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Just 10 years ago, most application development testing strategies focused on unit testing for validating business logic, manual test cases to certify user experiences, and separate load testing ...

Talk to any industry insider, and they’ll tell you that the landscape of software testing is undergoing a paradigm shift that’s rendering many existing practices inadequate. The pace of software ...

The hybrid model is emerging as the framework for trustworthy AI in test analytics. It retains traceability and supports continuous learning without losing control of causality. For engineers, that’s ...

The majority of software development teams believe they don’t test well. They understand that the effect of quality defects is substantial, and they invest heavily in quality assurance, but they still ...

Materials testing is critical in product development and manufacturing across various industries. It ensures that products can withstand tough conditions in their ...

It’s been discovered that a new tool using routine blood tests and a simple online app could help detect tuberculosis (TB) ...

For a machine-learning algorithm to be truly—and, in some cases, just marginally—effective, it needs to be trained using data sets that are as close to real-life collections as possible. However, when ...

In the rapidly evolving landscape of data science and machine learning, ensuring accessibility of data is critical for obtaining meaningful insights. Continuous data plays a pivotal role in various ...