Visual Test Framework: Enhancing Software Test Automation with Visual Artificial Intelligence and Behavioral Driven Development

Software test automation plays a crucial role in today's software needs. Traditional test automation approaches often rely on script-based testing, which can be time-consuming, error-prone, and challenging to maintain. In recent years, Visual AI (Artificial Intelligence) and Behavior Driven Development (BDD) have emerged as valuable approaches to enhance the efficiency and effectiveness of software testing. Visual AI leverages machine learning algorithms to identify visual differences in Graphical User Interfaces (GUI), accelerating the test automation process and improving accuracy. BDD focuses on defining and automating system behavior from the end-user perspective, fostering collaboration between stakeholders and eliminating the need for specialized technical expertise. This paper explores the integration of Visual AI and BDD in software test automation, aiming to evaluate its impact on test creation, execution, and maintenance. The research employs a mixed-methods approach, including surveys and evaluations of the Visual Test Framework integrated with Visual AI tools. The findings provide valuable insights into the benefits and challenges of integrating Visual AI and BDD in software test automation, highlighting their potential to streamline testing processes, improve accuracy, and eliminate technical barriers. This paper recommends the usage of Visual AI with BDD