# Maoni0/mem-doc

This is a document to help with .NET memory analysis and diagnostics.

Repository: https://github.com/Maoni0/mem-doc
Canonical: https://ross.abutalabs.com/products/mem-doc
License Family: other
Last push: 2024-02-18T21:06:03+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2187, "days_push": 927, "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 1960, forks 160 (observed 2026-08-28T04:05:59.354136+00:00)

## What it is
A comprehensive guide document for .NET memory performance analysis and GC heap diagnostics, written by a former .NET GC developer. It also includes slide decks and video links from related conference talks.

## Use cases
- diagnose memory leaks in .NET applications
- learn how the .NET garbage collector works
- analyze GC heap performance issues
- find the right tools for .NET memory profiling
- understand when to worry about memory usage in .NET
- learn .NET GC internals from expert talks

## When to choose
- you are debugging memory leaks or high memory usage in a .NET app
- you want expert-level guidance on .NET GC behavior and diagnostics tooling
- you need a structured learning path for .NET memory performance analysis

## When to avoid
- you need a runnable tool or library rather than documentation
- you are profiling memory in non-.NET runtimes like JVM or native C++
- you want automated memory analysis rather than manual guidance

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, monitoring, developer-tools
- domain: developer-tools, performance, tutorials
- platform: dotnet, cross-platform
- tags: dotnet, garbage-collector, memory-analysis, diagnostics, performance-tuning

## Member repositories
- Maoni0/mem-doc (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:59.354136+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 2026-08-30T03:05:43.881175+00:00, confidence not recorded.
  - readme: https://github.com/Maoni0/mem-doc (fetched 2026-08-28T04:05:59.354136+00:00, sha a1dcd0675e62)
- Data as of 2026-08-30T08:39:29.467469+00:00.