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Mutation testing applied to virtual reality environments modeled with scene graph

Grant number: 17/19492-1
Support type:Scholarships in Brazil - Doctorate
Effective date (Start): January 01, 2018
Effective date (End): July 31, 2020
Field of knowledge:Physical Sciences and Mathematics - Computer Science
Principal Investigator:Márcio Eduardo Delamaro
Grantee:Stevão Alves de Andrade
Home Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

Applications that uses virtual reality resources or functionality gained popularity due to the vast field of use. It aims to provide the feeling of immersion in the environment, rather than a limited area, such as the simple representation on the screen of a monitor. Despite the benefits that maybe achieved with virtual reality softwares, its implementation mechanisms represent new potential sources of faults that should be handled during the testing phase. In general, the development of this kind of application does not include a systematic software testing process that consider particularities of that application domain. Due to this, most part of the tests developed in the testing phase is fulfilled manually or with ad-hoc approaches. Mutation testing is a widely investigated fault-based test criterion that can help to demonstrate the absence of prespecified faults in the software. However, to date, do not exist initiatives to customizing mutation testing for virtual reality domain. This project tackles these limitations by propose a comprehensive mutation-based testing approach for virtual reality context considering specific types of simulated faults and the need of adequate tool support and proper evaluation. To achieve this goal, it's intended to define a specific fault taxonomy, such taxonomy should be used as base in order to define a mutation-based testing approach. To validate the approach we will perform a wide range of experiments, which will address comparative studies regarding the effectiveness of the proposed approach to detect faults. (AU)