Titelaufnahme

Titel
Cross learning in software engineering from the automotive industry / von Anita Helene Messinger
VerfasserMessinger, Anita Helene
Begutachter / BegutachterinKugler, Hans-Jürgen
Erschienen2011
Umfang76 Bl. : Ill., graph. Darst.
HochschulschriftWien, Techn. Univ., Master Thesis, 2011
SpracheEnglisch
DokumenttypMasterarbeit
URNurn:nbn:at:at-ubtuw:1-50238 Persistent Identifier (URN)
Zugriffsbeschränkung
 Das Werk ist frei verfügbar
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Cross learning in software engineering from the automotive industry [2.22 mb]
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Zusammenfassung (Englisch)

The automotive industry is characterised by an expanding role of software. That means that two domains with quite different philosophy in technology, management, and production work closely together. Both domains started with individual construction disposable for a few people and have a major customer base around the world, today. The technological change trace back to the 19th century with the transition from horse carriages to auto-mobiles and the transition from manual enumeration to the automation of census. The industrial development influenced decisively the company's management, production, and humans' behaviour, at least the society in the 20th century. In the first half of the 20th century the production system was formed from Henry Ford in the United States of America as mass production, and Toyota production system from the family Toyota in the middle of the 20th century in Japan. The lean management affects the way of thinking of many domains down to the present day. Technical systems like electronic control units used in a car are multidisciplinary products, which recommend a high level of availability, reliability, and safety. Software is interwoven with mechanical and electronic parts. The production takes place in highly dynamic and innovative environment with changing relationship and distribution through different suppliers, which imposes high requirements on communication. The challenge for the automotive industry is the increasing numbers of electronic control units used in a car. With the speed of growth several motor vehicle manufacturers express interest in developing the idea of open-source platforms. The willingness to share and expand technology is a turnaround in automotive industry. The community based application standards and platforms for vehicle software architecture independent from the associated hardware will revolutionize automotive software development. The AUTomotive Open System ARchitecture (AUTOSAR) standard, to take as an actual example, serves as a platform for automotive electronic units' architecture. The GENIVI1 platform establishes a foundation upon which automobile manufacturers and their suppliers can add their differentiated products and services streamlining the development and support of In-Vehicle Infotainment (IVI). The team-oriented development teams of open source software belong to different organizations without being subject to control of only one organization as a consequence. Why is open source software respected now while it was rejected ten years ago? What will the use of open source mean for the organisations in general and the development processes in the companies? Will the future organization structure be flatter and promote creativity and teamwork? Will the development team be open, flexible and pragmatic? Separately from automotive industry software engineering is influenced by the spirit of lean management. Which methods and experiences of lean management are assignable for software engineering? Agile software project management is a topic for ten years. Are agile methods still a spleen of some software developers or the future for software development? The objective of the master thesis is to give an overview about the development of Toyota production system, the influence of automotive industry to management theories and to give a historical summary about software engineering, and to compare the two branches, automotive industry and software development, in regard to similarities and differences as well as mutual learning. Based on the results from this analysis, a plan for future research will be derived from identified deficiencies of existing approaches.