rippled VS QEMU

The bug occurred when a multi-path payment interacted with an AMM synthetic offer, and the synthetic offer required to fulfill the payment exceeded the AMM pool size. In this case, the payment engine attempted to use the single-path strategy to back-out the maximum liquidity available to swap against the pool. Although this condition was properly detected, there was an error on how the payment engine resized the synthetic offer to consume liquidity only up to the AMM size. Instead of using the actual swap rate, which represents the cost of fully swapping one side of an AMM pool, the new synthetic offer’s exchange rate was incorrectly set to the spot exchange rate of the AMM (that is, the rate it takes to execute an infinitesimally sized order). Consequently, an AMM operation that should have been expensive became relatively cheap, effectively violating the constant-product invariant of the pool. In this state, another user could deposit funds into the drained side of the pool, generating a large number of LP tokens and taking ownership of the pool. Now that the fix amendment is active, the team has opened a PR with a unit test demonstrating this behavior.

Explore the XRPL Developers Discord, the XRP Ledger Learning Portal, and the extensive documentation available on XRPL.org. You can also participate in XRPL Community Events and Hackathons to engage with like-minded individuals and stay abreast of the latest developments in the XRPL ecosystem.

fixDisallowIncomingV1: Fixes an issue that occurs with authorized trustlines and the “lsfDisallowIncomingTrustline” flag.

It’s good news for the builders who have been working round the clock. Tools such as AI chatbots will enable developers to quickly receive answers to their queries, speeding up the process from concept to application. AI Chatbots have already become a part of RippleX’s commitment to making blockchain development on the XRP Ledger more accessible and less time-consuming, especially for those new to the field. This approach will not only foster increased innovation on blockchains but could also enhance financial inclusion, making tools more accessible globally.

Currently Rippled 2.0.0 is scheduled to release December 18th, 2023: https://github.com/XRPLF/rippled/milestone/8

The XRPL Accelerator, a program dedicated to nurturing innovation and development on the XRP Ledger, is back with its second cohort of groundbreaking projects. After the success of the inaugural cohort, the Accelerator continues to support entrepreneurs and builders looking to scale their projects on the XRP Ledger.

The third annual Apex Developer Summit was the biggest yet. Held in collaboration with the XRP Ledger Foundation, this event brought together an impressive gathering of over 400 blockchain developers, validators, and XRPL community members in the heart of Amsterdam at the Leonardo Royal Hotel.

Explore the XRPL Developers Discord, the XRP Ledger Learning Portal, and the extensive documentation available on xrpl.org. You can also participate in XRPL Community Events and Hackathons to engage with like-minded individuals and stay abreast of the latest developments in the XRPL ecosystem.

As developers and contributors to the decentralized, open-source XRP Ledger (XRPL), the RippleX engineering team is excited to announce a major breakthrough in the XRPL ecosystem that will revolutionize the way developers build decentralized applications (dApps).

My most-wanted QEMU feature: https://github.com/qemu/qemu/commit/a2260983c6553

Using `gic-version=3` on macOS you can now use more than 8 cores on ARM chips.

A better solution is just to write a plain ass shell script that tests if various C snippets compile.

https://github.com/oilshell/oil/blob/master/configure

https://github.com/oilshell/oil/blob/master/build/detect-pwe...

Not an unholy mix of m4, shell, and C, all in the same file.

---

These are the same style as a the configure scripts that Fabrice Bellard wrote for tcc and QEMU.

They are plain ass shell scripts, because he actually understands the code he writes.

https://github.com/qemu/qemu/blob/master/configure

https://github.com/TinyCC/tinycc/blob/mob/configure

OCaml’s configure script is also “normal”.

You don’t have to copy and paste thousands of lines of GNU stuff that you don’t understand.

(copy of lobste.rs comment)

Related:

A fast Pascal (Delphi) WebAssembly interpreter:

https://github.com/marat1961/wasm

WASM-4:

https://github.com/aduros/wasm4

Curated list of awesome things regarding WebAssembly (wasm) ecosystem:

https://github.com/mbasso/awesome-wasm

Also, it would be nice if there was a WASM (soft) CPU for QEMU, which (if it existed!) would go here:

https://github.com/qemu/qemu/tree/master/target

> architectural registers are always updated

In tiny code, the guest registers (global TCG variables) are stored in the host's registers until you either call an helper which can access the CPU state or you return (`git grep la_global_sync`). This is the reason why QEMU is not so terribly slow.

But after a check, this also happens when you access the guest memory address space! https://github.com/qemu/qemu/blob/master/include/tcg/tcg-opc... (TCG_OPF_SIDE_EFFECTS is what matters)

But still, in the end, it's the same problem. What QEMU does, can be done in LLVM too. You could probably be more efficient in LLVM by using the exception handling mechanism (invoke and friends) to only serialize back to memory when there's an actual exception, at the cost of higher register pressure. More or less what we do here: https://rev.ng/downloads/bar-2019-paper.pdf

Um, in case you don't know, UTM (based on QEMU) is out for quite a while.

Some of these tools include Oracle VM VirtualBox (that I've used since before the acquisition of Sun Microsystems by Oracle), VMWare Workstation Player, and QEMU, but last year, I found out about Multipass.

For C/C++ projects that use meson as the build system, there is an excellent way to manage dependencies:

https://mesonbuild.com/Wrapdb-projects.html

https://mesonbuild.com/Wrap-dependency-system-manual.html

meson will download and build the libraries automatically and give you a variable which you pass as a regular dependency into the built target:

https://github.com/qemu/qemu/tree/005ad32358f12fe9313a4a0191...

https://github.com/harfbuzz/harfbuzz/tree/main/subprojects

https://github.com/harfbuzz/harfbuzz/blob/37457412b3212463c5...

Or, if you're using proper operating systems, they're managed by the usual package manager, just like everything else.

For all the users of the Linux platform, QEMU is the VM that you should go for. This software comes without any price tag and works as an emulator of various machines with utmost ease and completion; the software uses dynamic translations to emulate hardware peripherals and enhances its overall performance. If you are using QEMU as a virtualizer, then it will function exactly like the host system (provided you have the right set of hardware).

In this tutorial, we set up macOS and Windows virtual machines on UTM, a macOS application that provides a GUI wrapper for QEMU, a powerful open-source emulator and virtualizer. UTM allows you to easily manage and run virtual machines without memorizing complex commands. It also has special handling for macOS, making it simpler to install compared to other virtual machine software.