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

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 semi-structured expert interviews in the industrial automation domain. The three most important life cycle phases, the requirement, design, and testing phases, are addressed. The analysis demonstrates that, like adverse TD incidents, cross-life-cycle ripple effects can be advantageous or disadvantageous to the system. By implementing one measure, the system can benefit in multiple life-cycle phases and even disciplines. Additionally, the measures identified can prevent and eliminate numerous TD types and subtypes. The study elaborates on 31 measures that address 129 TD subtypes and proposes a systematic lessons-learned-based step for managing TD incidents in the automation sector.     «

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...     »