Software Testing Blogs Hotlist | Testing Feeds

AI-based automation testing helps the testing processes to achieve a slew of benefits. These include automated building and maintenance of test suites, predictive self-healing, visual validation, and cloud-based virtualization.

To pack a punch with the QA initiatives, business enterprises are utilizing AI-based testing to predict user behaviour, automate continuous testing, identify the root causes of glitches, and improve profitability, among others.

Digital transformation is the need of the hour for enterprises to improve productivity and deliver better customer services. The scale and quality of such transformation can be enhanced by leveraging AI and IoT technologies.

Artificial intelligence has become the go-to area for the QA and development teams to enhance the quality of software within short turnarounds. The rich analysis offered by the AI-based tools can be predictive, diagnostic, and prescriptive in nature.

AI tools can significantly enhance the level of software quality assurance leading to better test outcomes. They should be chosen with due care to achieve QA and cost optimization.

Artificial Intelligence and machine learning can help address the growing complexity associated with QA by writing and executing automated codes and predicting the users’ needs.