# ming1016/study

学习记录

Repository: https://github.com/ming1016/study
Canonical: https://ross.abutalabs.com/products/study
Language: C
License Family: other
Last push: 2026-02-23T14:50:24+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": 4206, "days_push": 191, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3905, forks 766 (observed 2026-08-28T04:08:28.691349+00:00)

## What it is
A personal study repository by Dai Ming containing extensive wiki articles and notes on iOS/Swift development, compilers (LLVM/Clang, JavaScriptCore, WebKit), performance optimization, and programming practices. It serves as a curated learning resource rather than a shippable software product.

## Use cases
- learn iOS performance optimization techniques
- understand how LLVM and Clang compilation works
- study Swift language features like generics and concurrency
- learn how JavaScriptCore and WebKit engines work internally
- find notes on iOS app launch time optimization
- learn SwiftUI and Combine development patterns

## When to choose
- you want in-depth Chinese-language articles on iOS internals and Swift
- you are studying compiler internals like LLVM, Clang, or JavaScript engines
- you want curated notes from an experienced iOS practitioner

## When to avoid
- you need production-ready, maintained software or a library
- you expect a license permitting code reuse
- you need English-language documentation

## Facets
- artifact type: learning-resource
- maturity: active
- function: developer-tools, documentation
- domain: tutorials, developer-tools, mobile-development, programming-languages
- platform: -
- tags: study-notes, swift, ios-development, wiki, blog, deep-dives, compilers, performance-optimization, ios, macos

## Member repositories
- ming1016/study (main) score 63

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:28.691349+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 2026-08-29T18:25:07.703408+00:00, confidence not recorded.
  - readme: https://github.com/ming1016/study (fetched 2026-08-28T04:08:28.691349+00:00, sha 30e4e0493ff5)
- Data as of 2026-08-30T08:39:29.467469+00:00.