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The latest News and Information on Software Testing and related technologies.

How Low-Code/No-Code is Redefining Enterprise Test Automation

Today, speed is everything, and that has put businesses under immense pressure to develop and deploy applications faster than ever before. The rapid expansion of low-code/no-code (LCNC) development platforms has been driven by this requirement for speed.In fact, Gartner predicts that by the end of 2025, a staggering 70% of new applications developed by enterprises will use LCNC technologies.

How Delphix Virtualization Drives Cost Savings and Cloud-Readiness #shorts

Discover how Delphix’s data virtualization platform pays for itself by eliminating hardware costs, enabling on-demand environment creation, and preparing businesses for seamless cloud migration. With Delphix, teams can deliver higher-quality products faster, support multiple channels with ease, and strengthen collaboration across the organization.

Risk-Based Approach for Regression Testing: A Practical Guide

Software changes fast. Every new update, bug fix, or feature risks breaking something that used to work. That’s why teams rely on regression testing to make sure the old stuff still runs smoothly. But here’s the challenge: you can’t test everything, every time. Regression test suites get large, fast. Running all of them slows teams down. That’s where a risk-based approach for regression testing makes all the difference. Instead of testing everything, you test what matters most.

Manual vs Automated Regression Testing: A Practical Guide

Regression testing is the process of re-running tests to make sure new code changes don’t break what used to work. It acts like a safety net. If your app used to calculate prices correctly, and now it doesn’t because of a new update. Regression tests are what tell you something broke. Now here’s the real question: should you run those tests manually or automate them? That’s where the discussion around manual vs automated regression testing begins.

Integration Testing: A Comprehensive Guide

Integration testing is a critical phase in software development that ensures different components of a system work together as intended. This blog covers the importance of integration testing, its methodologies, and best practices. Learn more about component and integration testing methods, benefits, and challenges.

What Is A Python Bytestring?

In the programming language, Python, binary data and text are often used when working with files, APIs, data encoding and decoding, and networking. In this article, we are going to answer some of the common questions that arise in this process. Some of which include what bytestrings are, how to convert strings to bytes and vice versa, their differences, and many more. This guide will cover all that is required for you to master bytestrings in Python.

Harnessing AI to save time for Exploratory Testing

Exploratory Testing is one of the most valuable practices in software testing, especially when we want to discover issues that impact user experience. But at the same time, it is also one of the most demanding approaches in terms of time and focus. In a world where product development life cycles are becoming shorter and where QA teams need to ensure faster releases without compromising quality, a question arises: How can we gain time without sacrificing the depth of exploratory tests and their findings?

One Platform to Test Them All: Katalon's ROI from Drinking Its Own Champagne

When Katalon made the decision to run its own quality practice entirely on the Katalon platform, it wasn’t just a symbolic gesture. It was a deliberate business decision to replace fragmented tools, eliminate reporting silos, and sharpen product-market fit—all while holding itself to the same standards expected by our customers.

Self-healing Test Automation: A Practical Guide

Test scripts break. It’s one of the most frustrating parts of test automation. You update a button. The UI layout shifts. Suddenly, dozens of test cases fail because the locators no longer work. This is where self-healing test automation enters the scene. Instead of failing outright, these smart tests diagnose the issue, find an alternative path, and continue running.