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Title:

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

Document type:
Forschungsdaten
Publication date:
12.06.2023
Responsible:
Bi, Fandi
Authors:
Bi, Fandi; Vogel-Heuser, Birgit; Huang, Ziyi; Land, Kathrin; Ocker, Felix
Author affiliation:
TUM
Publisher:
TUM
End date of data production:
31.03.2023
Subject area:
DAT Datenverarbeitung, Informatik; MAS Maschinenbau; TEC Technik, Ingenieurwissenschaften (allgemein)
Resource type:
Experimente und Beobachtungen / experiments and observations; Umfragen und Interviews / surveys and interviews; Statistik und Referenzdaten / statistics and reference data
Data type:
Bilder / images
Description:
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...     »
Method of data assessment:
expert interview, coding, data analytics
Key words:
technical debt, technical debt management, automation, correlation analysis, life cycle, requirements, design, testing, industrial best practice, TD type, TD subtype
Technical remarks:
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Language:
en
Rights:
by-nc-nd, http://creativecommons.org/licenses/by-nc-nd/4.0
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