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3 Ways AI Will Impact Software Testing

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It’s easy to see why the demand for effective software testing training is on a steady rise. After all, as the digital world expands, so does the complexity and intricacy of software applications. As a result, new technologies like artificial intelligence (AI) are starting to be used in software testing, bringing about a revolutionary transformation. Let’s look at three ways in which AI is set to reshape the industry, consequently reshaping the future of software testing training.


Enhanced reliability


The ever-changing nature of software development often introduces frequent modifications in applications, such as renaming or resizing fields. These seemingly minor changes can lead to failures in traditional testing frameworks like UFT or Selenium, creating a constant demand for test maintenance.


Here's where AI steps in, offering a robust solution to this prevalent issue. AI can correct and adapt the testing code, making it more reliable and maintainable. It eliminates the need for testers to modify the test with every small change developers make. AI and Machine Learning (ML) tools are capable of reading and understanding the relationship between changes made to the application. This results in improved reliability of software tests, significantly reducing the time and effort spent on maintaining test scripts.


Automation of visual validation


The rising popularity of image-based testing using automated visual validation tools is a testament to the power of AI in software testing. Machine Learning (ML) based visual validation tools can identify even the minutest of UI anomalies that might be missed by human testers. The primary aim of UI testing is to ensure that each UI element appears as intended—correct shape, colour, size, and position—without physically overlapping with other UI elements. These visual inconsistencies can be easily detected by an ML test, reducing the need for manual intervention.


Automatic generation of test cases


The process of manually writing test cases can be time-consuming and prone to human error. This is where AI comes into play, automating the generation of test cases and significantly improving efficiency. The use of AI allows for a more thorough examination of possible scenarios, leading to a comprehensive set of test cases. Moreover, AI algorithms can analyse software applications on a deeper level, identifying potential edge cases that might be overlooked by a human tester. This saves valuable time and enhances the quality and accuracy of the test cases, further enriching the effectiveness of software testing training.


With the rise of AI in the realm of software testing, it's crucial to keep pace with these technological advancements. Hitek Computer School—with its comprehensive and up-to-date software testing training—is at the forefront of this evolution. They are committed to providing learners with the skills and knowledge needed to navigate the AI-driven landscape of software testing, making them an excellent choice for anyone looking to embark on or further their career in this field.


Take your software testing skills to the next level with Hitek Computer School's cutting-edge training. Enroll today!


About the Author:

This article is written by Oleg Vertlib, director of Hitek Computer School (established in 2007). Hitek Computer School provides education and training in Software QA and Software Testing to prepare students for manual and automated testing of modern software applications according to the standards of Information Technology. Hitek Computer School is certified by the Minister of Human Resources and Skills Development, Canada, and registered with PTIB (Private Training Institutions Branch of the Ministry of Post-Secondary Education and Future Skills).




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