Digital transformation, AI, robotic process automation, and aligning an agile IT capability with business outcomes. These are all topics that are close to our heart.
That’s why we’re Platinum sponsors of the Gartner Application Architecture, Development & Integration Summit in London on 20 to 21 May 2019.
A recent study found that nearly half of all internet traffic in 2018 came via a mobile app. Across sectors, it’s clear that smartphones are increasingly the preferred method for accessing web content and the trend is forcing organizations to rethink their approach to app development, accessibility and interoperability.
A year ago, we brought you Performance Matters, our one-day conference in London. Alongside web performance topics and case studies, we talked about intelligent test automation, big data, and how we saw these worlds converging.
A lot has happened in a year. And at Eggplanet, this year’s Eggplant conference in London on 6 June, we have a lot more to show you.
Today’s complex, digital world relies on computer systems and software and downtime is more than an inconvenience—in many industries, it’s a critical failure that can have a lasting, negative impact on customer experience, the corporate brand and the bottom line.
Digital Automation Intelligence offers something truly revolutionary: automated, AI-driven testing of the entire user experience on any technology. But one thing we don’t talk about very often is our integration with other solutions.
Many organizations have existing tools to manage the testing process, and we need to be sure we can work with them. Others may be looking to move to a new test management solution at the same time as switching to Eggplant, and we want to be certain that the move to Digital Automation Intelligence doesn’t constrain their choice of test management tool.
Wikipedia will tell you that “software testing is an investigation conducted to provide stakeholders with information about the quality of the software product or service under test.” While technically accurate, this definition does not encapsulate all that testing does and how critical the function is in our complex, hyperconnected world.
The focus of software testing is changing. It's been moving away from simply checking that an application meets technical requirements and towards ensuring that it delivers better user experiences and business outcomes.
Or at least that's what we'd all like to believe.
The reality is that capabilities can lag behind the desire for change, and not everyone can agree on how best to represent the voice of the customer in the testing process.
A recent Bloomberg headline proclaimed, “Human Spaceflight Could be a $23 Billion Industry by 2030.” The article examined a UBS report on space travel, which predicts that “spaceflight” will compete with long-distance airline flights in the not-too-distant future.
It’s a fascinating prospect, and one that underscores how critical it is for software to perform optimally in mission critical environments. Eggplant’s Antony Edwards recently explored this theme in detail in a DigitalisationWorld article, highlighting some of the key technology challenges facing space exploration.
We live in a digital world, with software permeating every aspect of our everyday lives. And businesses are waking up to the fact that the quality of that software is critical to their very existence.
This is where Continuous Quality Meets Business Outcomes, and it’s the theme of our inaugural Eggplanet Europe on 6 June, London.
A recent SD Times article suggested that AI is not delivering tangible testing improvements, cautioning “…customers need to realize there’s probably more hype than reality in most of what test solution vendors are saying.” This sentiment reminds us of the unhelpfully polarized “manual-vs-automated test execution” debate that held back testing for 10 years and we’ve only recently moved on from with the realization that there’s a place for both in testing. It would be catastrophic for the testing industry if we went into another 10 year debate of “AI-vs-non-AI” only to realize that there are strong benefits to AI, but it probably doesn’t solve everything.
These sentiments are unhelpful and dangerous to the testing community. Sure, there are exaggerated claims about the use and impact of AI in some products, but there are also fantastic products that demonstrate that the technology can deliver real improvements today. Below are just a few examples of how AI can help testing now—not several years down the road: