The Impact of Artificial Intelligence on Automation Testing in Quality Assurance
- January 15, 2024
- Posted by: admin
- Category: Software QA
Artificial intelligence (AI) continues to prove its advantages to many industries—including software development and IT. These days, online QA classes are introducing AI to keep learners up-to-date with their skill sets and knowledge for software quality assurance and testing.
Automated testing has been around for a while, with platforms like Unified Functional Testing (UFT) Selenium WebDriver, Watir, Katalon, and others. However, AI is transforming the process by streamlining operations, reducing errors and expenses, and delivering insights into user behavior and other critical information. Now more than ever, it’s becoming an important aspect of automation testing for QA.
How AI is helping automation testing
To assess software and its functions, QA and testing specialists develop test suites and produce test data. Doing these manually can be time-consuming and error-prone, resulting in additional expenses and more time wasted. Complex software also requires more tests, which require additional resources to manage.
Leveraging AI for quality assurance can speed up the testing and verification procedures and overcome those challenges. AI also improves automation testing in QA by:
- Automating testing operations
- Comprehensive API testing supervision
- Determining the best method and timing for executing test scripts
- Using AI-based spidering solutions to improve data analysis
Benefiting from AI
Newer online QA classes are teaching software quality assurance and testing specialists how to make the most of AI technology to bring more accuracy, efficiency, and adaptability to their testing procedures. One of the ways AI can help is by recognizing and mitigating security issues and risks. With machine learning (ML), AI becomes more effective at identifying potential anomalies, vulnerabilities, and threats in the code.
In addition, ML algorithms pick up historical data to identify patterns associated with privacy or security issues to enhance the efficacy of security testing. Incorporating AI can strengthen security measures and make the software more resilient against threats.
AI in Software QA also enhances behavioural testing, continuous integration, and performance testing optimization, ultimately streamlining the entire QA process and speeding up time to market.
Boost your software QA skills today by enrolling in one of our online QA classes. Hitek Computer School also offers a free trial so you can determine if our lessons are right for you.