Unlock the potential of AWS Generative AI in DevOps. Experience streamlined code development, improved collaboration, and optimized CI/CD. AWS's cutting-edge AI simplifies and enhances DevOps workflows, making them more efficient.
In our blog, we take a deep dive into the latest QA strategies, methodologies, and industry best practices driving the world of quality assurance. Follow our blog to get new ideas as to how to effectively deliver high-quality, bug-free software products, websites, and applications, while keeping costs low.
Unlock the potential of AWS Generative AI in DevOps. Experience streamlined code development, improved collaboration, and optimized CI/CD. AWS's cutting-edge AI simplifies and enhances DevOps workflows, making them more efficient.
Legacy code is a common challenge many organizations face when dealing with outdated software systems. As technology evolves rapidly, businesses must keep their tech stacks up to date to remain competitive. Converting codes to a modern tech stack can be complex and time-consuming, but AI makes it easy and efficient. This blog covers how AI can streamline the legacy code conversion to the latest tech stack, providing numerous advantages such as efficiency, accuracy, savings, and risk reduction.
Voice recognition and voice assistants have become central to the software as a service (SaaS) industry, changing how we interact with SaaS and promising benefits for businesses and users alike. But if you plan to offer a voice assistant or other voice recognition tool, it’s important to thoroughly test your offering before bringing it to market.
Analysts predict AI's market size in software testing will reach an impressive $4 billion by 2024. But the impact of all this AI is tied to the precision and robustness of the underlying models.
AI in mobile testing is booming, pushing developers to stay competitive and enhancing regression testing, script, data, performance, usability, and visual testing.
Software testing is vital because it allows you to test if an application is working properly. There are various types of tests that you can perform if you work in the software industry. Nevertheless, all these tests fall under one of these two classifications: positive and negative testing. Both categories are equally important, but positive testing is more popular than negative testing.
Micro-services architecture excels in complex, large-scale apps with diverse tech needs and evolving features. Performance testing is crucial for smooth interactions, scalability, bottleneck detection, and reliability. This series explores AI-driven techniques for assessing efficiency and system performance in micro-services architecture.
Tech debt from trade-offs during software development can result in substantial costs for your business. A survey conducted across 200 tech companies disclosed that an average of 25-40% of a developer's time is spent addressing tech debt. And 79% of tech leaders cited tech debt as a significant hurdle in achieving their business objectives, signifying the gravity of this issue. But AI is a game-changer when it comes to reducing it.
In the new era, Automation testing is expected to play a crucial role in software development and quality assurance processes in the coming years. In 2024, it is anticipated that automation testing will become even more prevalent and sophisticated because of advancements in technologies like artificial intelligence and machine learning are likely to enhance automation testing capabilities further. AI-powered testing tools can analyze vast amounts of data, identify patterns, and generate test cases, thereby increasing the efficiency and effectiveness of testing processes.
QASource Blog, for executives and engineers, shares QA strategies, methodologies, and new ideas to inform and help effectively deliver quality products, websites and applications.
Our bloggers are the test management experts at QASource. They are executives, QA managers, team leads, and testing practitioners. Their combined experience exceeds 100 years and they know how to optimize QA efforts in a variety of industries, domains, tools, and technologies.