# fenixsoft/jvm_book

《深入理解Java虚拟机（第3版）》样例代码&勘误

Repository: https://github.com/fenixsoft/jvm_book
Canonical: https://ross.abutalabs.com/products/jvm_book
Language: Java
License Family: other
Topics: jvm, book
Last push: 2022-05-15T02:39:42+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": 2458, "days_push": 1571, "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 1402, forks 226 (observed 2026-08-28T04:04:37.362440+00:00)

## What it is
A companion repository for the Chinese book 'Understanding the JVM (3rd Edition)' containing sample code from the book plus a continuously updated errata list. The code demonstrates JVM internals such as class loading, memory management, and garbage collection, with required VM arguments annotated per example.

## Use cases
- run sample code from the Understanding the JVM book
- learn how the Java virtual machine works internally
- check errata for the 3rd edition of the JVM book
- experiment with JVM memory and GC behavior
- study class loading and bytecode examples
- report or track book corrections via issues

## When to choose
- you are reading the book and want runnable examples
- you want to reproduce JVM demonstrations like OOM or GC scenarios
- you need the latest errata for the 3rd edition

## When to avoid
- you need a general-purpose JVM library or tool
- you want an English-language JVM tutorial
- you need production-ready code rather than book demos

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: developer-tools, interpreter
- domain: programming-languages, tutorials, education
- platform: jvm, cross-platform
- tags: jvm, book, sample-code, errata, java-virtual-machine, deep-dive-java

## Member repositories
- fenixsoft/jvm_book (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:37.362440+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 2026-08-30T04:38:58.670382+00:00, confidence not recorded.
  - readme: https://github.com/fenixsoft/jvm_book (fetched 2026-08-28T04:04:37.362440+00:00, sha a88d967d702e)
- Data as of 2026-08-30T08:39:29.467469+00:00.