# bytedance/memory-leak-detector

Repository: https://github.com/bytedance/memory-leak-detector
Canonical: https://ross.abutalabs.com/products/memory-leak-detector
Language: C
License: NOASSERTION
License Family: other
Last push: 2025-02-07T07:01:02+00:00

## Health v2 (maintenance only)
Score: 25/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 5, release rhythm 8, longevity 100
- inputs: {"age_days": 1967, "days_push": 572, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1192, forks 190 (observed 2026-08-28T04:03:56.411263+00:00)

## What it is
MemoryLeakDetector (Raphael) is a native memory leak monitoring library for Android apps, developed by ByteDance's Xigua video team. It hooks native allocations to track leaks, with simple integration, low overhead, and a Python tool for analyzing reports.

## Use cases
- detect native memory leaks in android app
- monitor malloc leaks in native so libraries
- debug memory growth in android production
- analyze memory leak reports with symbols
- track native memory usage per process

## When to choose
- you maintain an Android app with native (C/C++) components leaking memory
- you need low-overhead leak monitoring usable in production
- you want adb broadcast control to toggle monitoring remotely

## When to avoid
- you need Java/Kotlin heap leak detection (use LeakCanary instead)
- your project is not Android
- you need iOS or desktop native memory profiling

## Facets
- artifact type: library
- maturity: active
- function: monitoring, developer-tools
- domain: mobile-development, developer-tools, performance
- platform: cli
- tags: memory-leak-detection, native-memory, android-debugging, profiling, android, mobile

## Member repositories
- bytedance/memory-leak-detector (main) score 25

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:56.411263+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 2026-08-30T06:22:28.535606+00:00, confidence not recorded.
  - readme: https://github.com/bytedance/memory-leak-detector (fetched 2026-08-28T04:03:56.411263+00:00, sha 729a111c9bab)
- Data as of 2026-08-30T08:39:29.467469+00:00.