# plctlab/PLCT-Open-Reports

PLCT实验室的公开演讲，或者决定公开的组内报告

Repository: https://github.com/plctlab/PLCT-Open-Reports
Canonical: https://ross.abutalabs.com/products/plct-open-reports
Language: Typst
License: CC-BY-SA-4.0
License Family: other
Last push: 2025-09-03T02:19:36+00:00

## Health v2 (maintenance only)
Score: 50/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 40, release rhythm 35, longevity 100
- inputs: {"age_days": 2401, "days_push": 365, "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 1147, forks 154 (observed 2026-08-28T04:03:45.964955+00:00)

## What it is
A public archive of talks and internal reports from the PLCT Lab (Institute of Software, Chinese Academy of Sciences), covering topics like RISC-V, LLVM, eBPF, and WebAssembly. Slides are authored in Typst and PDF, with links to recorded videos on Bilibili.

## Use cases
- learn RISC-V toolchain internals from expert talks
- study LLVM backend topics like register allocation
- find slides and videos on eBPF runtimes
- research WebAssembly component model
- find RISC-V vector extension learning material
- browse compiler and systems engineering presentations

## When to choose
- you want free, expert-level slides and videos on RISC-V, LLVM, or eBPF
- you are researching compiler internals or open-source toolchain work
- you want Chinese-language systems programming talks

## When to avoid
- you need structured documentation or tutorials rather than slide decks
- you need English-only material
- you want a software tool rather than educational content

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation
- domain: tutorials, developer-tools, compilers, programming-languages
- platform: cross-platform
- tags: slides, presentations, risc-v, llvm, ebpf, compiler-internals, chinese-language, typst

## Member repositories
- plctlab/PLCT-Open-Reports (main) score 50

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:45.964955+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 2026-08-30T06:34:03.560453+00:00, confidence not recorded.
  - readme: https://github.com/plctlab/PLCT-Open-Reports (fetched 2026-08-28T04:03:45.964955+00:00, sha 7d4efd707634)
- Data as of 2026-08-30T08:39:29.467469+00:00.