One of my best commits was removing about 60K lines of code, a whole "server" (it was early 2000's) with that had to hold all of its state in memory and replacing them with about 5k of logic that was lightweight enough to piggyback into another service and had no in-memory state at all. That was pure a algorithmic win - figuring out that a specific guided subgraph isomorphism where the target was a tree (directed, non cyclic graph with a single root) was possible by a single walk through the origin (general) directed bi-graph while emitting vertices and edges to the output graph (tree) and maintaining only a small in-process peek-able stack of steps taken from the root that can affect the current generation step (not necessarily just parent path).I still remember the behemoth of a commit that was "-60,000 (or similar) lines of code". Best commit I ever pushed.
Those were fun times. Hadn't done anything algorithmically impressive since.
ifellover|8 months ago
Cthulhu_|8 months ago
But a lot is opportunity. Like, I had the opportunity to work on an old PHP backend, 500ms - 1 second response times (thanks in part to it writing everything to a giant XML string which was then parsed and converted to a JSON blob before being sent back over the line). Simply rewriting it in naive / best practices Go changed response times to 10 ms. In hindsight the project was far too big to rewrite on my own and I should have spent six months to a year trying to optimize and refactor it, but, hindsight.
PaulRobinson|8 months ago
amake|8 months ago
meistertigran|8 months ago
It's the difference between hearing a lecture from a "bad" professor in Uni and watching a lecture video by Feynman, where he tries to get rid of scientific terms, when explaining things in simple terms to the public.
As long as you get a definition for your terms, things are manageable.
dev0p|8 months ago
weaksauce|8 months ago
neilv|8 months ago
One way to often arrive at it is to just draw some graphs, on paper/whiteboard, and manually step through examples, pointing with your finger/pen, drawing changes, and sometimes drawing a table. You'll get a better idea of what has to happen, and what the opportunities are.
This sounds "Then draw the rest of the owl," but it can work, once you get immersed.
Then code it up. And when you spot a clever opportunity, and find the right language to document your solution, it can sound like a brilliant insight that you could just pull out of the air, because you are so knowledgeable and smart in general. When you actually had to work through that specific problem, to the point you understood it, like Feynman would want you to.
I think Feynman would tell us to work through problems. And that Feynman would really f-ing hate Leetcode performance art interviews (like he was dismayed when he found students who'd rote-memorize the things to say). Don't let Leetcode asshattery make you think you're "not good at" algorithms.
sensanaty|8 months ago
Jokes aside, could I get a layman's explanation of the graph theory stuff here? Sounds pretty cool but the terminology escapes me
ninetyninenine|8 months ago
It’s because every task was doing a database call but they had a whole repo and aws lambdas for running it. Stupidest thing I’ve ever seen.
motorest|8 months ago
Your example raises some serious red flags. Did it ever dawned upon you that the reason these background tasks were offloaded to a dedicated service might have been to shed this load from your main server and protect it from handling sudden peaks in demand?
ninetyninenine|8 months ago
Given two graphs one is a tree you cannot determine if the tree is a subgraph of the other graph in one walk through?
It’s only possible if you’re given additional information? Like a starting node to search from? I’m genuinely confused?
jcynix|8 months ago
http://www.nsl.com/papers/samefringe.htm
If you flatten both of your trees/graphs and regard the output as strings of nodes, you reduce your task to a substring search.
Now if you want to verify if the structures and not just the leave nodes are identical, you might be able to encode structure information into you strings.
bironran|8 months ago
unknown|8 months ago
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ccppurcell|8 months ago
hershey890|8 months ago
There’s also a role called being an algorithms engineer in standard tech companies (typically for lower level work like networking, embedded systems, graphics, or embedded systems) but the lack of an engineering background may hamstring you there. Engineers working in crypto also use a fair bit of algorithms knowledge.
I do low level work at a top company, and you only use algorithms knowledge on the job a couple of times a year at best.
fuzztester|8 months ago
I heard from someone who was in that field, that the main qualification for such a job is analytical ability and mathematics knowledge, apart from programming skills, of course.
bironran|8 months ago
These days it's very different, mostly large-ish distributed systems.
chamomeal|8 months ago
ninetyninenine|8 months ago
The graph that is to be determined as a subset is a tree. From there he says it can be done in an algorithm that only traverses every node at most one time.
I’m assuming he’s also given a starting node in the original graph and the algorithm just traverses both graphs at the same time starting from the given start node in the original graph and the root in the tree to see if they match? Standard DFS or BFS works here.
I may be mistaken. Because I don’t see any other way to do it in one walk through unless you are given a starting node in the original graph but I could be mistaken.
To your other point, The algorithm inherently has to also be statefull. All traversal algorithms for graphs have to have long term state. Simply because if your at a node in a graph and it has like 40 paths to other places you can literally only go down one path at a time and you have to statefully remember that node has another 39 paths that you have to come back to later.
ninetyninenine|8 months ago
You are starting at a specific node in the graph and saying that if there’s an isomorphism the target tree root node must be equivalent to that specific starting node in the original graph.
You just walk through the original graph following the pattern of the target tree and if something doesn’t match it’s false otherwise true? Am I mistaken here? Again the target being a tree is a bit irrelevant. This will work for any subgraph as long as as you are also given starting point nodes for both the target and the original graph?
bironran|8 months ago
bravesoul2|8 months ago
fuzztester|8 months ago
the select-a-bunch-of-code-and-then-zap-it-with-the-Del-key is the best hardware algorithm.
ddejohn|8 months ago
bironran|8 months ago
bbkane|8 months ago
bironran|8 months ago
antihero|8 months ago
b0a04gl|8 months ago
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pech0rin|8 months ago
cess11|8 months ago
Is this, from elsewhere in the thread, a system rethink, https://github.com/dotnet/runtime/pull/36715/files ?
I've worked on a product that reinvented parts of the standard library in confusing and unexpected ways, meaning that a lot of the code could easily be compacted 10-50 times in many place, i.e. 20-50 lines could be turned into 1-5 or so. I argued for doing this and deleting a lot of the code base, which didn't take hold before me and every other dev left except one. Nine months after that they had deleted half the code base out of necessity, roughly 2 MLOC to 1 MLOC, because most of it wasn't actually used much by the customers and the lone developer just couldn't manage the mess on his own.
I wouldn't call that a system rethink.