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Eintrag in der Universitätsbibliographie der TU Chemnitz

Volltext zugänglich unter
URN: urn:nbn:de:bsz:ch1-qucosa2-964013


Datsogiannis, Dimitrios
Hardt, Wolfram (Prof. Dr. Dr. h. c.) ; Windisch, André (Prof. Dr.)

Smart Detection of Deficiencies and Faults in Automotive Software Releases


Kurzfassung in englisch

A novel approach for evaluating Electric and Electronic automotive software development
processes is introduced. The aim is to provide transparency among stakeholders and deliver
feedback throughout the development cycles, preventing software defects and conflicts.
The proposed model allows stakeholders to assess the status, performance, and quality of
software packages by posing targeted questions and evaluating the answers to draw conclusions.
These questions, derived from literature as metrics and principles, are selectively proposed by a
Reinforcement Learning agent using Contextual Multi-Armed Bandits (CMAB) as a
recommendation system.
The questions serve as software packages with key evaluation information, enabling a complete
system assessment. Each question has a pre-evaluated weight, and each answer has a value.
These parameters define the agent's reward, balancing exploration and exploitation.
The model is scalable in terms of the target software or component's complexity, allowing
continuous performance improvement as the algorithm learns over time. The evaluation results
confirm the concept's functionality in various circumstances, addressing challenges of cold start,
partial feedback, and data parsing.
In summary, this thesis contributes to automotive software development by enhancing
transparency and enabling timely detection of process deficiencies and software faults.

Universität: Technische Universität Chemnitz
Institut: Professur Technische Informatik
Fakultät: Fakultät für Informatik
Dokumentart: Dissertation
Betreuer: Hardt, Wolfram (Prof. Dr. Dr. h. c.)
ISBN/ISSN: 978-3-96100-257-3
DOI: doi:10.51382/978-3-96100-258-0
URL/URN: https://nbn-resolving.org/urn:nbn:de:bsz:ch1-qucosa2-964013
Quelle: Chemnitz : Universitätsverlag Chemnitz, 2025. - 230 S. - Wissenschaftliche Schriftenreihe EINGEBETTETE, SELBSTORGANISIERENDE SYSTEME ; Band 22
SWD-Schlagwörter: Softwarelebenszyklus , Empfehlungssystem , Kraftfahrzeugindustrie
Freie Schlagwörter (Englisch): Automotive software development , Evaluation of software releases , Recommender Systems
DDC-Sachgruppe: Ingenieurwissenschaften
Sprache: englisch
Tag der mündlichen Prüfung 21.03.2025
OA-Lizenz CC BY-SA 4.0

 

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