David McCarter has released the 7th edition of "Rock Your Career: Surviving The Technical Interview," providing essential strategies for software engineers facing modern hiring challenges. This updated guide covers interview preparation, resume crafting, navigating recruitment processes, and salary negotiation, helping candidates increase their confidence and stand out in the job market.
The fifth edition of David McCarter's book, "Röck Yöur Cöde: Code & App Performance for Microsoft .NET," is now available on Amazon. It offers practical techniques for enhancing .NET application performance, including coding patterns, memory insights, and benchmarking. This definitive guide is essential for modern .NET developers aiming for speed and scalability.
dotNetDave will be speaking at SQL Saturday in Austin, Texas, on June 27, 2026, as part of the No Rest for the Wicked World Tour. His sessions, "Röck Yoür Cäreer" and "Unleash Your Inner Rockstar," focus on valuable career insights for tech professionals and strategies for dynamic public speaking, promising actionable guidance and inspiration.
After experimenting with the GitHub Copilot Agent during the 2026 Microsoft MVP Summit, the author faced numerous challenges, including code deletion, slow performance, and inconsistent adherence to coding conventions. Despite these issues, the agent added valuable unit tests to the Spargine projects, but it requires careful oversight and refining of prompts for effective use.
A practical look at complexity, coverage, Copilot, and keeping your code ready to rock. If you have ever attended my conference session about coding standards or read my articles on dotNetTips.com, you already know I preach about cyclomatic complexity. That number matters. To me, it represents the minimum number of unit tests a method should … Continue reading Unit Tests: Keep Your CRAP Score from Wrecking the Show
Do you trim your applications? Do you configure your reusable DLLs to be trimmable? If you build class libraries, NuGet packages, shared internal frameworks, or utility assemblies, this is something you should care about. Trimming allows the .NET linker to remove unused IL when an application is published with trimming enabled. Done correctly, it can … Continue reading Make Your .NET Assemblies Trimmable: Smaller Apps, Faster Starts, and AOT-Ready Code
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.
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.
You must be logged in to post a comment.