Development of Cloud and Artificial Intelligence based Software Testing Platform (ChArIoT)

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.

I. Introduction

Traditional software testing methods are limited in addressing the challenges of autonomous systems. However, integrating AI and Cloud-based solutions can greatly improve testing efficiency and effectiveness. AI-powered tools can analyze data, generate test cases, and detect issues, enhancing the quality and safety of autonomous systems. Cloud-based testing platforms provide scalable and cost-effective resources, enabling parallel testing, reducing time, and creating realistic environments. Adopting AI and Cloud-based testing brings significant benefits in terms of cost, effort, and time savings. It expedites defect identification, shortens development cycles, and improves productivity. The ECS-SRIA 2023 plan emphasizes the importance of testing, particularly with AI and cloud systems, to achieve trustworthy and scalable technologies [1]. Comprehensive testing, supported by AI, ensures reliability, safety, and security. Automated testing with AI enables efficient deployment and operation of intelligent and autonomous systems, aligning with the goals of the ECS-SRIA 2023 plan.