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Auflistung Software Engineering nach Erscheinungsdatum

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  • Konferenzbeitrag
    Wann fahren wir autonom? Eine Untersuchung aus technischer und rechtlicher Sicht.
    (Software Engineering 2022 Workshops, 2022) Birkemeyer, Lukas; Delventhal, Marlene; Schaefer, Ina; Schmieder, Fabian
    Autonomes Fahren rückt immer mehr in den Fokus der Gesellschaft. Im Gesetz zum autonomen Fahren sieht die deutsche Bundesregierung einen Meilenstein, der die Realisierung des autonomen Fahrens ermöglicht. Dennoch sind keine serienreifen, autonomen Fahrfunktionen auf deutschen Straßen zugelassen. Wie weit sind wir noch vom Traum vom autonomen Fahren entfernt? In diesem Beitrag wird untersucht, welche offenen Fragen es aus juristischer und technischer Sicht gibt und in welchen Punkten beide Disziplinen aufeinander warten. Der aktuelle Stand wird in den Bereichen Typgenehmigung/Zulassung, Fahrerlaubnis (Führerschein) und Haftung systematisch untersucht. Mit Hilfe eines Gedankenexperiments, bei dem der menschliche Fahrer durch einen Roboterfahrer ersetzt wird, wird eine einheitliche Basis geschaffen, um automatisierte Fahrfunktionen und Fahrerassistenzsysteme zu vergleichen. Dieser Beitrag deckt offene Fragen auf, die für die Realisierung des vollständig autonomen Fahrens noch beantwortet werden müssen. Eine praktische Umsetzung erfordert eine enge interdisziplinäre Zusammenarbeit, insbesondere von Expert*innen aus den Bereichen Regulierung, Technik und Sozialwissenschaften.
  • Konferenzbeitrag
    19th Workshop on Automotive Software Engineering (ASE'22)
    (Software Engineering 2022 Workshops, 2022) Dörr, Heiko; Helke, Steffen
    Preface of the 19th Workshop on Automotive Software Engineering (ASE'22)
  • Konferenzbeitrag
    A Multi-Platform Small Scale Drone Demonstrator for Technology Maturation of Next Generation Avionic Functions
    (Software Engineering 2022 Workshops, 2022) Pickard, Michael; Ludewig, Philipp; Halbig, Jens; Krach, Bernhard
    The emerging need for new types of airborne platforms that are to be operated in a System-of-Systems context, e.g. like the European Future Combat Air System, drives the development and maturation of new technologies for the next generation of military aircraft. A special focus is on the utilization of swarms/teams of unmanned platforms which are envisaged to be operated in highly automated collaboration with manned platforms. To accelerate the development of those technologies Airbus Defence and Space has launched a small scale demonstrator project using customized Micro Air Vehicles 2. This enables modular and agile technology integration with low threshold to get new developments airborne. A major focus of the recent activities has been the establishment and enhancement of the development environment including test benches, mission software and ground control station. However, already a fi rst set of new technologies for formation management, collaborative navigation and sensor management as well as multiple sensors like a radio frequency emitter localization sensor and an industrial camera have been integrated and tested comprehensively. In summary it can be confi rmed that there are major benefi ts in the utilization of Micro Air Vehicles as rapid prototyping platform for avionics technology maturation.
  • Konferenzbeitrag
    Build Your Own Training Data - Synthetic Data for Object Detection in Aerial Images
    (Software Engineering 2022 Workshops, 2022) Laux, Lea; Schirmer, Sebastian; Schopferer, Simon; Dauer, Johann
    Machine learning has become one of the most widely used techniques in artificial intelligence, especially for image processing. One of the biggest challenges in developing an accurate image processing model is to collect large amounts of data that are suffi ciently close to the real-world scenario. Ideally, real-world data is therefore used for model training. Unfortunately, real-world data is often insuffi ciently available and expensive to generate. Therefore, models are trained using synthetic data. However, there is no standardized method of how training data is generated and which properties determine the data quality. In this paper, we present fi rst steps towards the generation of large amounts of data for human detection based on aerial images. To create labeled aerial images, we are using Unreal Engine and AirSim. We report on fi rst impressions of the generated labeled aerial images and identify future challenges – current simulation tools can be used to create realistic and diverse images including labeling, but native support would be benefi cial to ease their usage.
