Is there a formula or approach to estimate how much you should spend on your quality engineering (QE) efforts? Our CEO, Steve Semelsberger, is frequently asked that question in discussions…
What can quality assurance (QA) teams expect in 2025? This article will cover what software testing trends QA teams should prepare for to succeed this year.
The deadline is looming, June 28th, 2025, and a lot of companies are keen to tell you how they can help you navigate the new European Union member states’ enforcement of the EAA.
Did you know that 90% of mobile users abandon an app because of bugs or performance issues? Smooth app functionality is key nowadays. Without it, users leave quickly.
Volume testing is a type of software performance testing that evaluates a system’s capacity to process massive data volumes within a specific timeframe. It identifies bottlenecks, crashes, or inefficiencies under high data loads, ensuring performance, accuracy, and stability.
A year of milestones and gratitude: Celebrating 10+ years with Testlio and the incredible clients that make it all possible.
As software systems are updated and new bugs are created, previously functioning features may stop working as intended.
In the software testing process, quality assurance (QA) and quality control (QC) are closely related and complement each other to ensure product quality. QA prevents defects through process improvements, while QC ensures that bugs are detected and fixed in the final product.
Manual testing is a type of software testing that involves testers executing test cases step-by-step, observing results firsthand, without relying on scripts or automated tools.
Imagine you are designing a new mobile app that will help global users in managing their schedules. You have spent a lot of time designing the features and polishing the design, but you are not sure how intuitive it really is.
25% to 35% of a software testing team’s time is spent on writing and maintaining test cases. Yet, poorly written or incomplete test cases can lead to missed defects, inefficient testing, and costly rework.
Suppose you’re working on a complex software project with a tight deadline. Your team has limited time and resources, but the application is growing in complexity with each sprint. Testing every feature thoroughly is impossible, so how do you decide what to test first?