# EarsEyesMouth/computerese-cross-references

计算机专业术语中英文对照。

Repository: https://github.com/EarsEyesMouth/computerese-cross-references
Canonical: https://ross.abutalabs.com/products/computerese-cross-references
License: MIT
License Family: permissive
Last push: 2024-11-13T07:54:50+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3750, "days_push": 658, "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 1029, forks 191 (observed 2026-08-28T04:03:17.671816+00:00)

## What it is
A curated glossary of computer science and software engineering terminology with English-to-Chinese translations, organized alphabetically. It serves as a reference for developers and students needing accurate Chinese equivalents for technical terms.

## Use cases
- look up the Chinese translation of a computer science term
- translate software engineering jargon to Chinese
- study computer terminology in English and Chinese
- find standard Chinese names for design pattern terms
- reference glossary for reading English technical docs

## When to choose
- you need authoritative English-Chinese mappings for computing terms
- you are a Chinese-speaking developer reading English documentation
- you want a simple alphabetical terminology reference

## When to avoid
- you need translations for non-Chinese languages
- you need in-depth definitions or explanations rather than term mappings
- you need machine-translated or exhaustive coverage of niche terms

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, internationalization
- domain: developer-tools, tutorials
- platform: cross-platform
- tags: glossary, english-chinese, computer-terminology, reference, localization

## Member repositories
- EarsEyesMouth/computerese-cross-references (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:17.671816+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 2026-08-30T07:07:37.205896+00:00, confidence not recorded.
  - readme: https://github.com/EarsEyesMouth/computerese-cross-references (fetched 2026-08-28T04:03:17.671816+00:00, sha 1af149d9808d)
- Data as of 2026-08-30T08:39:29.467469+00:00.