On .NET Live: How Coding Standards Supercharge .NET Quality & Performance

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

Collection Performance: AddRange() vs. InsertRange() When Populating Lists

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.

Rock Your Code: I Let AI Build a Visual Studio Extension—Here’s What REALLY Happened

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.

Collection Performance: Finding Items at Blazing Speed

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.

String Performance: Why Some String Searches Are Slower Than You Think

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.

Collection Performance: High-Performance Emptiness Checks for Concurrent & Immutable Collections

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.

String Performance: Avoid Unnecessary Conversions with StringBuilder

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

Coding Faster with dotNetTips.com Spargine 10: April 2026 Release

Spargine 10 (v2026.10.4.1) is released on April 1, 2026, featuring support for .NET 10, new methods, and enhanced performance benchmarks. This open-source project aims to improve reliability and speed significantly. Community feedback and contributions are encouraged to refine and expand its capabilities. Detailed benchmarks are accessible on GitHub.

General Performance: Comparing Methods for Retrieving Process File Path

The excerpt from "Rock Your Code" explains two methods for retrieving the initiating file's path in .NET.

General Performance: Exploring Thread ID Retrieval Methods

This article explains two methods to obtain the current thread ID in .NET and shows which method is more performant.