Abstract:
In the rapidly evolving field of autonomous systems, the traditional methods of software testing have proven to be time-consuming, resource-intensive, and inadequate in a...Show MoreMetadata
Abstract:
In the rapidly evolving field of autonomous systems, the traditional methods of software testing have proven to be time-consuming, resource-intensive, and inadequate in addressing the complex challenges posed by these systems. This highlights a pressing need for more efficient and effective testing methodologies. In response to this, we present ChArIoT, a cloud-based web platform that leverages the power of artificial intelligence (AI) and the MERN Stack architecture to conduct mutation testing on Python codes. ChArIoT provides a scalable and cost-effective solution, offering flexible testing environments, improved test coverage, and enhanced accuracy. By integrating AI into mutation testing, ChArIoT significantly reduces time and resource requirements, thereby advancing the effectiveness and efficiency of the testing process. The system infrastructure has been improved to accommodate various AI models, enhancing customization capabilities based on user requirements. Specifically, the platform can adapt its mutation functionalities to match the abilities of installed models, such as code fixing or code generation. This study underscores the superiority of AI and cloud-based testing over manual methods, emphasizing the value of ChArIoT in ensuring trustworthy operation for autonomous systems.
Date of Conference: 11-13 October 2023
Date Added to IEEE Xplore: 31 October 2023
ISBN Information: