Could the effort be bootstrapped by using a C to Rust translator, like https://github.com/immunant/c2rust, preserving the existing semantics prior to updating the code to remove the "unsafe" tags.
369 karma · joined March 2, 2012
Regardless of the programming task, it is usually hard to find the best way to do it, and not trivial to implement it correctly. This is demonstrated by the fact that most code sucks.
Also, not using stl and boost because it is too slow? In my experience people who make this argument often use significantly worse implementations with serious shortcomings.
Tell that to these guys: https://www.youtube.com/watch?v=v1apqfrJYwk. I think one day we have have two wheeled robots with these kind of capability.
Beyond the classic spatial search data structures, the fastest solutions all used SSE instructions (see https://github.com/sDessens/churchill-challange for nice writeup). People did try pretty hard to win the grand prize of $5000, and the fastest solution was 7 times faster than the best optimized code that Churchill's team had previously.
Frankly, I can't help being disappointed by how bland this language is, and I have zero interest in using it. Maybe because I like coding, and the IMHO using Go or Java would totally kill the fun of it.
One remark. In the unordered_set case, it would be faster to assign rather than inserting the first set, because with insert() we loose the fact that the elements in A are already unique and out will not be resized appropriately.
out = A; out.insert(B.begin(), B.end());
"Most developers access Piper through a system called Clients in the Cloud, or CitC, which consists of a cloud-based storage backend and a Linux-only FUSE13 file system. Developers see their workspaces as directories in the file system, including their changes overlaid on top of the full Piper repository. CitC supports code browsing and normal Unix tools with no need to clone or sync state locally. Developers can browse and edit files anywhere across the Piper repository, and only modified files are stored in their workspace. This structure means CitC workspaces typically consume only a small amount of storage (an average workspace has fewer than 10 files) while presenting a seamless view of the entire Piper codebase to the developer."
This is a very powerful model when dealing with large code bases, as it solves the issue of downloading all the code to each client. Kudos to Microsoft for open sourcing it, and under the MIT license no less.