AUTOMATED TESTING OF WEB PROJECT FUNCTIONALITY WITH USING OF ERROR PROPAGATION ANALYSIS

Abstract

Automated testing is indispensable in the area of software engineering, particularly for web project functionality, as the complexity of software systems continues to surge. This paper delves into the pivotal role of automated testing and how the integration of error propagation analysis, grounded in chaos theory, can elevate its efficacy. The objective is to elucidate the significance of this methodology and its application in bolstering the reliability and performance of web projects. Automated testing automates the execution of predefined test cases, offering efficiency gains, reduced human error, and swift defect detection in software development. Various testing approaches, including unit testing, integration testing, and regression testing, cater to distinct facets of software functionality, ensuring seamless operation of all components. Web project functionality is integral to the user experience, encompassing navigation menus, forms, and search features. Testing this functionality is imperative to unearth inconsistencies or errors that could compromise user satisfaction and task completion. This paper proposes a methodology for automated testing coupled with error propagation analysis, which involves scrutinizing how errors evolve through a system over time. Chaos theory, a branch of mathematics examining complex systems' behavior, is employed to understand how minor variations in initial conditions can precipitate substantial system behavior shifts. Traditional error propagation analysis hinges on linear, deterministic models, but real-world systems often exhibit non-linear, chaotic characteristics, rendering such models inadequate. Chaos theory's non-linear dynamics model the intricate interactions between input variables and their effects on outputs, capturing the sensitivity of chaotic systems to initial conditions. This approach appreciates system complexity and intricate feedback loops, enhancing error analysis's robustness and accuracy. However, the application of chaos theory introduces complexity and computational demands, necessitating a balance between model intricacy and practicality. The proposed methodology unveil valuable insights into error propagation within web projects' functionality, pinpointing vulnerable components and areas ripe for improvement. The methodology's advantages include the ability to identify potential issues and vulnerabilities, ultimately enhancing web project reliability.