I implemented Smart Pointers from scratch in C++ (UniquePtr, SharedPtr & WeakPtr)
I’ve been trying to spend more time building things from scratch instead of just reading about them.
My latest project was implementing UniquePtr, SharedPtr, and WeakPtr in C++ with reference counting.
It ended up being much more interesting than I expected. Small mistakes in reference counting quickly turned into bugs like memory leaks, double-free, and use-after-free, which made me appreciate the standard library implementation even more.
Current status:
UniquePtr
SharedPtr
WeakPtr
Reference counting
18/18 test cases passing
Repository:
https://github.com/574-jayeshSh/smart-pointer-library
I’d love to hear feedback from people who’ve implemented something similar or suggestions on what I should improve next.
https://redd.it/1v3m5k5
@r_cpp
I’ve been trying to spend more time building things from scratch instead of just reading about them.
My latest project was implementing UniquePtr, SharedPtr, and WeakPtr in C++ with reference counting.
It ended up being much more interesting than I expected. Small mistakes in reference counting quickly turned into bugs like memory leaks, double-free, and use-after-free, which made me appreciate the standard library implementation even more.
Current status:
UniquePtr
SharedPtr
WeakPtr
Reference counting
18/18 test cases passing
Repository:
https://github.com/574-jayeshSh/smart-pointer-library
I’d love to hear feedback from people who’ve implemented something similar or suggestions on what I should improve next.
https://redd.it/1v3m5k5
@r_cpp
GitHub
GitHub - 574-jayeshSh/smart-pointer-library
Contribute to 574-jayeshSh/smart-pointer-library development by creating an account on GitHub.
Pure Virtual C++ Videos Are Now Available
https://devblogs.microsoft.com/cppblog/pure-virtual-c-2026-is-a-wrap/
https://redd.it/1v3myfh
@r_cpp
https://devblogs.microsoft.com/cppblog/pure-virtual-c-2026-is-a-wrap/
https://redd.it/1v3myfh
@r_cpp
Microsoft News
Pure Virtual C++ 2026 Is a Wrap
Pure Virtual C++ 2026 is a wrap. Every featured and on-demand session is now available on YouTube — catch up on C++/Rust interop, AI-driven tooling, build performance, and more.
Project A backend-agnostic C++17 document intelligence pipeline with measurable OCR, layout and table stages
I have been working on an early-stage open-source document intelligence engine in C++17.
The goal is not to own every OCR or layout model. The core keeps typed pipeline boundaries and normalizes PDF text, OCR, layout blocks, tables, reading order, coordinates, confidence and provenance into a stable document model.
Current components include:
\- PDFium rendering and native text
\- PaddleOCR ONNX and optional Tesseract
\- RF-DETR DocLayNet and Paddle PP-DocLayoutV3
\- Table Transformer detection and structure recognition
\- JSON/Markdown/HTML output
\- small public regression datasets
\- an optional FastAPI/Redis Streams/persistent C++ Worker/React inspection platform
It is still an alpha. The current small benchmark subsets are regression checks, not production accuracy claims.
I am looking for contributors interested in C++ architecture, ONNX session reuse, OCR/CV evaluation, Redis Streams recovery, reading order, or Web-based bounding-box diagnostics.
Repository:
https://github.com/ChNanAn/technical-doc-parser
https://redd.it/1v41u7b
@r_cpp
I have been working on an early-stage open-source document intelligence engine in C++17.
The goal is not to own every OCR or layout model. The core keeps typed pipeline boundaries and normalizes PDF text, OCR, layout blocks, tables, reading order, coordinates, confidence and provenance into a stable document model.
Current components include:
\- PDFium rendering and native text
\- PaddleOCR ONNX and optional Tesseract
\- RF-DETR DocLayNet and Paddle PP-DocLayoutV3
\- Table Transformer detection and structure recognition
\- JSON/Markdown/HTML output
\- small public regression datasets
\- an optional FastAPI/Redis Streams/persistent C++ Worker/React inspection platform
It is still an alpha. The current small benchmark subsets are regression checks, not production accuracy claims.
I am looking for contributors interested in C++ architecture, ONNX session reuse, OCR/CV evaluation, Redis Streams recovery, reading order, or Web-based bounding-box diagnostics.
Repository:
https://github.com/ChNanAn/technical-doc-parser
https://redd.it/1v41u7b
@r_cpp
GitHub
GitHub - ChNanAn/technical-doc-parser: C++ native, backend-agnostic document intelligence engine for traceable structured document…
C++ native, backend-agnostic document intelligence engine for traceable structured document parsing. - ChNanAn/technical-doc-parser