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To ensure the quality of the software product, software quality assurance is conducted comprising activities like planning, setting up the metrics, formal technical reviews, setting up multiple testing strategies, change control, report and documentation.

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.

To formulate a result-oriented quality engineering strategy, enterprises may require buy-in from the management and involve the integration of test automation, AI and ML, and greater collaboration among cross-functional teams.

The agile testing lifecycle comprises the planning of a sprint, designing a test case framework, conducting actual testing, ensuring product stability, and executing regression testing.

Quality engineering has become imperative for organizations to adopt given the increased demand for quality in the entire span of the product development, testing, and deployment process.

The barriers to a successful digital transformation include resistance to change, the prevalence of talent gap and a risk-aversion culture, continuance of old practices, and a silo-driven ecosystem.

Software quality assurance is extremely important for the diagnostic tools as well as healthcare apps to offer 100 percent accurate results. The same can lead to better diagnosis and setting up of accurate treatment protocol.

Test automation in Agile and DevOps testing can bring about a host of benefits – both to the developers and end customers. They can help the business achieve Continuous Integration and Deployment on a consistent basis.

Software quality assurance should be robust enough to identify glitches and meet the customer experience. It should be suitably redefined to incorporate the latest methodologies and technologies.

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.