# A Survey on Formal Verification and Validation Techniques for Internet of Things
## 6 Use of AI in Software Testing
### Advantages
This can help software companies save time and reduce costs by using a single, integrated \(TST_{\text{NG}}\) platform. Additionally, an integrated \(TST_{\text{NG}}\) platform can provide a holistic view of software quality, allowing developers to identify and address issues more effectively. * **Reduction of UI-based \(TST_{\text{NG}}\):** AI can help reduce the need for UI-based \(TST_{\text{NG}}\), which is often time-consuming and expensive. By automating backend \(TST_{\text{NG}}\), AI can help identify issues without the need for extensive UI \(TST_{\text{NG}}\), reducing the overall \(TST_{\text{NG}}\) effort required. Additionally, reducing the need for UI-based \(TST_{\text{NG}}\) can help improve the efficiency of \(TST_{\text{NG}}\) teams, allowing them to focus on more-complex and critical \(TST_{\text{NG}}\) tasks. * **Better code coverage:** AI can help improve code coverage by identifying areas that are not adequately covered by existing test cases. This can help ensure that all parts of the software are thoroughly tested, reducing the risk of issues and vulnerabilities. Additionally, better code coverage can lead to better software quality and reliability, improving the overall user experience and customer satisfaction. * **Improved reliability:** By automating \(TST_{\text{NG}}\) tasks, AI can help improve the reliability of software products. Automated \(TST_{\text{NG}}\) can detect defects and vulnerabilities that may be missed by manual \(TST_{\text{NG}}\), leading to more-reliable and stable software products. Additionally, improved reliability can help reduce the cost and effort required for maintenance and support, improving the overall efficiency and effectiveness of software development teams. * **Improved quality:** Using AI in software \(TST_{\text{NG}}\) can help improve the overall quality of software products. By detecting defects and vulnerabilities early in the development cycle, AI can help ensure that software products are of high quality and meet customer expectations. Additionally, improved quality can lead to better customer satisfaction, increased revenue, and a competitive edge in the marketplace. * **Automated visual validation \(TST_{\text{NG}}\):** AI can also be used for automated visual validation \(TST_{\text{NG}}\), which involves comparing the visual output of a software system with expected results. This can help identify visual defects and inconsistencies, improving the overall quality and user experience of the software. Additionally, automated visual validation \(TST_{\text{NG}}\) can help reduce the effort required for manual visual \(TST_{\text{NG}}\), allowing \(TST_{\text{NG}}\) teams to focus on more-complex and critical \(TST_{\text{NG}}\) tasks. Overall, the use of AI in software \(TST_{\text{NG}}\) offers numerous advantages, including faster time-to-market, improved reliability and quality, and reduced \(TST_{\text{NG}}\) effort and costs. As AI technology continues to evolve, it is likely that more benefits will become apparent, making it an increasingly valuable tool for software development and \(TST_{\text{NG}}\).