We didn’t get similar run times with Haskell.

Rust let us abstract even file types (path to a fastq file, fasta file, annotations, etc) with no run time costs. This eliminate many bugs at compile time.

You may say that we can get it in C too, and you will be correct. But in C we spend our time on herding pointers. Research is given X money for N months (sort of), so we have time constraints on development time.

If we do bit wise work, the compiler tests our base types.

Not to mention multithreading just works. Even big projects like BLAST had bugs that led to wrong results due C/CPP horrible multithreading. We encountered two more tools that had similar bugs.

I think that if someone ever does a meta-studies of research code written in C it may get papers retracted.

After fixing, now that you are expert, please migrate the regex to our new language.

It is easier to safely optimize Rust than C, but that was not the point. The point was on correctness of code.

It is not unheard of for code to run for weeks and months. I need the code to be as bug free as possible. For example, when converting one of our tools to Rust we found out a bug that will lead to the wrong results on big samples. It was found by the Rust compiler! Our tests didn’t cover the bug because it will only happen on very big sample. We can’t create a test file of hundreds of GB by hand and calculate the expected result. Our real data would have triggered the bug. So without moving to Rust we would have gotten the wrong results.

I used Gentoo in ancient time when kernel updates took a whole day. A modern computer can rebuild in an hour, a good one, even faster. I’m not a kernel developer, but I don’t think they need to rebuild the whole kernel for every iteration.

And as for Rust, I’m doing bioinformatics in Rust because our iteration time is order of magnitudes longer than a kernel build, and Rust reduced the number of iterations required to reach the final version.

The real world case I remember also included a TODO to return and fix the code later. In a published scientific software. I wonder how many paper were messed up by this buggy software. As I looked at the code due to the amount of bugs I encountered.

It’s been many years from publication, and to the surprise of no one, they did not return to fix it.

// This line does nothing, however removing it causes production to crash. DO NOT REMOVE

The newly freed 40+GB are a nice bonus.

Now run a VM from Google Cloud on a system booted from Google Cloud.

Bioinformatics isn’t used only for medical research or within big companies. Sub-topics like metagenomics, that are helpful in many areas of research, require high level of technical knowledge, that the life science people don’t have.

You can work in bioinformatics, the pay is lower than FAANG, but your code will benefit society.

In addition to other comments,read about Ada Lovelace. She was brilliant, she wrote the first program, and done so before we had computers!

DNA free

Function

I don’t own a yoga mat