Related Content
 |
Exploring the Features of CodeWhisperer and Its Role in the Future of Coding Learn how Amazon CodeWhisperer is uniquely designed to help you develop better code faster, improve security, protect your privacy, and strengthen—not threaten—your career as a coder. |
|
 |
Using Pipelines for CI/CD Continuous integration and continuous deployment have become very important in the daily workflow of building a product to production. We take a look at the stages necessary to have a well-functioning CI/CD pipeline. |
|
 |
Requirements Discipline: Avoiding “Death by a Thousand Paper Cuts" Absent an effective requirements baseline it is difficult to distinguish clarifications and error correction from enhancements and changes to the original ask. |
|
 |
What’s the Problem with User Stories? Agile projects focus on very lightweight, simple requirements embodied in user stories. However, there are some problems with relying solely on user stories. They often don't contain enough accuracy for development, testing, or industry regulations. There's a better way to write detailed requirements that are still agile. |
|
 |
How to Make a Fixed-Scope Contract More Agile Establishing a contract that genuinely supports agile methods can be a significant challenge. By its very nature, a contract that specifies detailed, upfront deliverables contravenes the principles of flexibility and adaptation that are at the heart of agile. But it is possible—both parties just need to focus on results. |
|
 |
Comparing 4 Top Cross-Browser Testing Frameworks The market is flooded with cross-browser testing frameworks, with more options than ever before. How should you decide which option is best to test your application for compatibility with different web browsers? Let’s take a look at four of the top open source solutions today and compare their benefits and drawbacks. |
|
 |
5 Pitfalls to Avoid When Developing AI Tools Developing a tool that runs on artificial intelligence is mostly about training a machine with data. But you can’t just feed it information and expect AI to wave a magic wand and produce results. The type of data sets you use and how you use them to train the tool are important. Here are five pitfalls to be wary of. |
|
 |
Code Integration: When Moving Slowly Actually Has More Risk Many decisions about code branching models are made in the name of managing risk, and teams sometimes pick models that make integration harder in the name of safety. Moving slowly and placing barriers to change can seem safer, but agile teams work best when they acknowledge that there is also risk in deferring change. |
