I've been watching my colleagues' adoption of Copilot with interest. From what I can tell, the people who are the most convinced that it improves their productivity have an understanding of developer productivity that is very much in line with that of the managers in this story.
Recently I refactored about 8,000 lines of vibe-coded bloat down into about 40 lines that ran ten times as fast, required 1/20 as much memory, and eliminated both the defect I was tasked with resolving and several others that I found along the way. (Tangentially, LLM-generated unit tests never cease to amaze me.) The PHBs didn't particularly appreciate my efforts, either. We've got a very expensive Copilot Enterprise license to continue justifying.
There will be vibe and amateur banged out hustle trash, which will be the cheap plastic cutlery of the software world.
There will be lovingly hand crafted by experts code (possibly using some AI but in the hands of someone who knows their shit) that will be like the fine stuff and will cost many times more.
A lot of stuff will get prototyped as crap and then if it gets traction reimplemented with quality.
This was said about large frameworks like electron on the desktop, but outside of some specific technical niches it literally doesn’t matter to end users.
Back in the day, if you went to a website you could always tell who wrote their HTML by hand and who used a tool like GruntPage, Dreamweaver, etc. even without looking at the META tags. The by-hand stuff was like a polished jewel that had only as much layout, styling, and markup as needed to get the desired effect. The proprietary web editor stuff was encrusted with extraneous tags and vendor-specific extensions (like mso: attributes and styles in GruntPage).
Then as now, if you let the machine do the thinking for you, the result was a steaming mess. Up to you if that was accessible (and for many, it was).
If the vision were true, we should see it happen with normal goods too. Quality physical goods do not beat the shit goods in the market : crap furniture is the canonical example (with blog articles discussing the issue).
Software (and movies) is free for subsequent copies, so at first sight you might think software is completely different from physical goods.
However for most factory produced goods, designing and building the factory is the major cost. The marginal cost of producing each copy of an item might be reasonably low (highly dependent on raw materials and labor costs?).
Many expensive physical goods are dominated by the initial design costs, so an expensive Maserati might be complete shit (bought for image status or Veblen reasons, not because it is high quality). There's a reason why the best products are often midrange. The per unit 2..n reproduction cost of cheap physical goods is always low almost by definition.
Some parts of iPhone software are high quality (e.g. the security is astounding). Some parts are bad. Apple monetisation adds non-optional features that have negative value to me: however those features have positive value to Apple.
What happens is the price difference gets huge. Quality furniture does beat shit at the high end of the market, but a real quality bed or sofa costs over a thousand dollars and up from there. The price difference between shit and quality starts at 5-10X.
Tangent but -- one furniture hack I've found is that if you don't want to pay a lot go for the simplest design you can find made of basic wood or metal. It'll be... a wood or metal kit that assembles into the basic form of what is needed. Wood is often unfinished or minimally finished. That stuff is pretty durable. Things that look "fancy" but are cheap tend to be utter trash, made of the worst materials with poor tolerances. A more elaborate or artistic design plus quality equals expensive.
When I say minimal I mean minimal. A cheap quality bed frame is a rack the mattress sits on. A cheap quality dresser is basically bins on tracks.
Ironically places like Amazon is where you find this cheap quality minimal stuff. Furniture stores are complete trash unless they are artisan, often local, like I live in Ohio and there are artisan Amish furniture sellers that sell good (but $$$) stuff that is literally hand made. But find one that is actually sourcing or even tied to an Amish community. You don't have to look into the store, just the stuff inside. It will be solid and build via obvious craft joinery, etc., and will weigh a ton. (and you're supporting a local community)
So I wonder if software will start to look like that. Pay a lot (like enterprise prices) for highly regarded pro software or find something minimal "hand made" by a 1-5 person shop. The world of quality native Mac apps comes to mind for the latter.
I guess it depends on how much you like things like well-obfuscated smoke tests and mocks that don't accurately simulate relevant parts of the behavior of the module they're mocking.
I don’t believe your numbers unless your colleagues are exceptionally bad programmers.
I’m using AI a lot too. I don’t accept all the changes if they look bad. I also keep things concise. I’ve never seen it generate something so bad I could delete 99 percent of it.
90%+ is a stretch. Anecdotally I have cleaned up a vibe coded PR and removed at least half of the code. The thing with the LLM is that often they will make some decision up front that has downstream ramifications for how the entire project's code is structured. I don't think I've seen an LLM re-visit it's assumptions, instead they code around them.
In the case I saw, it was rust code and the LLM typed some argument as a Arc<Mutex<_>> when it absolutely did not need to, which caused the entire PR to inflate. The vibe coder apparently didn't catch this and just kept it vibing... Technically the code did what it needed to do but was super inefficient.
It would have been easy for me to just accept the PR. It technically worked. But it was garbage.
Yes. This is why I’m still “designing” projects and asking fairly specific things most of the time.
But it’s pretty obvious when it produces garbage. So you’d reject it there and then. At the very least code review will raise so many questions. How did 8000 lines make it into the code base?
I think you are over-estimating how much people care. If the code runs and provides the desired result, there are many, many people who will simply ship it. This is the bed we made for ourselves.
I've never seen 8000 -> 40, but I have done ~10 kLoC -> ~600.
Aggggressively "You can write Java in any language" style JavaScript (`Factory`, `Strategy`, etc) plus a whole mini state machine framework that was replaceable with judicious use of iterators.
(This was at Google, and I suspected it was a promo project gone metastatic.)
The original used a Shlemiel the painter algorithm, a whole bunch of "enterprise" coding patterns, and its own implementations of a bunch of things we already had. Including domain objects, which meant that a whole bunch of excess glue code was needed to interface with the rest of the system.
Every now and then, in between reasonable and almost-reasonable suggestions, Copilot will suggest a pile of code, stylistically consistent with the function I’m editing, the extends clear off the bottom of the page. I haven’t been inspired to hit tab a couple times and try to reverse engineer the resulting vomit of code, but I can easily imagine a new programmer accepting the code because AI! or, perhaps worse, hitting tab without even noticing.
This is one of those stories that I am sure has happened, but when it comes to "and then they never asked him again le XD face" it's clearly just made up.
We had free soft drinks in the fridges at one place I worked. Cost-cutting measures were coming and I sent an email to all of engineering (including the VP) asking who wanted to join me in a shopping trip at 10AM to restock the fridge. In the email, I estimated that it would take between 60 and 90 minutes. Two carfuls of engineers left at 10AM sharp and returned a little before noon and restocked the fridges.
That was the first and last time we had to do it, as the soft drinks returned the following week.
That was exactly the point of the protest that was couched as totally-not-a-protest.
(I skipped clarifying in the GP post that they took the soft drinks out of the fridge and emailed the new policy, rather than merely being a little slow in restocking.)
Bill Atkinson recently died and there’s a great HN discussion about him. He had a good relationship with Steve Jobs; it’s reasonable to assume it’s true that he got left alone, especially if Andy Hertzfeld is the person making the assertion.
It was Bill fucking Atkinson. Not a disposable random contractor you hire by the dozen when you need to build more CRUD APIs.
At that time at Apple, even as an IC, Bill had lines of communication to Steve and was extremely valued. There's absolutely no doubt he could get "middle manager shenanigans" gone simply by not complying or "maliciously complying". Hell, I've seen ICs far less valuable, or even close to negative value get away with stunts far worse than these, succeed and keep their jobs. Out of all the stories in Folklore.org, this is the one you have an issue with?!
Most people know who Bill Atkinson on this forum. The story premise that he wrote negative code isn't my gripe, I am sure it happened.
The outcome where all of a sudden leadership just shit its pants and doesn't communicate at all and never followed up... It's like writing "and then everyone clapped" for programmers.
Man you must have only worked with really good management. "Management realised the stupid policy change they announced with great fanfare was stupid, stopped doing it, and never mentioned it again" is something I've seen several times in my career.
It just occurred to me that really good management is like a fruit at the optimum of its ripeness - it stays that way only for a while so enjoy it while it lasts otherwise it will rot and stink.
