# sdcuike/Clean-Code-Collection-Books

Clean Code Collection books-写代码的艺术--但是也不能死读书，照搬理论实践

Repository: https://github.com/sdcuike/Clean-Code-Collection-Books
Canonical: https://ross.abutalabs.com/products/clean-code-collection-books
License Family: other
Archived: true
Last push: 2022-03-17T15:37:01+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2689, "days_push": 1630, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, archived, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2233, forks 629 (observed 2026-08-28T04:06:29.218712+00:00)

## What it is
A curated collection of Clean Code books and related resources (SOLID diagrams, SEI CERT Java coding standards, Clean Coder blog links) for learning the art of writing clean code. It is a reference/reading list rather than executable software.

## Use cases
- find clean code books to read
- learn SOLID principles with diagrams
- study SEI CERT Java coding standards
- improve code quality and craftsmanship
- find recommended software design reading list

## When to choose
- you want a curated reading list on clean code and software craftsmanship
- you want SOLID principle visual references and Java coding standard links in one place

## When to avoid
- you need executable code, tools, or libraries
- you need actively maintained or updated resources (repo is no longer updated)
- you need a formal license for redistribution

## Facets
- artifact type: learning-resource
- maturity: abandoned
- function: documentation, developer-tools
- domain: developer-tools, tutorials, awesome-lists
- platform: cross-platform
- tags: clean-code, books-collection, solid-principles, coding-standards, chinese-language, software-craftsmanship

## Member repositories
- sdcuike/Clean-Code-Collection-Books (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:29.218712+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 2026-08-30T02:44:24.275393+00:00, confidence not recorded.
  - readme: https://github.com/sdcuike/Clean-Code-Collection-Books (fetched 2026-08-28T04:06:29.218712+00:00, sha 3e12a972a9f4)
- Data as of 2026-08-30T08:39:29.467469+00:00.