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Benchmarking Requirement Template Systems
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2025
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Gesellschaft für Informatik, Bonn
Zusammenfassung
Our publication 2024 in the Requirements Engineering Journal concerns the multiple semi-formal syntax templates for natural language requirements, that foster to reduce ambiguity while preserving readability. Yet, existing studies on their effectiveness do not allow to systematically investigate quality benefits and compare different notations. Extending previous work, we strive for a comparative benchmark and evaluation of template systems to support practitioners in selecting template systems and enable researchers to work on pinpoint improvements and domain-specific adaptions. We conduct experiments with five popular template systems—EARS, Adv-EARS, Boilerplates, MASTER, and SPIDER. First, we compare a control group of free-text requirements and treatment groups of their variants following the different templates. Second, we compare MASTER and EARS in user experiments for reading and writing. Third, we analyse all five meta-models’ formality and ontological expressiveness based on the Bunge-Wand-Weber (BWW) reference ontology. It shows that templates can generally improve various quality factors compared to free text. Although MASTER leads the field, there is no conclusive favourite choice, as most effect sizes are relatively similar.