Summary Despite the rapid growth and popularization of virtual reality (VR) applications, which have enabled new concepts for handling and solving existing problems through VR in various domains, practices related to software engineering have not kept up with this growth. Recent studies indicate that one of the topics that is still little explored in this area is software testing, as VR applications can be built for practically any type of purpose, making it difficult to generalize knowledge to be applied. In this paper, we present an approach that combines metamorphic testing, agent‐based testing and machine learning to test VR applications, focusing on finding collision and camera‐related faults. Our approach proposes the use of metamorphic relations to detect faults in collision and camera components in VR applications, as well as the use of intelligent agents for the automatic generation of test data. To evaluate the proposed approach, we conducted an experimental study on four VR applications, and the results showed an of the solution ranging from 93% to 69%, depending on the complexity of the application tested. We also discussed the feasibility of extending the approach to identify other types of faults in VR applications. In conclusion, we discussed important trends and opportunities that can benefit both academics and practitioners.

Mutation testing is well known as one of the most effective approaches to create test cases, which can detect software faults. However, its drawback is the low scalability — if no special attention is given to improve efficiency — that directly affects its application in practice. This paper shows a replication study focused on emphasizing evidence in which the use of distributed processing structures can improve mutation testing. For this purpose, an architecture that enables mutation testing concurrent execution was designed. Five load balancing algorithms responsible for controlling the distribution and execution of data while carrying out mutation testing were evaluated. Experiments were conducted in order to evaluate the scalability and performance of the architecture considering homogeneous and heterogeneous setups. A time reduction of 50% was observed when executing mutants in parallel in relation to the conventional sequential application of mutation testing. The performance gain was above 95% when there was a higher number of nodes in the distributed architecture.

This Research Full Paper reinforces that Software Testing can be a helpful practice to students while working on programming assignments. Considering Software Testing as a process, the testing activity is composed by a sequence of steps. When students write and submit their own test cases, they are responsible for the test design, automation, execution, and evaluation. Otherwise, instructors can provide ready-made test suites, needing only to execute it and evaluate it. In this scenario, we conducted an experimental study to investigate how the programming performance of students from the Computer Science area is affected when Software Testing is integrated with programming. We proposed three different approaches: (i) ad hoc programming; (ii) programming and testing by writing the test suite; and (iii) programming and testing with a readymade test suite. We assessed students' programs in terms of correctness, measured by the pass rate of the reference test suite. Results indicate that students had a lower performance with ad hoc programming in comparison with both approaches involving Software Testing. On the other hand, using ready-made test cases raised better results than when students had to write their own test cases. We also assessed students' attitudes towards testing by means of a survey.