QASource Blog

AI in mobile testing is booming, pushing developers to stay competitive and enhancing regression testing, script, data, performance, usability, and visual testing.

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.

Testing remains a cornerstone for delivering impeccable products in the dynamic world of software development. With AI's emergence in this domain, there's a buzz about its capabilities. But the question remains: Can AI-driven testing truly match the discernment of a seasoned software tester? Let's dive deeper.

AI and ML are transforming the way that retailers do business, and their use in retail app testing can help organizations improve their accuracy, efficiency, and customer experience. In this blog post, we will explore the benefits of AI and ML in retail testing, the different types of AI and ML used in this context, the challenges of implementing these technologies, and best practices for successful implementation. We will also discuss the role of QASource, a software testing and quality assurance provider, in using advanced technologies to ensure that retail apps are functioning optimally.

In recent years, conventional SaaS models have evolved into sophisticated service-oriented platforms geared toward enhancing business efficiencies and capabilities between the company and its suppliers, clients, and business partners. Artificial intelligence has become an integral part of SaaS 2.0, as AI-based SaaS integrations allow businesses to cater to their customers’ needs in DTC, B2C, and B2B markets.

Modern consumers have everything they need right at their fingertips to interact with organizations. They can research, and purchase software products online, and also share their opinions of the product and overall consumer experience in minutes.

Application programming interface (API) integration testing is necessary when building any software or mobile application. If your software does not match and supersede the efficiency and quality of other products in the market, it will fail. Let’s understand the basics of API integration.

Artificial intelligence or AI is one of the trends that is highly in-demand in the quality assurance industry. By implementing AI in the test automation framework, QA engineers can expect faster release cycles and businesses can provide good customer experience.

The use of artificial intelligence in test automation is one of the latest trends dominating the quality assurance industry. In fact, in Capgemini’s survey titled World Quality Report 2020-2021, 21% of IT leaders said that they are implementing AI in some form or another in their testing methodologies, while only 2% said that AI has no part in their future planning.