van2z

Let me start by noticing, I am not interested in playing a game of Tic Tac Toe, nor programming any form of "AI". With that out of the way, let me give some background:

I have found Rust, with its ownership model, frequently nudges me to rethink whatever I am building. Usually it involves fixing some structs / enums, to avoid references. Correctly structuring an object can make me avoid lots of headaches later when I actually add functionality.

One thing I noticed that helps is understanding what kind of properties should the data have? Should it maintain a certain order, or can it be unordered? Are all of the values unique, or can it have duplicates? All of these details are very important. It is wrong to just shove everything into a Vec. A Vec implies ordering and duplicates, which could be a bad model. We need to choose something which most closely represents the data.

Ok, enough lecture. Onto the Tic Tac Toe grid. Observing this grid provides me with a few important properties:

A Tic Tac Toe grid can be rotated clockwise or counterclockwise, and the game is still the same. The grid can also be flipped over horizontally or vertically and the game will be the same. To decide if anyone won, we just need to see if any rows have 3 of the same value. The rest of the grid does not matter.

I am trying to figure out the best memory model would best represent this behavior. How to build a grid whose orientation does not matter?

Ideally, all of these values should be represented in memory exactly the same way:

  X|O|   X| |    | |
   |O| = O|O| = O|O|
   | |    | |   X| |

But how to do this? One way I was thinking, is perhaps instead of saving a grid at all, we should just be keeping track of all of the rows.

• [X, O, E] (E = Empty)
• [O, O, E]
• etc for all the other rows..

However there are several problems with this model:

1. The same cells are owned by multiple rows. This is not good. Perhaps the rows can hold a reference to the cells?
2. The ordering of each row should not matter. So this shouldn't be an array. A better representation may be a Set or Bag/Multiset.

#1 continues to bug me. If we have rows holding references to all of the cells, then it will be hard to update any of them because of rust's restrictions on multiple mutable borrows. Or am I wrong here? How can I update a cell using a reference from a row? Where would the cell live anyway?

It doesn't seem to help to declare the rows inside of the cells, because that leads to cyclical references.

I continue to mull over this problem with not much success. I hope someone can help me discover a better path forward.

For some reason, it seems popular for GUI crates to use the GPU. I just want to make simple widgets, for like a calculator.

No fancy graphics. I want it quite lightweight.

For some reason, popular GUI crates love to do everything through a GPU, which bumps up the memory / cpu use significantly.

I just attempted to write up a simple Minesweeper game with Iced. No bells or whistles, but it works:

https://github.com/veniamin-ilmer/minesweeper

On one hand, I find it pretty cool I built a clear cross platform GUI with actual functionality, within only 200 lines of code.

On the other hand, I can't help but see how inefficient it seems. If I ever need to modify any of the objects, I need to redraw all of them. The structure of the view method makes me think it is very difficult for Iced to maintain a "virtual DOM" to only make delta changes.

Am I wrong? Is there a more efficient way to do this in Iced?

Edit: I just found this - https://github.com/iced-rs/iced/pull/1284

As the library matures, the need for some kind of persistent widget data (see #553) between view calls becomes more apparent (e.g. incremental rendering, animations, accessibility, etc.).

If we are going to end up having persistent widget data anyways... There is no reason to have impure, stateful widgets anymore!

So it seems like Iced plans to have an internal "persistent widget storage", which in abstracted away from the user. But it is quite unclear to me how they would accomplish this, considering the view method doesn't provide an ID for any of its objects, so it would not be easy for Iced to determine the difference between updates.

cross-posted from: https://programming.dev/post/864349

I have spent some time trying to simplify the release process. For a variety of reasons, we can only release on Thursdays. The code is "frozen" on Tuesday before it can be released on Thursday. But we sometimes squeeze in a quick fix on Wednesday as well.

The question, is when should QA test the code?

Here is what I have seen happen:

1. Dev writes code and sends it to QA.
2. QA finds problems, sends it back to the Dev.
3. Dev fixes and sends it back to QA.

I have seen a Dev fix their code on Tuesday, and then QA comes back on Wednesday with problems, when the code should have been frozen anyway.

I am looking, what should be the best solution here.

We have several problems going on at once:

1. Developers test on the same server as QA tests. I am working to switch developers to a separate Dev server, but it is a long work in progress.
2. We don't have an easy way to revert code back from the QA server. It is easier to build revisions than revert changes. We can try to revert code more, but it will require a culture change.
3. QA don't really have a schedule when they are supposed to do functional testing vs regression testing.

I don't know what is the best way to proceed forward. Thus far, I haven't thought too much about the QA because I was focused more on getting releases out. Now that releasing is more simplified, that we can potentially do weekly releases, I am trying to see how we should proceed with the testing process.

I recently decided to think of an algorithm based on natural selection of DNA mutations. Being unclear about its speed complexity, I decided to write it up and test it out. The result was counter intuitive.

First, a simpler variant: Imagine the following sorting algorithm, given an array of numbers: Randomly shuffle the numbers until they are sorted.

What is the median amount of times you end up shuffling the array before it is sorted?

The answer is n! where n is length of the array. This is known as Bogosort.

Now, a slightly more advanced version:

Assume you can tell which numbers are already in their correctly sorted position, and which aren't. Only randomly shuffle the numbers which are not yet sorted. Keep all the others in place.

What is the median amount of times you end up doing this kind of shuffling before the whole array is sorted?

I'll be revealing the answer tomorrow.

Edit: The answer is that you end up shuffling only n times.

Addressing some concerns: this is not a real sorting algorithm, because it assumes you already know whether some of the records are sorted or not.

It shows me how "random chance" in DNA mutations can actually occur much faster than we expect. When a better gene allows an organism to survive better, it sticks around, while all of the other useless genes randomly shuffle around until they can become more useful too. This way organisms with a long DNA code can still evolve rather quickly even if it's by random chance.

Not only will a bidet save you on toilet paper, but you will actually feel like you have a clean butt after pooping. Initially it feels weird, but after you get used to it, you won't want to poop without it.

BTW in case you are wondering: yes, you still need toilet paper to wipe the water off. But it is a small amount.

There are tons of Rust communities spread on multiple instances. Is the expectation that users interested in rust should just subscribe to all of these? Is there a community which aggregates posts from all rust communities together into one?

I have been working at a large bank for a few years. Although some coding is needed, the bulk majority of time is spent on server config changes, releasing code to production, asking other people for approvals, auth roles, and of course tons of meetings with the end user to find out what they need.

I guess when I was a junior engineer, I would spend more time looking at code, though I used to work for small companies. So it is hard for me to judge if the extra time spent coding, was because of me being a junior or because it was a small company.

The kicker, is when we interview devs, most of the interview is just about coding. Very little of it is about the stuff I listed..