
Quality gates, steps required to ensure the reliability of code changes, are supposed to increase the confidence stakeholders have in a release. In today's fast paced environments, we have less time to perform the necessary precautions to minimize the risk of a faulty release. This leads to an inherent trade-off between risk of lower release quality and time to market. We provide a model for this trade-off of release confidence and velocity that led to the formulation of 4 categories (cautious, balanced, problematic, madness), in which companies can be classified in. We showcase real examples of these categories as case studies based on previous empirical studies. We close by presenting possible transitions between categories that guide future research.
1712 Software, 10009 Department of Informatics, 1708 Hardware and Architecture, 000 Computer science, knowledge & systems, 000 Computer science, knowledge & systems
1712 Software, 10009 Department of Informatics, 1708 Hardware and Architecture, 000 Computer science, knowledge & systems, 000 Computer science, knowledge & systems
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 19 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
