When developing software applications, we want to make sure the application does what the software requirements say it’s supposed to do, and testing proves that it does. In this article, I’ll explore how to link requirements to test cases, and I’ll explain what a requirement traceability matrix is and how to build a simple one.

Being a UI developer, I’ve learned one thing: It doesn’t matter how carefully you write your code. Suppose you’ve double-checked that you defined and called all functions the right way or followed all the best practices. Even then you’ll see that a tiny variable can sneak behind and create an error. Now, suppose you find out that for some unknown reason a form validation or submit button isn’t working.

When I’m writing new software, one of the most important thoughts in my mind is how I’ll test to make sure it works. There are lots of ways to test software, and when you’re at your best, you should be using all of them. Sure, you should make sure that your QA team is able to verify that your code works before it goes live. You should make sure that the code passes acceptance tests, too.

Finding slow JavaScript code can be a tricky problem to solve. Small code changes can have a big impact on the performance of your code. Fortunately, many different approaches can help you nail down the exact source of the problem. In this post, you’ll learn about three methods that’ll bring you the results you’re seeking. You can trust manual code inspection, but that has its disadvantages.

Rostyslav Kosmirak is a .NET developer from Ivano-Frankivsk, Ukraine using Rider and Visual Studio IDE. Kosmirak was not looking for a Dynamic Code Profiler when he came across Prefix. Kosmirak explains that initially he was searching through Google for a log management system when he stumbled on Prefix. Upon downloading, Kosmirak discovered hidden performance problems in his code before they manifested to actual performance problems.

Have you ever looked at your website logs and realized they don’t make sense to you? Maybe your log levels have been abused, and now every log categorizes as “Error.” Or your logs fail to give clear information on what went wrong, or they reveal sensitive information that hackers may harvest. Fixing these problems is possible! Let’s explore how you can write meaningful log messages and use log levels correctly.

Welcome to Stackify’s guide to C# exception handling. Why is this topic so important? In modern languages like C#, “problems” are typically modeled using exceptions. Jeff Atwood (of StackOverflow fame) once called exceptions “the bread and butter of modern programming languages.” That should give you an idea of how important this construct is.

Almost every business today runs online. The internet is one of the easiest avenues for businesses to reach users, and websites are a great way to impress your customers. So, when you’re building a web application for your business, it’s important that you make it the best version it can be. To make sure that your web application is good enough to impress customers and avoid any negative impact, you have to test your application and fix any issues.

My computer programming teacher had always told me that 10% of our time is spent developing 90% of our application, and the other 90% of our time finishing the last 10% of our project. Even with a good project plan and a concept that makes logical sense, most of our time will be consumed with fixing errors. Moreover, with JavaScript, our application can run without obvious errors preventing it from being run, so we have to employ several techniques to make sure everything is running smoothly.

CAI stands for Continuous Application Improvement. It is a software improvement process that is implemented at each step of the SDLC, ensuring immediate feedback at each step rather than waiting till risk levels and impact has gone up. When you implement CAI you shift your improvement process as far left as possible and you catch software bugs and performance problems where they are introduced, eliminating countless hours of time spent chasing issues.