Software Testing Articles, Blog Posts, Books, Podcasts and Quotes
Software businesses cannot ignore cybersecurity if they don’t want to face fines from regulators, unhappy customers and damages to their reputation. This article explains how to incorporate cybersecurity testing into test management and why a disciplined culture across development, testing, and QA teams matters.
The modern software development landscape is increasingly complex, with growing demands for faster delivery, higher quality, and more innovative features. Against this backdrop, testing processes have had to evolve significantly to keep pace with rapid development cycles without compromising on quality.
Software updates in the modern world need to happen as rapidly and as often as possible. The pace of the digital world is relentless and unforgiving to any platform that can’t keep up. Simply put, sites and platforms that don’t update often can’t survive. There are just too many variables to keep up with.
In the fast-paced world of online poker, the difference between a great platform and an average one often comes down to the way its software is tested before reaching players. Americas Cardroom, one of the leading US-facing poker operators, has recently rolled out Survivor Flips, a game designed to get players into big-money tournaments within minutes.
In performance testing, you need a lot of data to get results that are meaningful for a production context. In this article, Sudhakar Reddy Narra explains why you should not just focus on the quantity, but also on the quality of the data that you are going to use in your tests.
Advances in voice artificial intelligence have greatly transformed the way we interact with digital systems. From smart speakers to sophisticated content creation devices, AI voices are becoming increasingly integral to our daily lives. This growing dependence on man-made speech makes voice quality and speech accuracy a fundamental element of user satisfaction.
In the modern software development lifecycle, test data is as critical as the test cases themselves. Without realistic and diverse datasets, even the most sophisticated automated testing frameworks can fail to detect hidden defects. Traditionally, QA teams have relied on manual creation, production data sampling, or synthetic generation tools. However, with the rise of Generative AI in 2025, the game has changed.
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