# thangchung/clean-code-dotnet

:bathtub:  Clean Code concepts and tools adapted for .NET

Repository: https://github.com/thangchung/clean-code-dotnet
Canonical: https://ross.abutalabs.com/products/clean-code-dotnet
Language: C#
License: MIT
License Family: permissive
Topics: awesome, aspnet, azure, csharp, dotnet, clean-code, best-practices, principles, composition, inheritance, clean-architecture, solid
Last push: 2026-02-27T03:58:00+00:00

## Health v2 (maintenance only)
Score: 63/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 69, release rhythm 35, longevity 100
- inputs: {"age_days": 3278, "days_push": 187, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 7725, forks 1139 (observed 2026-08-28T04:10:02.613657+00:00)

## What it is
A curated guide adapting Robert C. Martin's Clean Code principles to .NET and .NET Core, with C# examples for naming, functions, classes, SOLID, testing, and error handling. It is an educational reference list inspired by clean-code-javascript and clean-code-php.

## Use cases
- learn clean code principles in C#
- improve readability of .NET codebase
- SOLID principles examples for dotnet
- onboarding guide for .NET developers
- refactoring guidelines for C# projects

## When to choose
- you write C#/.NET and want actionable clean-code examples
- you need a reference for code reviews or team coding standards

## When to avoid
- you need a linting or enforcement tool rather than guidelines
- you work outside the .NET ecosystem

## Facets
- artifact type: learning-resource
- maturity: active
- function: developer-tools, documentation
- domain: developer-tools, tutorials, programming-languages
- platform: dotnet, cross-platform
- tags: clean-code, best-practices, solid, csharp, awesome-list, code-quality

## Member repositories
- thangchung/clean-code-dotnet (main) score 63

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:02.613657+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:35:15.167908+00:00, confidence not recorded.
  - readme: https://github.com/thangchung/clean-code-dotnet (fetched 2026-08-28T04:10:02.613657+00:00, sha 73ffbadb1835)
- Data as of 2026-08-30T08:39:29.467469+00:00.