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Titel:

Managing Technical Debt in Automation: Best Practices and Cross-Life-Cycle Strategies Figure 1

Dokumenttyp:
Forschungsdaten
Veröffentlichungsdatum:
12.06.2023
Verantwortlich:
Bi, Fandi
Autorinnen / Autoren:
Bi, Fandi; Vogel-Heuser, Birgit; Huang, Ziyi; Land, Kathrin; Ocker, Felix
Institutionszugehörigkeit:
TUM
Herausgeber:
TUM
Enddatum der Datenerzeugung:
31.03.2023
Fachgebiet:
DAT Datenverarbeitung, Informatik; MAS Maschinenbau; TEC Technik, Ingenieurwissenschaften (allgemein)
Quellen der Daten:
Experimente und Beobachtungen / experiments and observations; Umfragen und Interviews / surveys and interviews; Statistik und Referenzdaten / statistics and reference data
Datentyp:
Bilder / images
Methode der Datenerhebung:
expert interview, coding, data analytics
Beschreibung:
Technical decisions that offer short-term gains but result in long-term disturbances and costs are often made due to the insufficient appreciation or underestimation of their scope, impact, and remedial actions. Technical Debt (TD) is a metaphor that embodies such phenomena and poses a particularly harmful threat when interdisciplinary teams interact and collaborate. The study presents new methods analyzing cross-company TD characteristics and positive TD best practice use cases gathered from 47...     »
Schlagworte:
technical debt, technical debt management, automation, correlation analysis, life cycle, requirements, design, testing, industrial best practice, TD type, TD subtype
Technische Hinweise:
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Sprache:
en
Rechte:
by-nc-nd, http://creativecommons.org/licenses/by-nc-nd/4.0
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