Automated Test Case Generation with AI: A Novel Framework for Improving Software Quality and Coverage
Senior Quality Engineering Manager, CA, USA.
Review Article
World Journal of Advanced Research and Reviews, 2024, 23(02), 2880-2889
Publication history:
Received on 05 July 2024; revised on 20 August 2024; accepted on 23 August 2024
Abstract:
Modern software testing has become imperative as testing is being automated test case generation: it makes the test efficient, accurate and completely covered. Traditionally, scalability, adaptability, and completeness are the Achilles heels of scalability of traditional testing methods as manual and scripted. In this paper, we introduce a novel AI driven framework for automated test case generation based on deep learning and reinforcement learning using evolutionary algorithm to improve test case generation process. It provides an effective test coverage by dynamically generating and prioritizing test cases according to their historical data, execution patterns and real time software update. AI driven testing reduce manual effort, reduce test execution time, and detects defect earlier in the development cycle as per results. Although the challenge includes the quality of the data, the computing resource demand and application to the complex software system, the future advancement of AI and integration of AI & CI/CD pipelines will further increase the ability of automation in test case generation.
Keywords:
Automated Test Case Generation; Artificial Intelligence; Machine Learning; Software Testing; Deep Learning; Reinforcement Learning; Test Automation
Full text article in PDF:
This paper has received best paper award of (Volume 23, Issue 2, Year 2024)
Copyright information:
Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0