An Adaptive Scriptless Behavior-Driven Development Automation Framework with Self-Healing Intelligence for Evolving Software Applications
Adaptive Framework; Artificial Intelligence; Behavior-Driven Development (BDD); Dynamic Locator Identification; Machine Learning; Reinforcement Learning; Self-Healing Test Automation; Test Automation
Background: The high rate of user interface (UI) and source code changes in contemporary software development resulted in automated testing failures that augmented maintenance expenses and decreased the usefulness of automated testing. The current tools need regular updating by manual means, which is ineffective and expensive. Purpose: To present the Adaptive Scriptless Behavior-Driven Development (BDD) Automation Framework with Self-Healing Intelligence, which is an artificial intelligence (AI) and machine learning (ML)-driven framework of automatic test failure detection and resolution based on UI drift, broken locators, or timing. Approaches: The framework uses dynamic locator approaches, adaptive test generation, and reinforcement learning to allow updating test scripts in response to application changes. Such a self-healing feature will minimize human intervention and reduce maintenance expenses. An experimental case study was conducted in order to assess the performance of the framework in a practical context. Findings: The framework demonstrated significant advances in automated testing, such as a 30% drop in maintenance speed, reduced number of resources to update tests, a 25 % reduction in total cost of testing since less manual effort is needed, and a 40 % rise in stability of the test suites, which can execute its tests more reliably and with greater accuracy despite the presence of changes to the application. Conclusions: The Adaptive Scriptless BDD Automation Framework with Self-Healing Intelligence goes a long way to improving the flexibility, scalability, and efficiency of automated testing. It enhances the speed of testing, saves costs, and adds confidence in the quality of software, and is therefore valuable for ensuring high-quality standards in dynamic software landscapes. 2026, Innovative Information Science and Technology Research Group. All rights reserved.
Journal of Internet Services and Information Security;Volume;16;Issue;1;pp.291-310
Innovative Information Science and Technology Research Group
https://doi.org/10.58346/JISIS.2026.I1.017 https://www.scopus.com/pages/publications/105033801226?origin=resultslist
Murugan S.S., Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Balamurugan M., Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bengaluru, India