In the past two weeks, this series has taken a look at how often consumers encounter errors while browsing online and some of the behaviors a user will display when discovering a bug. If you’re new to the party, I’ll encapsulate it here by saying mobile apps are rife with coding issues and the vast majority of consumers have little to no tolerance for low-performing software. What we haven’t discussed yet is the ripple effect of one user encountering a problem.

Hello Katalians! Katalon Studio team here with some great news: Our latest release of Katalon Studio (8.3.0) is now available, and it is one of our best releases yet. This release introduces changes to the licensing model and focuses on an enhanced user experience, security compliance, reporting and insights, integration with Katalon TestCloud, and much more. As you can see the list is vast, so without further ado let’s dive right into the details.

Selenium is the oldest and most well-recognized automated testing tool for web apps, so a lot of software teams try it out when they first experiment with automated testing. But most teams quickly run into three Selenium disadvantages: Because of these challenges, many software companies that use Selenium find testing to be a huge drain on time, effort, and resources. That’s why we designed Rainforest QA—to solve the limitations of Selenium and make QA easy to scale and maintain.

Hello to the Testhouse family! This is what I hope will be the first in a series of blog posts aimed at sharing insights into things I have learned or experienced in my career in testing to date. If you find anything that sparks your interest, or have follow up questions, then please do let me know. This first blog is about mentorship, conferences, and the value of networking; I hope you find taking a few minutes to read this will be time well spent!

I am back with blog 3 in this series! In blog 1 I introduced the concept of the Digital Complexity Paradigm (DCP), and in blog 2, I broke down the DCP by focusing on the Technical Complexity factor of that formula. As covered in blog 2, using my favorite “digital transformation of the broom” example, the Technical Complexity enabling today’s digital is getting more and more challenging, and there is no end in sight. That in itself can be a mountain to climb.

Ever wondered, how do you measure testing productivity or testing effectiveness? When to say testing is complete? In all such questions, QA metrics come to the rescue. QA metrics allow test leads or managers to take decisions on various situations encountered in the project life cycle. Tricky part is that QA metrics make sense only in the given context. For example, for one project 95% pass percentage is good to go live but for a safety-critical application anything less than 100% is life-threatening.