> The outcome where all of a sudden leadership just shit its pants and doesn't communicate at all and never followed up...
This is not only a possible outcome, it is a common one. When leadership realizes it was a mistake to instill one of these types of "productivity motivators", it is easier to disappear it and never (officially) speak of it again.
1. The site is called folklore.org. You’re sort of saying the site is true to its name.
2. It’s a direct recollection from someone who was there, not an unnamed “my cousin’s best friend” or literal folklore that is passed down by oral tradition. Andy knew Bill and was there. There is no clear motivation to tell a fictional story when there were so many real ones.
3. The specifics line up very well with what we know about Bill Atkinson and some his wizardry needed to make the Mac work.
Given this, it’s much easier to assume that your assertion is what is made up.
How long would a quicksort (say, of integers) be in 68000 assembly? Maybe 20 lines? My 68000 isn't very good. The real advantage of writing it in Haskell is that it's automatically applicable to anything that's Ord, that is, ordered.
This is great, thanks! I was thinking it could be much simpler, but it looks like I was mistaken.
I'm trying to code up a version in ARM assembly to compare, and it looks like it'll be about 30 lines; when I get that working I can compare to see why the difference. In some ways the 68000 is more expressive than ARM, like being able to reference memory directly, even twice in one instruction.
(Am I misunderstanding this, or is this the source code to Apple System 7.1? There seems to have been a mailing list about this codebase from 02018 to 02021: https://lists.ucc.gu.uwa.edu.au/pipermail/cdg5/)
> Am I misunderstanding this, or is this the source code to Apple System 7.1?
More or less, yes. It only encompasses the system (i.e. not applications like the Finder) and isn't entirely complete, but it's still a great window into the world of Apple pre-OS X.
This mailing list was for a set of projects which focused on taking this code dump (among other things) and making it compile, ideally to reproduce released binaries.
Here's a quicksort in 20 lines of ARM assembly, sorting an array of integers in memory starting at [r0] and ending at [r1] (i.e., inclusive bounds):
quirks: push {r4, r5, r6, lr}
4: subs r2, r0, r1
bhs 3f @ Exit if carry set (no borrow).
mov r5, r1 @ This frees up r1 as a temp.
mov r6, r0
ldr r3, [r5]
1: ldr r4, [r5, r2]
cmp r4, r3 @ Is element at r2 ≤ pivot?
bgt 2f @ If so, swap elements at r2 and r6,
ldr r1, [r6] @ Load previously first element in > side,
str r4, [r6], #4 @ and postincrement r6,
str r1, [r5, r2] @ and save previous element at end of > side.
2: adds r2, #4 @ Increment offset. Reached the end (>0)?
ble 1b @ Loop if ≤ 0 (either N && !V && !C, or !N && V && C)
subs r1, r6, #8
bl quirks @ Recursively sort left partition.
mov r0, r6
mov r1, r5
b 4b @ Tail-recursively sort right partition.
3: pop {r4, r5, r6, pc}
In college I worked for a company whose goal was to prove that their management techniques could get a bunch of freshman to write quality code.
They couldn't. I would go find the code that caused a bug, fix it and discover that the bug was still there. Because previous students had, rather than add a parameter to a function, would make a copy and slightly modify it.
I deleted about 3/4 of their code base (thousands of lines of Turbo Pascal) that fall.
Bonus: the customer was the Department of Energy, and the program managed nuclear material inventory. Sleep tight.
In addition to not breaking existing code, also has added benefit of boosting personal contribution metrics in eyes of management. Oh and it's really easy to revert things - all I have to do is find the latest copy and delete it. It'll work great, promise.
Add tests to the function as it exists today. Submit. Add new functionality, make sure tests still pass. Done. Updating a function here and there shouldn't require more staff.
This implies adding tests that accurately capture all the nuances of the function and don't test the simplest logic need to hit code coverage. When we are talking someone new to the function, then this is about the same as asking them to learn the function so they can be sure they didn't make an error when they changed it. The benefit of tests is that they are written by the person creating the function originally who is most aware of the hidden dangers of it.
