp Steghöfer, Riccardo Scandariato
    ACM Trans. Cyber Phys. Syst. 7(1): 3:1-3:26 (2023)
    Hier lesen

  • Trustful Model-Based Information Exchange in Collaborative Engineering.
    David Schmelter, Jan-Philipp Steghöfer, Karsten Albers, Mats Ekman, Jörg Tessmer, Raphael Weber
    EuroSPI (1) 2023: 156-170
    Hier lesen

  • Exploiting Meta-Model Structures in the Generation of Xtext Editors.
    Jörg Holtmann, Jan-Philipp Steghöfer, Weixing Zhang.
    Proceedings of the 11th International Conference on Model-Based Software and Systems Engineering (MODELSWARD).
    PDF-Download

  • Creating Python-style Domain Specific Languages: A Semi-automated Approach and Intermediate Results.
    Weixing Zhang, Regina Hebig, Jan-Philipp Steghöfer, Jörg Holtmann.
    Proceedings of the 11th International Conference on Model-Based Software and Systems Engineering (MODELSWARD).
    PDF-Download

  • Automated Extraction of Grammar Optimization Rule Configurations for Metamodel-Grammar Co-evolution.
    Weixing Zhang, Regina Hebig, Daniel Strüber, Jan-Philipp Steghöfer
    SLE 2023: 84-96
    PDF-Download

2022
  • Predicting thermal resistance of solder joints based on Scanning Acoustic Microscopy using Artificial Neural Networks.
    Andreas Zippelius, Tobias Strobl, Maximilian Schmid, Joseph Hermann, Alwin Hoffmann, Gordon Elger.
    9th Electronics System-Integration Technology Conference (ESTC 2022).
  • Identifying security-related requirements in regulatory documents based on cross-project classification.
    Mazen Mohamad, Jan-Philipp Steghöfer, Alexander Åström, and Riccardo Scandariato.
    Proceedings of the 18th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE’22), pp. 82-91.
  • A Closer Look at Sum-based Embedding Aggregation for Knowledge Graphs Containing Procedural Knowledge.
    Richard Nordsieck, Michael Heider, Anton Hummel, Jörg Hähner.
    6th International Workshop On Deep Learning For Knowledge Graphs (DL4KG) at the 21th International Semantic Web Conference (ISWC 2022).
    PDF-Download
  • Towards Conceptual and Procedural Models of Operator Knowledge in Industrial Information Models.
    Richard Nordsieck, Anton Hummel, Michael Heider, Alwin Hoffmann, Jörg Hähner.
    First International Workshop On Semantic Industrial Information Modelling (SemIIM) at the 19th Extended Semantic Web Conference (ESWC 2022).
    PDF-Download
  • Reliability-Based Aggregation of Heterogeneous Knowledge to Assist Operators in Manufacturing.
    Richard Nordsieck, Michael Heider, Alwin Hoffmann, Jörg Hähner.
    2022 IEEE 16th International Conference on Semantic Computing (ICSC).
2021
  • Learning Classifier Systems for Self-Explaining Socio-Technical-Systems.
    Michael Heider, Richard Nordsieck, Jörg Hähner.
    Proceedings of the LIFELIKE 2021 – 9th Edition in the Evolution of the Workshop Series of Autonomously Learning and Optimizing Systems (SAOS).
    PDF-Download
  • CAD-based Grasp and Motion Planning for Process Automation in Fused Deposition Modelling.
    Andreas Wiedholz, Michael Heider, Richard Nordsieck, Andreas Angerer, Simon Dietrich, Jörg Hähner.
    International Conference on Informatics in Control, Automation and Robotics (ICINCO).
    Link
  • Knowledge Extraction via Decentralized Knowledge Graph Aggregation.
    Richard Nordsieck, Michael Heider, Anton Winschel, Jörg Hähner.
    IEEE International Conference on Semantic Computing (ICSC).
    PDF-Download
2020
  • Evaluating the Effect of User-Given Guiding Attention on the Learning Process.
    Richard Nordsieck, Michael Heider, Andreas Angerer, Jörg Hähner.
    IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS).
    Link
  • Interactive Knowledge-Guided Learning.
    Richard Nordsieck & Jörg Hähner.
    IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C).
    Link
  • Opportunities and Limitations of Mixed Reality Holograms in Industrial Robotics.
    Michael Filipenko, Andreas Angerer, Alwin Hoffmann, Wolfgang Reif.
    Factory of the Future: How to digitalize the robot-aided manufacturing process in Industry 4.0? Part of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
    PDF-Download
2019
  • Towards Automated Parameter Optimization by Persisting Expert Knowledge.
    Richard Nordsieck, Michael Heider, Andreas Angerer, Jörg Hähner.
    International Conference on Informatics in Control, Automation and Robotics (ICINCO).
    PDF-Download
2018
  • partsival – Collision-based Particle and many-body Simulations on GPUs for Planetary Exploration Systems.
    Roy Lichtenheldt, Simon Kerler, Andreas Angerer, Wolfgang Reif.
    Joint International Conference on Multibody System Dynamics (IMSD).
    PDF-Download
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2023

  • Creating Python-style Domain Specific Languages: A Semi-automated Approach and Intermediate Results.
    Weixing Zhang, Regina Hebig, Jan-Philipp Steghöfer, Jörg Holtmann.
    Proceedings of the 11th International Conference on Model-Based Software and Systems Engineering (MODELSWARD).
  • Exploiting Meta-Model Structures in the Generation of Xtext Editors.
    Jörg Holtmann, Jan-Philipp Steghöfer, Weixing Zhang.
    Proceedings of the 11th International Conference on Model-Based Software and Systems Engineering (MODELSWARD).

