Print Email Facebook Twitter Graphical vs. Tabular Notations for Risk Models: On the Role of Textual Labels Title Graphical vs. Tabular Notations for Risk Models: On the Role of Textual Labels Author Labunets, K. (TU Delft Safety and Security Science) Massacci, Fabio (Università di Trento) Tedeschi, Alessandra (Deep Blue srl) Date 2017 Abstract Security risk assessment methods in industry mostly use a tabular notation to represent the assessment results whilst academic works advocate graphical methods. Experiments with MSc students showed that the tabular notation is better than an iconic graphical notation for the comprehension of security risks. [Aim] We investigate whether the availability of textual labels and terse UML-style notation could improve comprehensibility. [Method] We report the results of an online comprehensibility experiment involving 61 professionals with an average of 9 years of working experience, in which we compared the ability to comprehend security risk assessments represented in tabular, UML-style with textual labels, and iconic graphical modeling notations. [Results] Tabular notation are still the most comprehensible notion in both recall and precision. However, the presence of textual labels does improve the precision and recall of participants over iconic graphical models. [Conclusion] Tabular representation better supports extraction of correct information of both simple and complex comprehensibility questions about security risks than the graphical notation but textual labels help. Subject Cognitive fitComprehensibilityEmpirical studyRisk modelingSecurity risk assessment To reference this document use: http://resolver.tudelft.nl/uuid:1e5aebdd-cfae-4745-9751-463be738dd7b DOI https://doi.org/10.1109/ESEM.2017.40 Publisher IEEE Source Proceedings of the 11th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2017 Event ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2017, 2017-11-09 → 2017-11-10, Toronto, Canada Bibliographical note Accepted Author Manuscript Part of collection Institutional Repository Document type conference paper Rights © 2017 K. Labunets, Fabio Massacci, Alessandra Tedeschi Files PDF SSRN_id3025473.pdf 654.19 KB Close viewer /islandora/object/uuid:1e5aebdd-cfae-4745-9751-463be738dd7b/datastream/OBJ/view