International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Informative Article | Science and Technology | India | Volume 7 Issue 11, November 2018 | Rating: 5.1 / 10


The Power of AI Driven Reporting in Test Automation

Rohit Khankhoje [4]


Abstract: In the ever-evolving realm of software testing, the utilization of test automation has become essential. Nevertheless, the significance of test automation surpasses its mere execution. This research paper delves into the transformative influence of AI driven in the realm of reporting for test automation. By incorporating artificial intelligence, we empower test automation to not solely detect defects but also provide actionable insights. Our investigation explores the harmonious relationship between AI and reporting for test automation, with a particular focus on how AI algorithms can extract valuable information from extensive datasets generated throughout the testing process. These algorithms bring to light patterns, anomalies, and correlations that were previously concealed. This newfound intelligence equips testing teams with the capacity to make well-informed decisions, prioritize issues, and improve the overall quality of the product. Furthermore, we examine the practical implementation of report dashboards driven by AI, exemplifying how they bridge the gap between the execution of tests and the provision of meaningful reports. This approach leads to more intelligent testing, accelerated resolution of issues, and ultimately, the development of more reliable software. The paper emphasizes that AI driven is not merely a concept of the future, but rather a current necessity for organizations striving for excellence in test automation. The Comprehensive Exploration of the Influence of AI driven in the Reporting of Test Automation is an in-depth analysis of how AI can enhance the efficiency and effectiveness of test automation, resulting in a fundamental change in our approach to software testing.


Keywords: Test Automation, AI Integration, Reporting Enhancement, Data Analysis, Software Quality Improvement


Edition: Volume 7 Issue 11, November 2018,


Pages: 1956 - 1959


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