The news came out last Monday: Salesforce has acquired its third data intelligence startup of the year. This comes fast on the back of their April purchase of MetaMind and the February purchase of PredictionIO. Details aren’t yet available about how these technologies will be absorbed into Salesforce’s core offerings, but with technology like MetaMind’s image recognition it will be interesting to find out.
Salesforce’s focus on data-driven software and analytics has certainly been intensifying. Salesforce CEO Marc Benioff said recently:
“This will be the huge shift going forward, which is that everybody wants systems that are smarter
It makes sense, right? Smarter tools save us time and effort and give better return on investment. They also make our jobs more interesting by taking away repetitive or monotonous activities.
So how can we get smarter with test automation?
Often this is done by hiring smart test automation engineers. They have the technical skills needed to program tests using Selenium or other code-based frameworks. These are time-consuming to set up and laborious to maintain. And it often comes unstuck then the “smart” engineers move on, leaving a framework that no-one else understands to gather dust.
This kind of test automation is not maintainable, scalable or cost-effective. It basically relies on smart people instead of being smart itself.
But this can’t be the future, can it? We shouldn’t have to rely on smart people. We need to bring ‘smart’ into the tools.
When we started Provar, we set off with this mission in mind. Our mission was to make a tool that understood Salesforce intuitively, like a human does.
How did we do that? Our solution was to integrate Provar to the metadata of Salesforce itself. This gives Provar a native understanding of how Salesforce works and how to test it. So Provar automatically suggests field locators that won’t break. It recognises when a page layout change or a Visualforce page change is only cosmetic. It knows that for testing a console you need to start by closing any existing tabs. It automatically cleans up test data after each test run so that you don’t blow your limits. It can reach out to other systems to verify test results in a different database or email system.
Setting these things up in Provar doesn’t take time the way that it does in code. That’s because you’re not teaching the tool to be smart – it already is.
Most test automation strategy advises:
“Pick the simplest tests”
“Find the most repetitive and monotonous activities”
“Don’t automate anything too complicated”
This is good advice, but it’s built on the belief that only the simplest test automation can deliver ROI.
With a smarter testing tool you can turn this on its head.
When we start working with a customer, we don’t ask for the simplest tests to automate. We actually say the opposite: “what are your hardest, most complicated tests? Give us those.” We have still never found a test that we can’t deliver.
Our customers report a reduction in regression testing time ranging from 50% to 94%. An independent comparison found us between 4 and 6 times faster than Selenium across test authoring, maintenance and execution. We’re proud of these results but we’re not surprised.
This is the power of a smart tool, and it’s just getting smarter.
Originally posted on linkedin on 16 May 2016.