Multidimensional Framework for Characterizing Verification and Validation of Automated Systems
Joseba Andoni Agirre, Ahmet Taylan Yazıcı, Katia Di Blasio, José Luis de la Vara, Behrooz Sangchoolie, Uğur Yayan, Raul Barbosa, Leire Etxeberria, Massimo Nazaria, Mustafa Karaca · 2022
Verification and Validation (V&V) of automated systems is becoming more costly and time-consuming because of the increasing size and complexity of these systems. Moreover, V&V of these systems can be hindered if the methods and processes are not properly described, analysed, and selected. It is essential that practitioners use suitable V&V methods and enact adequate V&V processes to confirm that these systems work as intended and in a cost-effective manner. Previous works have created different taxonomies and models considering different aspects of V&V that can be used to classify V&V methods and tools. The aim of this work is to provide a broad, comprehensive and a easy to use framework that addresses characterisation needs, rather than focusing on individual aspects of V&V methods and processes. To this end, in this paper, we present a multi-domain and multi-dimensional framework to characterize and classify V&V methods and tools in a structured way. The framework considers a comprehensive characterization of different relevant aspects of V&V. A web-based repository has been implemented on the basis of the framework, as an example of use, in order to collect information about the application of V&V methods and tools. This way, practitioners and researchers can easily learn about and identify suitable V&V processes.