Resources

Without question, generative AI in software testing for 2025 (and beyond) promises transformative advancements in the field.

In this white paper, you will learn:

Definition and Importance: Generative AI involves machine learning algorithms to generate new data, test cases, or code, enhancing the speed and accuracy of software testing.

Application Areas: It's increasingly used in sectors like healthcare, finance, and design, for tasks like data simulation, risk analysis, and product design.

Evolution of Testing: The paper discusses the historical development of software testing, highlighting the transformation brought by Generative AI.

Technological Innovations: Significant advancements include autonomous test case generation, predictive testing, and integration with DevOps practices.

Future Predictions: For 2025, trends, like augmented intelligent testing, industry-specific customizations, increased cloud-based AI use, and enhanced reporting and analytics, are expected.

Impact on Testing Processes: Generative AI is revolutionizing testing efficiency, quality, and the collaboration between testers and developers.

This guide explores how intelligent agent system autonomously perform tasks, enhance productivity, and streamline operations across various industries.

Learn how Functionize’s innovative agents leverage advanced AI and machine learning to generate, execute, diagnose, maintain and document test cases autonomously. Download now to unleash the full potential of AI in software testing and elevate your testing processes to the next level.

We show how easily you can integrate Functionize with your existing DevOps workflows. We offer a growing number of native integrations with tools including Jenkins, Jira, PagerDuty, and Xray. This means there is a low bar to entry if you want to transform your DevOps with AI-powered testing.

Digital transformation is a priority for most CEOs. But it causes real issues for your QA team. In any digital transformation, QA teams are under pressure to deliver the green light for every release. But at the same time, the team is trying to stay afloat under the burden of growing test debt. The solution is AI-powered test automation. However, this can sometimes cause your QA team to feel threatened or worried for their jobs. In this white paper, we look at why AI-powered test automation is actually a good thing for everyone involved in QA. Not only can it eliminate test debt completely, it will also help future-proof your job wherever you are on the career ladder.

There was a time when applications were created natively for every platform. Desktop apps were delivered monolithically. Mobile apps were native to each phone platform. Web apps were used for things like eCommerce. Nowadays, we see a very different landscape. Many apps are designed to work cross-platform. There is often no difference between a desktop office app and the web-based version. Sometimes the browser can even replace the OS completely.

This change puts a new emphasis on web UI testing. In this eBook, we will look at the top 10 scenarios for modern web app testing. We will explain what makes them hard, and show how an AI-powered test automation platform allows you to address all 10 scenarios. Finally, we will preview how AI testing will evolve over the coming months and years.

Automation is revolutionizing the worlds of business and IT. The world of testing is no exception. From simple scripts to recorders, and systems that use artificial intelligence, test automation allows testing to be done at scales that were impossible just a few years ago. This is driving the creation of more complex applications and enabling new development models such as CI/CD. In this eBook we discuss how you can assess the level of automation your test tool provides, and we introduce a new model for levels of automation in testing. Using this model will allow you to compare automated testing solutions on a like-for-like basis.

Your test team faces a conundrum every day. How can they help deliver high-quality software quickly while not wasting money on unnecessary testing? Here, we explore how intelligent test automation can solve this and deliver a good return on investment. 

Testing ensures you release quality software that gives your users the best experience. However, there has always been a tension between software quality, speed of delivery, and value for money. The accepted wisdom has been that you can only have two of the three. However, as we will see, intelligent automated testing allows you to have all three. However, before we look at that, we need to understand what testing is, and why it is so expensive.

Will 2021 see the end of the QA winter?

Some years ago, our founder, Tamas Cser, stated that the software industry was stuck in a QA winter. Test automation had languished years behind the rest of the software world. Teams were wasting countless hours writing scripts that then needed constant maintenance. Since then, test automation has evolved significantly. AI-powered testing is making leaps and bounds, test automation is becoming mainstream, and even Selenium is evolving. In this piece, we explore how AI and machine learning will continue to drive improvements in test automation. We will also share our predictions for the year ahead.

Software testing has endured, what I term, a QA Winter. Developers and testers still maintain tests the same way they did in the early ages of the internet. Test automation has fallen far behind — and at Functionize we are on a mission to change that.

Software testing has endured, what I term, a QA Winter. Developers and testers still maintain tests the same way they did in the early ages of the internet. Test automation has fallen far behind — and at Functionize we are on a mission to change that.

Ever since Jason Huggins invented Selenium, professional QA testers have relied on selectors to create automated test scripts. However, recent advances in AI and the onset of intelligent test agents may spell the death of the selector. At the very least, in the next few years, selectors will become far richer and more reliable than we are used to.

Here, we explore why the selector has been so important and why we are predicting its demise.

Autonomous testing is steadily replacing test automation as the default for UI and web app verification. However, migrating from your old system can seem like an impossible step. Many teams feel they are trapped in a migration Catch 22. They fear that migration will take too much time and effort, disrupting their delivery cycle. But the longer they leave it, the worse this situation becomes. In this whitepaper, we want to show you how easy it is to migrate to Functionize, as well as highlighting the true costs of sticking with your legacy system.

Why you need it and how to get started

This ebook examines common types of software tests and their evolution alongside common software development practices. It’s an introduction to testing methodologies within an evolving context of bug finding-and-fixing, including both manual and test automation. And it’ll help you understand why test automation is so critical for the modern software development lifecycle.

In this article we will look at the top 10 reasons why Selenium tests fail. We will also show how Functionize offers a better solution that avoids these pain points.