.Net Code Review: Best Practices and AI Tools (2026)
The article discusses the importance of an effective .NET code review process that goes beyond mere quality control. It highlights the challenges faced by teams, such as divided attention and bottlenecks in the review process. The use of AI tools is suggested to automate routine tasks, allowing engineers to focus on architectural considerations.
- ▪A good .NET code review process should facilitate knowledge transfer and maintain architectural coherence.
- ▪AI tools can help automate style guide violations and bug detection, freeing engineers to concentrate on architecture.
- ▪Reviewing .NET code requires understanding the interaction between code and the runtime, as well as the impact on performance and security.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 907253) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Edvaldo Freitas for Kodus Posted on May 26 • Originally published at kodus.io .Net Code Review: Best Practices and AI Tools (2026) #dotnet #codereview #devex A good .NET code review process should do more than just quality control. It can be a way to transfer knowledge, reduce risk, and keep the architecture coherent. For many teams, though, it is just a bottleneck.
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