Automation insights and productivity tips from LEAPWORK.
Steep learning curves make it difficult to evaluate automation tools within a reasonable time frame. This can cause the evaluation to drag out and in the worst cases, automation projects are tanked altogether.
Most mistakes in test automation are predictable and can be avoided by following best practices. Here's a handful of guidelines to help you achieve success with automation:
The 2018.1 Release of the LEAPWORK Automation Platform introduces a new Controller – the software that, among other things, stores all the data used in automation flows. With the new Controller, LEAPWORK users can ensure that their data storage in relation to test and process automation is GDPR compliant.
Failing digital channels can have a devastating effect on your revenue stream. In this post we’ll look at how to ensure the quality of e-commerce operations with the help of test and process automation.
So far, test automation has been synonymous with programming. Why? Because all available test automation frameworks and tools are dictating it.
Websites and web applications are crucial to how businesses acquire customers, and a growing number of traditional front- and back-office applications are migrated from desktops to web-based interfaces. As web technologies come with their own challenges, being able to test them is highly critical.
Selenium WebDriver is great for automating browsers, but as a stand-alone automation tool it has some limitations. This post compares script-based Selenium automation with LEAPWORK web automation.
IT projects are multidimensional and difficult to perceive. How do you test a project with potentially infinite dimensions?
When a company decides to adopt new methods or change existing processes, for example by rolling out new software, it often requires that employees upgrade their skill set or learn completely new skills. One way to ensure that an employee has the required skills is to rely on certification. The same goes for consultants who need to document that they are proficient in the tasks they are hired to do.
Once a test automation strategy has been approved and the implementation plan has been initiated, there will inevitably come a point at which testers will begin asking themselves: “Can we trust the results generated from automated testing?”
As test automation is introduced to the software delivery process, the amount of available test results explodes. Robots, or test execution agents, can run 24/7 without breaks, and, on top of this, the number of test cases accumulate during each sprint. As such, more results are produced to be managed and analyzed. This requires the right approach.
Test automation is a cornerstone in DevOps, and when implemented correctly, it helps increase output quality while containing costs. Not surprisingly, IT departments everywhere are realizing the importance of having an actual test automation strategy, instead of just putting out fires here and now.
Too many test automation projects fail – and often for predictable reasons. To help you avoid these pitfalls, we have condensed the most common issues into this short guide along with related best practices for achieving success with automation.
Once a QA team has made the case for automation and is moving from doing all testing manually to introducing automated testing, the change process often comes with some challenges that need to be addressed.
Automation is a prerequisite for success with DevOps. Especially test automation is a key ingredient when it comes to providing fast and accurate feedback to testers and developers enabling quick reactions to errors, bugs, and changing requirements.
Agile transformation helps businesses manage change and pursue emerging opportunities in any market situation. A key ingredient of this approach is to implement agile testing.
In a world where new business models are disrupting established revenue streams and expectations to the customer experience are constantly increasing, businesses everywhere are struggling to stay relevant. To stay competitive requires efficiency: Fast market adaptation, well-organized change management, and the ability to secure emerging opportunities. One of the ways to get there is through agile transformation.
When implementing test automation there are several things to consider, including: how much can we automate? which tool is right for us? can we justify the initial investment of time and effort? and much more.
Business-critical processes of everyday work often involves several applications across environments, i.e. both desktop and web applications. This makes it especially challenging to test those processes with conventional methods.
Proactive quality assurance and early-stage bug fixing require testing, and as more product features are introduced and released more frequently (continuous delivery), the need for repeated testing mounts rapidly.
The Data Builder Pattern is used to automatically create data in the system under test. In this post, I will show how to apply the pattern using LEAPWORK to generate data and increase the value of automated test cases.
Artificial Intelligence (AI) is an intriguing – and sometimes intimidating – phenomenon. It is no longer the stuff of a faraway future. With headlines warning about job elimination, it is only natural for professionals in any industry to think about how AI will affect their work.
By taking a look at how Robotics Process Automation (RPA) is defined, we find obvious similarities with the concept of visual GUI / UI test automation.
In any organization, every single day, a myriad of processes and tasks are performed in and between desktop applications.
At TestExpo 2017, held in August 31 in Copenhagen, LEAPWORK's CTO, Claus Topholt, presented our idea of flowchart-based automation design. The novel approach generated a lot of buzz among conference attendees.