 |
Tackling Testing Challenges in an Agile Transition Even though jumping onto the agile bandwagon is tempting for businesses, it is not always easy, and a transition to agile is likely to come with a slew of challenges for testing in particular. In order for agile to enable delivery of quality products at speed, testing has to begin much earlier in the process than ever before. Enabling certain practices will help your organization achieve a more successful transition to agile testing. |
|
 |
An Introduction to Web Optimization Testing When testing websites, most software testers check the functionality and the UI of the page. But webpage optimization is another area that should get consideration. There are a variety of factors, such as relevance and readability, that search engines consider in webpages before assigning a position in search results, and testers can help positively influence this ranking by increasing site speed and removing blockers to usability. |
|
 |
JUnit vs. TestNG: Choosing a Framework for Unit Testing There are multiple frameworks available for unit testing, and for any type of programming language. For Java developers, JUnit and TestNG are the most widely used. These frameworks are siblings and have the same test roots, and the debate over which is better is complex. Let’s look at how these two testing frameworks are different from each other, and which framework is better suited for your unit testing. |
|
 |
Embedding Security in a DevOps World Faster DevOps processes also create new challenges. It was difficult enough to add security into a traditional waterfall software development lifecycle with monthly or quarterly releases, but now software updates are released several times a day! What can developers do to build and maintain more secure applications? Here are some ways to encourage better security practices throughout the DevOps lifecycle. |
|
 |
Bringing Continuous Testing to Your Organization Continuous testing means all your tests are executing all the time, providing continuous feedback into the quality and health of your applications. In order to achieve continuous testing, you must first adopt the right test automation strategy. Understanding how to bring in all different types of test automation practices as efficiently as possible enables you to get started down the path of continuous testing. |
|
 |
Using Computer Vision to Reduce Test Automation Blind Spots The standard test automation toolkit easily completes web and mobile automation, but it fails to detect elements on desktop and mobile content-based applications. Computer vision (CV) replicates the human eye using deep learning technology and can determine objects in pictures, which helps machines orient in space and perform repetitive detection tasks. Let's see how CV can help automate the testing of a much wider software product list. |
|
 |
Improve Tester-Developer Relationships with Helpful Feedback Testers and developers often have a strained relationship. Each side has a certain level of expectations as to what the other side should know and do, while there is little understanding of the constraints, conditions, and requirements that the other team has to work within. But it does not have to be this way. A little effort in giving more specific and helpful feedback can go a long way toward improving attitudes. |
|
 |
Integrating Security and Testing Practices QA and information security use different methods to approach the same goals. When both groups work together, they can make a greater impact on the security of our products. Here's how the QA team can collaborate with infosec to implement strong security standards, prioritize what to test, and obtain quicker feedback on processes, ultimately seeing fewer production incidents related to security. |
|
 |
A Simpler Way of Using Machine Learning to Shift Testing Left The advantages of shifting left and testing as early as possible are obvious. But as you automate more testing, the test suite grows larger and larger, and it takes longer and longer to run. Instead, just automate the process of finding the right set of tests to run. The key to that is machine learning. This isn't AI bots finding bugs autonomously without creating tests; this is a different way to use machine learning, and it’s far simpler. |
|
 |
More Than a Score: Taking a Deeper Dive into Your Metrics One key benefit of metrics is that they can be measured using a standard process; we can explain the numbers, and leadership can understand what that means. The downside is that it is only a measurement, so issues can easily hide until they become problems, and great work can also go unrepresented. Sporting events are a great example: The end score tells you who won, but not the details of the game. We need to look deeper. |
Pages
Upcoming Events
| Jun 02 |
AI Con USA Bridging Minds and Machines |
| Sep 22 |
STARWEST Software Testing Conference in Anaheim & Online |
| Oct 13 |
Agile + DevOps USA The Conference for Agile and DevOps Professionals |
Recommended Web Seminars
| May 23 | How Generative AI Boosts Speed and Quality in Software Testing |
| On Demand | Building Confidence in Your Automation |
| On Demand | Leveraging Open Source Tools for DevSecOps |
| On Demand | Five Reasons Why Agile Isn't Working |
| On Demand | Building a Stellar Team |