  • Konferenzbeitrag
    Message from the SE’22 Workshop Chairs
    (Software Engineering 2022 Workshops, 2022) Michael, Judith; Pfeiffer, Jérôme; Wortmann, Andreas
    Preface of the SE’22 Workshop Proceedings
  • Konferenzbeitrag
    Requirement Management in Enterprise Systems Projects
    (Software Engineering 2022 Workshops, 2022) Weiss, Christoph; Keckeis, Johannes
    Preface of the Workshop Requirement Management in Enterprise Systems Projects (AESP - Anforderungsmanagement in Enterprise Systems-Projekten)
  • Konferenzbeitrag
    Static Analysis Methodologies for WCET Calculating with Asynchronous IO
    (Software Engineering 2022 Workshops, 2022) Seifert, Georg
    The estimation of the upper bound of the WCET is one of the hardest challenges in the analysis of safety critical real time applications. Since a long time, the static WCET estimation of single core CPU-focused systems without shared resources has been investigated and can now be regarded as solved. The WCET analysis with shared resources is not feasible with current practice due to the lack of information about the internal timing, especially the IO system. The rise of system functionality and the growth of interfaces with high bandwidth in MCUs has resulted in a situation where a CPU-only processing of the IO, or a degraded usage of DMACs, is no more feasible. Therefore, dedicated hardware components, like DMAC, have to be considered and the disadvantages of conflict-affl icted transfers must become part of the analysis. To resolve the problems with interference afflicted MCU internal data transfers, an approach is presented which describes the infl uence parameters on the WCET and expresses these in a simplified timing model of the MCU. Afterwards the information is used to extrapolate the increase of the execution time caused by a given type of traffic to estimate the WCET with asynchronous IO accesses.
  • Konferenzbeitrag
    Erweiterung von Gefahren- und Risikoanalysen der Funktionalen Sicherheit um Aspekte der Produktsicherheit nach ISO 12100
    (Software Engineering 2022 Workshops, 2022) Emig, Moritz; Metz, Pierre; Reißing, Ralf
    Bei der Brose Fahrzeugteile SE & Co. KG wird eine Gefährdungs- und Risikoanalyse (HARA) nach der ISO 26262 [DI18] angewandt. Diese Analyse betrachtet zufällige oder systematische Fehlfunktionen, die durch E/E-Probleme (Elektrik/Elektronik) verursacht werden. Die HARA soll nun um die Produktsicherheit (ProSi) erweitert werden. Diesbezüglich existiert bereits ein Brose-interner Ansatz, mit welchem allerdings nur funktionale Aspekte ermittelbar sind. Bei der ProSi-HARA sollen allerdings auch nicht-funktionale Gefährdungen (NFH) berücksichtigt werden. Damit bei der ProSi-HARA-Durchführung so viele NFH wie möglich ermittelt werden können, wurde als Hilfsmittel eine Checkliste generiert. Diese basiert auf der Tabelle B.1 der ISO 12100 [DI11], die sich mit der Sicherheit von Maschinen beschäftigt. Anschließend wurden drei alternative Konzepte zur Integration der Checkliste in die ProSi-HARA erarbeitet. Die Konzepte wurden in einem Pilotprojekt bei Brose erprobt. Dabei hat sich eines der Konzepte klar mit dem besten Aufwand-Nutzenverhältnis durchgesetzt. Mittels dieser Vorgehensweise konnten mit der Checkliste eine Vielzahl eigenständiger NFH identifiziert werden, die mit der herkömmlichen HARA nicht erkannt worden wären. Mit eigenständig sind hier NFH gemeint, die nicht in Zusammenhang mit funktionalen Fehlern oder Use Cases (funktionalen Anwendungsfälle) stehen.
  • Konferenzbeitrag
    An Anthropomorphic Approach to establish an Additional Layer of Trustworthiness of an AI Pilot
    (Software Engineering 2022 Workshops, 2022) Regli, Christoph; Annighoefer, Björn
    AI algorithms promise solutions for situations where conventional, rule-based algorithms reach their limits. They perform in complex problems yet unknown at design time, and highly efficient functions can be implemented without having to develop a precise algorithm for the problem at hand. Well-tried applications show the AI’s ability to learn from new data, extrapolate on unseen data, and adapt to a changing environment — a situation encountered in fl ight operations. In aviation, however, certifi cation regulations impede the implementation of non-deterministic or probabilistic algorithms that adapt their behaviour with increasing experience. Regulatory initiatives aim at defining new development standards in a bottom-up approach, where the suitability and the integrity of the training data shall be addressed during the development process, increasing trustworthiness in eff ect. Methods to establish explainability and traceability of decisions made by AI algorithms are still under development, intending to reach the required level of trustworthiness. This paper outlines an approach to an independent, anthropomorphic software assurance for AI/ML systems as an additional layer of trustworthiness, encompassing top-down black-box testing while relying on a well-established regulatory framework.
  • Konferenzbeitrag
    A Translation Semantics for Driving Simulation Languages
    (Software Engineering 2022 Workshops, 2022) Schneider, Jörn; Schneider, Marvin
    The development of advanced driver assistance systems and automated driving functions requires the usage of driving simulation as integral part of the software engineering process. Moreover, safety standards such as SOTIF (ISO 21448) and legal regulations give driving simulation a key role for the safety validation of automated driving functions by OEMs and Tier-1s as well as independent or governmental institutions. Even as new standards for driving simulation languages come into use, this gives rise to the need for translation tools between different driving simulator languages. Two major challenges in this context for translation tools are hitherto not well addressed: 1. Adaptability to new languages or versions thereof. 2. Correctness of translation. We elaborate on some of the central challenges in this regard, present a prototype of a retargetable translator for driving simulation languages, and a suiting translation semantics, as first cornerstones of a future approach to validate or verify translations.