I've been working on a small project called bdockerimg.

It's a collection of pre-built Docker images for some less common development tools (currently bmakelib, QuickLisp, and SDKMAN).

The idea is to streamline setup, especially for CI/CD pipelines, where I found myself repeating the same Dockerfile steps a lot. Basic functionality tests are included for a bit of extra peace of mind.

👀 Here's the repo if you're interested: https://github.com/bahmanm/bdockerimg
🗣 And here's the the Matrix room: https://matrix.to/#/#bdockerimg:matrix.org

I'm curious:

• Does this seem like something you might find useful?
• Are there any specific tools you'd love to see as easy-to-use Docker images?

This project is still in its early stages, so any feedback or contributions are much appreciated 🙏

Release 14.2 of GDB, the GNU Debugger, is now available. GDB is a source-level debugger for Ada, C, C++, Fortran, Go, Rust, and many other languages. GDB can target (i.e., debug programs running on) more than a dozen different processor architectures, and GDB itself can run on most popular GNU/Linux, Unix and Microsoft Windows variants. GDB is free (libre) software.

GDB 14.2 brings the following fixes and enhancements over GDB 14.1:

• PR symtab/31112 (DLL export forwarding is broken)
• PR c++/31128 (gdb crashes when trying to print a global variable stub without a running inferior)
• PR tdep/31254 ([gdb/tdep, arm] FAIL: gdb.threads/staticthreads.exp: up 10)
• PR gdb/31256 (Crash with basic 'list .')
• PR python/31366 (Frame.static_link() segfaults)

Vulkan 1.3.279 debuted on Friday with many fixes/clarifications to the specifications plus one new extension. The VK_NV_raw_access_chains extemsion should allow for more efficient shaders compiled from HLSL sources.

Extensions available in RISC-V enable the customizations that make it ideal as a basis for open innovation. Here’s the extension situation as it stands today.

This tutorial will teach you how to use the OpenXR API. OpenXR is an API managed by the Khronos Group which provides a cross-platform way for applications to interact with immersive devices. This includes virtual reality (VR) headsets, augmented reality (AR) devices, motion controllers and more.

Eight years after launching the Vulkan database to the public, it’s approaching 30,000 uploaded reports from more than 3,300 different devices across Windows, Linux, Android, MacOS and iOS. With that much data available, good filtering capabilities are crucial.

We are excited to announce that with the latest release of Steam Audio, the complete source code of the Steam Audio SDK is now available as open source. With this release, our goal is to provide more control to developers, which will lead to better experiences for their users, and hopefully valuable contributions back to the wider community of developers using Steam Audio.

I'm planning on creating an AI tournament as a project to test out some of the potential AI performance in a game, eg tic-tac-toe.

I'd like the AI to know the full history of a game instead of the instantaneous game-state because I might want some AI that use the historical data, eg AI that always put in the opposite cell of it's previous move if possible.

The question I am wondering is, what is the best way to setup the tournament.

I have a few options in my headspace:

1. Write everything in Rust (since I also am semi-interested in getting experience with the language)
2. Write everything in Python
3. Write the AI's in anything I want, but interact using stdin/stdout. Connect the AI using some shell script.

There are a few nice things I want to have:

1. able to run AI ad hoc against each other, or easily modify the tourney. ie I might want to add a new AI that runs against each of the previous AI instead of having the re-run the whole tourney
   • Rust would require a re-compile of the tourney code each time which may not be convenient
   • Options 2 and 3 would be much more convenient since it wouldn't require a full compilation and I can easily write a throwaway script
2. be able to run it in a somewhat performant way since I might want to simulate many rounds
   • Rust AI would be fast, but to avoid the issue in (1), I might go with solution 3 with the underlying AI being in Rust. But I'm not sure how significant the speed of piping IO between programs compare to if I had wrote everything as a Python program

Any advice on this would be great, cause there might be some options that I might have omitted.

With this step, we are opening Qt SVG up to support elements beyond SVG Tiny 1.2. This means that we will aim to include useful and common elements from SVG 1.1 and SVG 2.0, if maintenance is reasonably feasible. We will not aim for compliance with these standards but we will keep an eye on feature requests from our users. Further, we are open to contributions of such extensions by the community. So if you miss your favorite SVG element in the list above, fell free to send us some code, preferably on our code review platform.