![]() |
Testing What You Can’t See: Risk Blindness in Coverage Models The way we think about what necessitates test coverage being “complete” influences how we test and the cases we create. After all, you wouldn't design tests for situations that don't occur to you—and you can't test what you can't see. It's time to take off the blinders. Here's how you can find where the bugs in your products are occurring, and then adjust your strategy to pinpoint them. |
|
![]() |
Brew vs. Pip: Which Package Installer Should You Use? A command-line package installer is a handy tool that installs your desired software package without a fancy UI, yet it often proves to be more effective than some tools integrated into expensive IDEs. Brew and Pip are two of the more popular options for package installers when using the script language Python. But what’s the difference between them, and which makes more sense for your use? Here’s an introduction to Brew and Pip for testers. |
|
![]() |
Taking the Negativity out of Negative Testing Everyone on the software team has the same goal of delivering the best product they can, so letting testers discover bugs is always good—the more bugs found, the better! But misconceptions often lead to testers getting the bad rap of "breaking" the software. It's a tester's job to think like a user. Developers and stakeholders might call that negative testing, but the result is a better product, and that’s all positive. Let's change the way we talk about testing. |
|
![]() |
Testing AI Systems: Not as Different as You’d Think AI-based tools have transformed from a vague, futuristic vision into actual products that are used to make real-life decisions. Still, for most people, the inner workings of deep-learning systems remain a mystery. If you don’t know what exactly is going on while the input data is fed through layer after layer of a neural network, how are you supposed to test the validity of the output? It’s not magic; it’s just testing. |
|
![]() |
Finding the Information inside Your Data Data analysts have to know a lot about diverse business areas so that our reports provide usable information, not just data. We can use this awareness of the value of information to merge different data sets in order to answer new questions, and even help our users make better decisions. But in order to do this, we need to present not just the data, but the information value represented in that data. |
|
![]() |
6 Reasons Automation Projects Fail No matter what the domain or company, there are some common problems that always tend to affect new automation projects. Here are six top reasons automation projects can fail. Keeping these pitfalls in mind will help you to avoid them and instead build stable automation frameworks, making the endeavor a collaborative experience so that your whole team owns automation. |
|
![]() |
Why You Shouldn't Use Cucumber for API Testing Many people misunderstand the purpose of Cucumber. Because it seems to yield clearer, plain-language test scripts, testers want to use Cucumber as a general-purpose testing tool, including for API tests. But its true purpose is as a BDD framework. You may be thinking, what’s the harm? Here’s why it makes a difference—and why you should choose another tool for API testing. |
|
![]() |
The Simple Rules of Software Testing Simple rules are great for guiding us through an overwhelming workload. Sometimes complicated solutions are necessary, but simple rules often outperform complex algorithms, making them more efficient than sophisticated, difficult flows. They can also break down big goals into practical daily guidelines testers can follow to perform more effectively. Let’s see how simple rules can be applied in software testing. |
|
![]() |
Test Everywhere: A Journey into DevOps and Continuous Testing A move to DevOps creates an opportunity to shift the testing process to the left. But what if you went further? DevOps supports continuous testing, so you can advocate for a constant focus on quality, with testing permeating the entire software development process. Here's how you can actually have a faster testing process when the software is tested throughout the lifecycle, by developers, testers, and automation alike. |
|
![]() |
Dealing with a Test Automation Bottleneck The test team uses the test automation system to execute thousands of test cases because … why not? The tests are running automatically, for free, so there is no incentive to improve test efficiency. Just run them all! But eventually, as more and more tests are added, the system becomes overloaded. Test runs are delayed and you get a bottleneck. Don't throw more money—or new systems—at the problem; do this instead. |
Pages
Upcoming Events
Apr 30 |
STAREAST Software Testing Conference in Orlando & Online |
Jun 04 |
Agile + DevOps West The Latest in Agile and DevOps |
Oct 01 |
STARWEST Software Testing Conference in Anaheim & Online |
Nov 05 |
Agile + DevOps East The Conference for Agile and DevOps Professionals |