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.
Why is monitoring microservices so important? It’s because we work in a time where systems are complex, distributed across multiple microservices. For example, even a simple e-commerce app may have Ordering, Product Catalog, and Shipping services. Our tooling and practices sometimes struggle to keep up with such complexity.
For any business to succeed, it’s important for it to reach users effectively. Almost every business today is online and therefore reaches users through applications. If you run an online business, or if you are a part of such a business, it’s important for you to know what impact your application has on your users. One of the best ways for you to know what impact your application has on the user is through end user monitoring.
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.