I'm distrustful on unit testing as I've seen too many tests written to make code coverage numbers but that don't actually test the functions they are aimed at. A non-trivial number which run the function asynchronously and then report a successful run before the function even finishes executing, meaning that even throwing errors don't fail the tests (granted, part of that is on the testing framework for letting unexpected errors ever result in a pass).
Of course, this is the way you need to write tests -- to test the actual logical pathways and requirements of the code, and not just finagle them together to overfit some code coverage metric.
We have a saying at my work. "If you like it, then you should have put a test on it". If the original author didn't add adequate coverage and you end up breaking them, it's on them.
Yes, but it just creates a new immutable branch in the commit graph. All the old commits are still there, but if they're not reachable from the root refs, they'll get GC'd eventually. The only mutable parts are HEAD, branch/tag names etc that can be changed to point to whatever. Anything that has a hash is necessarily immutable, because changing it in any way (including changing its parent pointer(s)) changes the hash.
I once had to deal with some contractors that habitually did this, when confronted on how this could lead to confusion they said "that's what Ctrl+F is for."
Oh boy! This reminded me of one of my worst tech leads. He pushed secret tokens to github. When I asked in the team meeting why would we do this instead of using secrets manager, the response was: "These are private respos. Also we signed an NDA before joining the company"
I work with someone who has a habit of code duplication like this. Typically it’s an effort to turn around something quickly for someone who is demanding and loud. Refactoring the shared function to support the end edge case would take more time and testing, so he doesn’t do it. This is a symptom of the core problem.
> The duplicated code that needs updating in 50 places every time a bug or new feature comes in? Yes, I'm sure.
If you're talking about duplicate code showing up in 50 places then your problem is not code duplication but incompetent developers not being able to maintain a project.
If instead you're talking about code with a passing resemblance showing up in 2 or 3 places then odds are you're actually looking at more maintainable code straight in the eye and you're not able to understand how that makes the project more maintainable.
But it's a false premise; the claim is that just copy/pasting something is faster, but is it really?
The demanding / loud person can and should be ignored; as a developer, you are responsible for code quality and maintainability, not your / their manager.
I have a habit of doing this for data processing code (python, polars).
For other code it's an absolute stink and i agree. But for data transforms... I've seen the alternative, a neatly abstracted in-house library of abstracted combinations of dataframe operations with different parameters and.. It's the most aesthetically pleasing unfathomable hell I've ever experienced.
So now, when munging dataframes, i will be much faster to reach for 'copy that function and modify it slightly' - maintenance headache, but at least the result is readable.
> I work with someone who has a habit of code duplication like this.
Are you sure it's code duplication?
I mean, read your own description: the new function does not need to support edge cases. Having to handle edge cases is a huge code smell, and a clear sign of premature generalization.
And you even admit the guy was more productive and added less bugs?
There is a reason why the mistakes caused by naive approaches to Don't Repeat Yourself (DRY) are corrected with Write Everything Twice (WET).
I didn’t say less bugs. There are a lot of bugs, they are just localized to each call, and then copy/pasted all over the place. So when found, they need to be fixed in a bunch of places. It makes for quite the mess.
They just aren’t making changes to the shared function, so they don’t need to test existing functionality still works, just their single use case.
This reminds me of my experience. I've worked for one company based in SEA that had almost identical portals in several countries in the region. Portals were developed by an Australian company and I was hired to maintain existing/develop new portals.
Source code for each portal was stored in a separate Git repository. I've asked the original authors how am I supposed to fix bugs that affect all the portals or develop new functionality for all the portals. The answer was to backport all fixes manually to all copies of the source code.
Then I've asked: isn't it possible to use a single source repository and use feature flags to customize appearance and features of each portals. Original authors said that it is impossible.
In 2-3 months I've merged the code of 4-5 portals into one repository, added feature flags, upgraded the framework version, release went flawlessly, and it was possible to fix a bug simultaneously for all the portals or develop a new functionality available across all the countries where the company operated. It was a huge relief for me as copying bugfixes manually was tedious and error-prone process.
