Hacker News - Newest: "C++"

Borland C++ 2.0 Compiler Source Reconstructed

fork-bomber — Sat, 14 Nov 2026 06:09:32 +0000

Article URL: https://hackaday.com/2026/11/13/borland-c-2-0-compiler-source-reconstructed/

Comments URL: https://news.ycombinator.com/item?id=50494481

Points: 5

# Comments: 1

C++26 stumbles at finish line over Contracts dispute

titusblair — Fri, 13 Nov 2026 18:48:49 +0000

Article URL: https://www.theregister.com/devops/2026/11/13/c26-stumbles-at-finish-line-over-contracts-dispute/5309526

Comments URL: https://news.ycombinator.com/item?id=50487969

Points: 1

# Comments: 0

Show HN: Ultra-Low Latency C++23 HFT Engine and Lock-Free Ring Buffers

snowdensay — Fri, 13 Nov 2026 08:16:36 +0000

Article URL: https://github.com/grfdsasdvef/awesome-hft-cpp23-internals

Comments URL: https://news.ycombinator.com/item?id=50480053

Points: 2

# Comments: 0

For the first time, a C++ standard failed to pass the national bodies

birdculture — Thu, 12 Nov 2026 22:36:16 +0000

Article URL: https://herecomesthemoon.net/2026/11/cpp26-failed-the-national-bodies/

Comments URL: https://news.ycombinator.com/item?id=50475379

Points: 4

# Comments: 0

Visual Studio C++ Dynamic Debugging is now generally available

pjmlp — Thu, 12 Nov 2026 18:15:28 +0000

Article URL: https://devblogs.microsoft.com/cppblog/c-dynamic-debugging-is-now-generally-available/

Comments URL: https://news.ycombinator.com/item?id=50471645

Points: 1

# Comments: 0

The difference between undefined behavior and ill-formed C++ programs

ibobev — Thu, 12 Nov 2026 13:50:05 +0000

Article URL: https://devblogs.microsoft.com/oldnewthing/20240802-00/?p=110091/

Comments URL: https://news.ycombinator.com/item?id=50467062

Points: 3

# Comments: 0

For the first time, a C++ standard failed to pass the national bodies

speckx — Wed, 11 Nov 2026 19:30:54 +0000

Article URL: https://herecomesthemoon.net/2026/11/cpp26-failed-the-national-bodies/

Comments URL: https://news.ycombinator.com/item?id=50457429

Points: 5

# Comments: 1

ILrDOS – header-only C++20 robot runtime for a Pi Zero 2 W

v0rtexlinux32 — Wed, 11 Nov 2026 17:38:55 +0000

Article URL: https://github.com/V0rtexLinux/ILrDOS

Comments URL: https://news.ycombinator.com/item?id=50456112

Points: 2

# Comments: 0

MSVC C++23: constexpr cmath with LLVM Libc

travelmalta — Wed, 11 Nov 2026 16:24:55 +0000

Article URL: https://devblogs.microsoft.com/cppblog/msvc-c23-constexpr-cmath-with-llvm-libc/

Comments URL: https://news.ycombinator.com/item?id=50455216

Points: 1

# Comments: 0

Show HN: Godbolt-in-a-floating-window for Neovim (C, C++, Rust)

0xdeadf1sh — Wed, 11 Nov 2026 13:34:24 +0000

No internet connection needed. Uses a locally-installed compiler for assembly generation.