 

2022

  • Predicting thermal resistance of solder joints based on Scanning Acoustic Microscopy using Artificial Neural Networks.
    Andreas Zippelius, Tobias Strobl, Maximilian Schmid, Joseph Hermann, Alwin Hoffmann, Gordon Elger.
    9th Electronics System-Integration Technology Conference (ESTC 2022).
  • Identifying security-related requirements in regulatory documents based on cross-project classification.
    Mazen Mohamad, Jan-Philipp Steghöfer, Alexander Åström, and Riccardo Scandariato.
    Proceedings of the 18th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE’22), pp. 82-91.
  • A Closer Look at Sum-based Embedding Aggregation for Knowledge Graphs Containing Procedural Knowledge.
    Richard Nordsieck, Michael Heider, Anton Hummel, Jörg Hähner.
    6th International Workshop On Deep Learning For Knowledge Graphs (DL4KG) at the 21th International Semantic Web Conference (ISWC 2022).
    PDF-Download
  • Towards Conceptual and Procedural Models of Operator Knowledge in Industrial Information Models.
    Richard Nordsieck, Anton Hummel, Michael Heider, Alwin Hoffmann, Jörg Hähner.
    First International Workshop On Semantic Industrial Information Modelling (SemIIM) at the 19th Extended Semantic Web Conference (ESWC 2022).
    PDF-Download
  • Reliability-Based Aggregation of Heterogeneous Knowledge to Assist Operators in Manufacturing.
    Richard Nordsieck, Michael Heider, Alwin Hoffmann, Jörg Hähner.
    2022 IEEE 16th International Conference on Semantic Computing (ICSC).

 

2021

  • Learning Classifier Systems for Self-Explaining Socio-Technical-Systems.
    Michael Heider, Richard Nordsieck, Jörg Hähner.
    Proceedings of the LIFELIKE 2021 – 9th Edition in the Evolution of the Workshop Series of Autonomously Learning and Optimizing Systems (SAOS).
    PDF-Download
  • CAD-based Grasp and Motion Planning for Process Automation in Fused Deposition Modelling.
    Andreas Wiedholz, Michael Heider, Richard Nordsieck, Andreas Angerer, Simon Dietrich, Jörg Hähner.
    International Conference on Informatics in Control, Automation and Robotics (ICINCO).
    Link
  • Knowledge Extraction via Decentralized Knowledge Graph Aggregation.
    Richard Nordsieck, Michael Heider, Anton Winschel, Jörg Hähner.
    IEEE International Conference on Semantic Computing (ICSC).
    PDF-Download

 

2020

  • Evaluating the Effect of User-Given Guiding Attention on the Learning Process.
    Richard Nordsieck, Michael Heider, Andreas Angerer, Jörg Hähner.
    IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS).
    Link
  • Interactive Knowledge-Guided Learning.
    Richard Nordsieck & Jörg Hähner.
    IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C).
    Link
  • Opportunities and Limitations of Mixed Reality Holograms in Industrial Robotics.
    Michael Filipenko, Andreas Angerer, Alwin Hoffmann, Wolfgang Reif.
    Factory of the Future: How to digitalize the robot-aided manufacturing process in Industry 4.0? Part of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
    PDF-Download

 

2019

  • Towards Automated Parameter Optimization by Persisting Expert Knowledge.
    Richard Nordsieck, Michael Heider, Andreas Angerer, Jörg Hähner.
    International Conference on Informatics in Control, Automation and Robotics (ICINCO).
    PDF-Download

 

2018

  • partsival – Collision-based Particle and many-body Simulations on GPUs for Planetary Exploration Systems.
    Roy Lichtenheldt, Simon Kerler, Andreas Angerer, Wolfgang Reif.
    Joint International Conference on Multibody System Dynamics (IMSD).
    PDF-Download

Unsere Partner

“Mit Forschungs- und Innovationsprojekten erkunden wir das Potenzial der Technologien von morgen. Dazu vernetzen wir uns mit starken Partnern und investieren bewusst in exzellente Nachwuchsforscher.”

Dr. Andreas Angerer
Head of Research and Innovation
XITASO GmbH

Sie interessieren sich für ein Projekt, eine Leistung oder haben eine sonstige Frage?

Dr. Andreas Angerer

Tel. +49 821 885882-94
andreas.angerer@xitaso.com