> Bonus: the customer was the Department of Energy, and the program managed nuclear material inventory. Sleep tight.
These are my favorite (in a sense) programmer stories--that there's these incomprehensible piles of rubbish that somehow, like, run The World and things, and yet somehow things manage to work (in an outwardly observable sense).
Although, I recall two somewhat recent stories where this wasn't the case. The unemployment benefits fiascos during early Covid-era, and some more recent air traffic control-related things (one which effected me personally).
I've been playing with Claude 4 Sonnet in VS Code and found it quite good. As part of the development plan, on its own it had included an optimization phase where it profiled my go code, identified some hot spots, and proposed ways to optimize it. For the most critical area, it suggested using a prefix tree which it wrote on the spot, adapted to my code, wrote benchmarks to compare the old and new version (5x improvement). Then it wrote specific tests to make sure both versions behaved the same. Then it made sure all my other tests passed and wrote a report on everything.
There were three performance optimizations in total, one which I rejected because the gain was minimal for typical use case and there are still some memory allocation optimization which I have deferred with because I'm in the middle of a major refactor of the code. The LLM has already written down plans to restart this process later when I more time.
Note for anyone wondering: reposts are ok after a year or so (https://news.ycombinator.com/newsfaq.html).In addition to it being fun to revisit perennials sometimes (though not too often), this is also a way for newer cohorts to encounter the classics for the first time—an important function of this site!
I am a simple man
I see -2k lines of code, I upvote
I've told this story to every client who tried schemes to benchmark productivity by some single-axis metric. The fact that it was Atkinson demonstrates that real productivity is only benchmarkable by utility, and if you can get a truly accurate quantification for that then you're on the shortlist for a Nobel in economics.
Important enough to re-state whenever it arises - once you have 2 or more axes/dimensions, you no longer have a linear ordering. You need to map back to a number line to "compare". This is the motivation or driving force toward your "single axis". { That doesn't mean it's a goal any easier to realize, though. I am attempting to merely clarify/amplify rather than dispute here.. }
I figured that articles like folklore are like an amusing movie file (say someone chopping a skin of a watermelon) that's repeatedly being passed around reddit.
Microsoft, the number being 30%; whether that's accurate is another matter. Twenty years ago people already used IDEs to generate boilerplate code (remember Java's getters/setters/hashCode/toString?) because some guy in a book said you had to.
I often have a mental picture of the thing I need, I start writing it, get a bit "stuck" on architecture and think I could be using a ready made library for this. I find one or a few of them, look at the code (which is obviously more generic) and realize it's many times as large as I thought the entire project should be. With few exceptions the train of thought doesn't even reach the "Do I want to carry this around and baby sit it?" stage. Some how this continues to surprise me every time.
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.
Otherwise just downvote or flag I guess, but this comment of yours just reads as an insult to a person that maybe did not put the most effort into writing their comment, but seems genuine to me at least.
I advise checking out the users other comments before jumping to conclusions. Doesn't look AI generated to me, rather just an "individual" writing style. Only because it's possible doesn't mean its true. Maybe user can confirm?
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’m a hobby programmer and lucky enough to script a lot of things at work. I consider myself fairly adept at some parts of programming, but comments like these make it so clear to me that I have an absolutely massive universe of unknowns that I’m not sure I have enough of a lifetime left to learn about.
Read some good books on data structures and algorithms, and you'll be catching up with this sort of comment in no time. And then realise there will always be a universe of unknowns to you. :-) Good luck, and keep going.
do try (so you get the joy of 'small' wins), also do know that it's untouchable (so you don't despair when you don't master quantum mechanics in one lifetime)
You could've figured out this one with basic familiarity with how graphs are represented, constructed, and navigated, and just working through it.
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.
I despise leetcode interviews. These days, with coding LLMs, I see them as even less relevant than they were before.
Yet, you ask someone "how do you build an efficient LFU" and get blank stares (I just LOVE the memcache solution of regions and probabilistic promotion/demotion).
(More than?) half of the difficulty comes from the vocabulary. It’s very much a shibboleth—learn to talk the talk and people will assume you are a genius who walks the walk.
