Recommendations for Tracelink Decisions – An Empirical Investigation of Visualizations

Abstract

Today, engineering processes integrate many subsystems from different domains like Mechanics, Electrics or Software. Therefore the systems that are engineered become more and more complex. As system complexity increases, the number of dependencies between subsystems increases as well. Hence, engineers are obliged to keep track on these dependencies via tracelinks. The present paper investigates four types of decision support (percentages, brief information, a traffic light metaphor and a half-star rating) that help engineers to decide if a tracelink should be set or not. Moreover multiple objective and subjective dependent measures were assessed. Despite the pre-study character of the present work results indicate that the half-star rating system was best in terms of objective performance, at least for experts. Implications of these findings are discussed.