Comments URL: https://news.ycombinator.com/item?id=50453229

Points: 104

# Comments: 20

Show HN: blqsort – A C++ Quicksort Faster Than std:sort

chrka — Wed, 11 Nov 2026 13:31:12 +0000

Article URL: https://tiki.li/blog/about_blqsort

Comments URL: https://news.ycombinator.com/item?id=50453189

Points: 2

# Comments: 0

Show HN: I checked 10 AI-written patches to real C++ projects – 6 didn't hold up

u-pump — Wed, 11 Nov 2026 13:14:12 +0000

Article URL: https://unfix.dev/

Comments URL: https://news.ycombinator.com/item?id=50453025

Points: 2

# Comments: 0

Powerful New Embedded C++ Scripting Language

Devacor — Wed, 11 Nov 2026 01:15:30 +0000

Article URL: https://jaiscript.com/

Comments URL: https://news.ycombinator.com/item?id=50448629

Points: 1

# Comments: 1

Build-Aware Context and a Checking Harness for C++ Coding Agents

anirudhak — Wed, 11 Nov 2026 01:08:20 +0000

Article URL: https://byteask.ai/research/byteask-system-cpp

Comments URL: https://news.ycombinator.com/item?id=50448569

Points: 1

# Comments: 0

Show HN: Usul – Express neural networks as raw math in C++23

ronny2fresh — Tue, 10 Nov 2026 13:43:38 +0000

SO, Usul-cpp is a library I've written in C++, it is based around allowing data scientists to create their models without heavy libraries such as tensorflow, and just express their models using maths, and Usul will handle the rest. There is builtin tensor support, auto-grad, back-prop and its quite fast.

I wrote it because, it seemed less mystifying to read maths instead of a random class that supposedly does something. I wrote it from scratch in cpp (23) due to the fact that I wanted to emphasise on precision, however it's subtly built on top of xtensor.

check it out in action #include using namespace std;

  int main() {
    double LR = 0.1;
    int EPOCH = 5000;
    // lets write the forward pass
    Tensor X = {
        {0.0, 0.0}, // this is what we're feeding it
        {0.0, 1.0},
        {1.0, 0.0},
        {1.0, 1.0},
    };

    // this is what we're after
    Tensor Y_true = {
        0.0, // xor{0.0, 0.0} = 0.0
        1.0, // xor{0.0, 1.0} = 1.0
        1.0, // xor{1.0, 0.0} = 1.0
        0.0  // xor{1.0, 1.0} = 0.0
    };

    Y_true.reshape({4, 1});

    // we are now going to create a single layer, double neuron network
    // each layer will have a bias and weights tensor.
    auto W1 = generate_random_matrix({2, 4}, -1.0, 1.0);
    auto B1 = generate_random_matrix({1, 4}, -1.0, 1.0);
    auto W2 = generate_random_matrix({4, 1}, -1.0, 1.0);
    auto B2 = generate_random_matrix({1, 1}, -1.0, 1.0);

    // this is the training loop
    for (int i = 0; i < EPOCH; i++) {
      // so lets do one forward pass
      // first layer
      auto Z1 = X % W1 + B1;
      auto A = Z1.ReLU();
      // second layer
      auto Z2 = A % W2 + B2;

      // activation
      // should be - auto S = Z2.activate(Activate::Sigmoid);
      auto S = Z2.Sigmoid();
      // Loss
      // should be - auto Loss = S.loss(Loss::MSE);

      auto loss = (S - Y_true) * (S - Y_true);
      loss = loss.mean();

      cout << "Loss: " << loss << "\n";
      cout << "guesses: " << "\n"
           << S << "\n";
      cout << "should be: " << Y_true << "\n";

      loss.backwards();

      W1.step(LR);
      B1.step(LR);
      W2.step(LR);
      B2.step(LR);
    }
  }

which will output

  Guesses: 
  Tensor({{ 0.027546},
   { 0.963592},
   { 0.964138},
   { 0.038964}}, shape=(4,1))

  should be: Tensor({{ 0.},
   { 1.},
   { 1.},
   { 0.}}, shape=(4,1))

  Loss: Tensor( 0.001222, shape=())

Just write the maths, and Usul-cpp will handle the rest, it is extremely lightweight, and the entire library is memory safe. And its called Usul, because I'm a huge dune fan.

You can view the project at [https://github.com/crushr3sist/Usul-cpp](https://github.com/crushr3sist/Usul-cpp)

Any ideas for what to do next are all welcome, you can also pull and implement features that you think could improve this project. (no vibecoded prs please, this project is not vibe-coded)

Comments URL: https://news.ycombinator.com/item?id=50440232

Points: 2

# Comments: 1