That! It took me a while to start. My education of graph theory wasn't much better than your average college grad. But I found that fascinating and started reading. I was also very lucky to have had two great mentors - my TL and the product's architect, the former helped me to expend my understanding of the field.
I want to believe a lot of these algorithms will "come to you" if you're ever in a similar situation; only later will you learn that they have a name, or there's books written about it, etc.
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.
Yes. I invented the Trie data structure when I was 19. It was very exciting finding out it had a name, and it was indeed considered a good fit for my use case.
Thats so funny, I had the exact same experience. And when I was 16 I "invented" csv's because I was too lazy to setup SQL for my discord bot. I like to think I've gotten better at searching for the correct solution to things rather than just jumping in with my best guess.
I was just going to say the same— LLMs are great for giving a name to a described concept, architecture, or phenomenon. And I would argue that hallucinations don't actually much matter for this usage as you're going to turn around and google the name anyway, once you've been told it.
This is my experience, and my favorite way to learn: go in blindly, look things up when you get stuck/run out of ideas. I think it forces a deeper understanding of the topic, and really helps things "stick". I assume it's related to the massive dumps of dopamine that come from the "Eureka!" moments.
I've "invented" all sorts of old patents, all sorts of algorithms, including the PID algorithm. I think it helped form a very practically useful "intuition".
But, I've noticed that some people are passionately against this type of self exploration.
A lot if it is just technical jargon. Which doesn't mean it's bad, one has to have a way to talk about things, but the underlying logic, I've found, is usually graspable for most people.
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.
Hi I'm a mathematician with a background in graph theory and algorithms. I'm trying to find a job outside academia. Can you elaborate on the kind of work you were doing? Sounds like I could fruitfully apply my skills to something like that. Cheers!
Look into quantitative analyst roles at finance firms if you’re that smart.
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.
That was about 20 years ago. Not much translates to today's world. I was in the algorithms team working on a CMDB product. Great tech, terrible marketing.
These days it's very different, mostly large-ish distributed systems.
You can try to get a job at an investment bank, if you're okay with heavy slogging, i.e., in terms of hours, which I have heard is the case, although that could be wrong.
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.
I would love a little more context on this, cause it sounds super interesting and I also have zero clue what you’re talking about. But translating a stateful program into a stateless one sounds like absolute magic that I would love to know about
He has two graphs. He wants to determine if one graph is a subset of another graph.
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.
I oversimplified the problem :). Really it was about generating an isomporhic-ish view, based on some user defined rules, of an existing graph, itself generated by a subgraph isomorphism by a query language.
Think a computer network as a graph, with various other configuration items like processes, attached drives, etc (something also known as a CMDB). Query that graph to generate a subgraph out of it. Then use rules to make that subgraph appear as a tree of layers (tree but in each layer you may have additional edges between the vertices) because trees are efficient, non-complex representation on 2d space (i.e. monitors).
However, a child node in that tree isn't necessarily connected directly to the parent node. E.g. one of the rules may be "display the sub network and the attached drives in a single layer", so now the parent node, the gateway, has both network nodes (directly connected to it) and attached drives (indirectly connected to it) as direct descendants.
Extend this to be able to connect through any descendant, direct or indirect (gateway -> network node -> disk -> config file -> config value - but put the config value on the level of the network node and build a link between them to represent the compound relationship).
Walk through the original subgraph while evaluating the rules and build a "trace back" stack to let you understand how to build each layer even in the presence of compound links while performing a single walkthrough instead of nm (original vertices rules for generation).
As I said, that was a lot of fun. I miss those days.
I deleted an entire micro service of task runners and replaced it with a library that uses setTimeout as the primitive driving tasks from our main server.
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.
> I deleted an entire micro service of task runners and replaced it with a library that uses setTimeout as the primitive driving tasks from our main server.
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?
These background tasks are all database calls. That means the cpu is just waiting on the database for the majority of the call. Most modern servers can handle 10k of these calls concurrently. And you can do this off of one not so powerful CPU. Even half a cpu can handle this. Of course it depends on the CPU but you get my point.
