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For the second time, I’m excited to be a guest on On .NET Live on May 18th at 9 AM PST! I’ll be talking about one of my favorite subjects: coding standards and how they can supercharge .NET code quality, performance, maintainability, and consistency across your projects. Join us live and bring your burning questions. … Continue reading On .NET Live: How Coding Standards Supercharge .NET Quality & Performance →

When populating collections in .NET, choosing the right bulk operation improves both clarity and efficiency. Methods like AddRange() and InsertRange() allow multiple items to be added in a single call, reducing overhead compared to repeated individual inserts and clearly expressing intent. When combined with proper capacity planning, these approaches help produce predictable, maintainable code—whether items are being appended or inserted at a specific position.

In March 2026, I challenged GitHub Copilot to build a Visual Studio extension, "Version Sync," from scratch without coding. Despite initial failures and needing extensive feedback, it succeeded in creating an extension to sync project version numbers. However, Copilot's code quality was lacking, emphasizing that AI can't replace experienced developers.

CharacterExtensions is a utility in the DotNetTips.Spargine.Extensions namespace that enhances performance in ASCII character processing. It offers high-performance methods for character classification, case conversion, and digit extraction, emphasizing minimal overhead. This tool is ideal for developers prioritizing speed and clarity in performance-critical .NET applications dealing with ASCII input.

The excerpt emphasizes the importance of clarity and maintainability in designing APIs and methods in Microsoft .NET. It explains that while out parameters can be useful, they often lead to reduced readability and increased complexity. Their use should be limited to specific scenarios, particularly the Try pattern, for clearer, more maintainable code.

Checking whether a collection contains a specific item is a routine task in .NET, and with `Contains()` available on many collection types, it’s easy to assume they all perform similarly. In reality, the underlying data structure and search strategy make a dramatic difference, turning what looks like a simple lookup into a potential performance trap in frequently executed code paths. This article explores how different collections approach item searches, why those differences matter, and how making informed choices can lead to faster, more predictable, and more scalable applications.

Join Taylor Desseyn and David McCarter live on the Guidance Counselor 2.0 podcast on April 21, 2026, at 9:30 AM CST. They'll discuss strategies for success in the tech job market, insights from McCarter's book "Rock Your Career," and provide valuable advice for preparing for technical interviews. Don't miss it!

String searching is fundamental to modern applications, yet its performance impact is often overlooked. This article explores how common string search patterns can quietly slow down your code—and how small, intentional changes can unlock up to 3× faster execution. Backed by real benchmarks, it shows why paying attention to string search performance matters far more than most developers realize.

Count vs IsEmpty can be the difference between fast code and a performance disaster. For some immutable and concurrent collections, the wrong choice is tens of thousands of times slower.

The excerpt from "Rock Your Code" advises caution when using StringBuilder with non-string types, highlighting that unnecessary conversions can hinder performance.