Systems | Development | Analytics | API | Testing

First published on the BSA site along with DXC Technology Data analytics and generative AI are revolutionizing the approach organizations take to software development, testing, and delivery, enabling standardization and scalability across the board, including test automation and management. Like other sectors, financial institutions struggle to match the rate of transformation necessary to maintain a competitive edge.

Artificial intelligence (AI) has taken the world by storm. ChatGPT was the ultimate proof of concept, demonstrating the power of large language models and AI in easy-to-understand terms. So naturally, business leaders are eager to unlock the productivity benefits that come from integrating AI into business operations. But despite their eagerness, organizations still need to do some work to prepare for AI integration.

Setting up and running a successful ecommerce store has never been easier. Tools like Shopify have always kept things simple, but the rise of AI has made it extremely straightforward for anyone to create various assets required to run a successful ecommerce store. These include landing pages, images, ads, and so many other things. The rise in AI has led to the introduction of hundreds and thousands of new SaaS tools.

Developers striving to learn iOS face a rate of change that’s unprecedented in mobile history. iOS 17 is about to go live, just weeks after Apple released the latest versions of iOS 15 and 16. The latest upgrade will cut off all versions up to the iPhone X (which itself is only six years old) and comes with: If you really want to learn and master iOS app development, you need a blend of learning resources that cover all these topics, as well as all the basics of iOS.

We're delighted to unveil Choreo TestGPT, Choreo's innovative approach to API testing powered by Generative Pre-trained Transformer (GPT) 3.5 large language model (LLM) from Azure OpenAI. This allows users to test APIs running or proxied via Choreo using natural language, serving as a complementary tool to traditional testing methods. It offers a convenient way to quickly test endpoints without delving deeply into API specifications or crafting intricate JSON payloads.

GraphQL is a query language to enable applications to fetch data from servers. In fact, as it isn't tied to any specific database or storage engine, GraphQL can aggregate data from multiple sources to create a natural representation of your data. The representation is a graph. The following image illustrates a typical GraphQL abstraction: A few common GraphQL use cases include.

NLP is a field of AI that enables machines to understand, interpret, and generate human language in a way that is both meaningful and contextually relevant. Recently, ChatGPT and similar applications have created a surge in consumer and business interest in NLP. Now, many organizations are trying to incorporate NLP into their offerings.

Mobile test automation has become a crucial aspect of software testing due to the increasing popularity of mobile devices. However, the lack of simple and focused toolsets has resulted in a gap in the availability of effective mobile test automation skills in the industry.

Although it might seem a little early, I was just thinking: what will 2023 be remembered for? For many it will be the year that Beyonce and Taylor Swift took to stages around the world and pushed the boundaries of live music (I’m a confirmed Swiftie if you didn’t know). It is also the year of AI. When I speak with customers, they all talk about how they are steering towards AI adoption.