The database is the bottleneck. The database is the thing that needs to be scaled first before you scale servers. This is the most common web application pattern. One way is providing more compute to the database (sharding is better then increasing cpu power as the bottleneck in the database is usually filesystem access not cpu power). Another way is to have a queue buffer the traffic spikes. Both of these are addressing an issue with the database first.
In most web apps. All the server does is wait for a database. The database is doing compute. You never want the server to do compute as that becomes what we call a “blocking call.” These blocking calls are the ones you offload to an external service as these calls “block” entire cpu threads. database calls do not “block” as the server will context switch to another green thread during database calls.
If you work somewhere where you’re scaling crud servers but not after scaling a central database it usually means you’re in a company that doesn’t get it and overemphasizes on “architecture” over common sense. It’s actually extremely common in lower tier small companies to have not so smart people build things like this that don’t make any sense. They aren’t thinking coherently and I’ve seen tons of people who just miss this common sense notion.
I’ll be Frank. It’s stupid and defies common sense. It’s likely you are doing this? But it’s also extremely commonplace.
The target being a tree is irrelevant right? It’s the “guided” part that makes a single walk through possible?
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?
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.
I was thinking in terms of finding all subgraph isomorphisms. But this definitely is O(N) if all you need is one solution.
But then I thought about it even further and this reduces to sliding window problem. In this case you still need to travel to each node in the window to see if there’s a match.
So it cannot be that you traverse each node once. Not if you want to find all possible subgraph isomorphisms.
Imagine a string that is a fractal of substrings:
rrrrrrrrrrrrrrrrrrrrrrrrrrrr
And the other one:
rrrrrrr
Right? The sliding window for rrrrrrr will be 7 in length and you need to traverse that entire window every time you move it. So by that fact alone every node is traversed at least 7 times.
A long time ago I was working in a big project where the PLs came up with the most horrible metric I've ever seen. They made a big handwritten list, visible for the whole team, where they marked for each individual developer how many bugs they had fixed and how many bugs they had caused.
I couldn't believe my eyes. I was working in my own project beside this team with the list, so thankfully I was left out of the whole disaster.
A guy I knew wasn't that lucky. I saw how he suffered from this harmful list. Then I told him a story about the Danish film director Lars von Trier I recently had heard. von Trier was going to be chosen to appear in a "canon" list of important Danish artists that the goverment was responsible for. He then made a short film where he took the Danish flag (red with a white cross) and cut out the white lines and stitched it together again, forming a red communist flag. von Trier was immediately made persona non grata and removed from the "canon".
Later that day my friend approached the bugs caused/fixed list, cut out his own line, taped it together and put it on the wall again. I never forget how a PL came in the room later, stood and gazed at the list for a long time before he realized what had happened. "Did you do this?" he asked my friend. "Yes", he answered. "Why?", said the PL. "I don't want to be part of that list", he answered. The next day the list was gone.
The danish flag is a white cross on a red background. If you cut out the white cross, you will be left with four rectangles of red, which can be pushed together and sewn up again, forming a solid red flag
Just because lines of code is being reported it didn't mean that bigger automatically means better. It does tell a story about how one is spending their time though.
An old Dilbert cartoon had the pointy haired boss declare monetary rewards for every fixed bug in their product. Wally went back to his desk murmuring "today I'm going to code me a minivan!"
it's just a stand-in for "expensive but relatable purchase". He's saying "I'm about to write so many bugs that the sum reward will be in the tens of thousands"
I am currently working on a piece of code which I am actively trying to simplify and make smaller. It's not a piece of code which has any business ever getting larger or having more features. The design is such that it is feature complete until a whole system redesign is required at which point the code would be itself wholesale replaced. So I am sitting here trying to codegolf the code down in complexity and size. It's not just important to keep it simple, it's also important to keep it small as this bit of code is, as part of this solution, going to be executed using python -c. All the while not taking the piss and making it unreadable (I can use a minifier for that).
In an old ops role we had a metric called ticket touches. One of my workmates had almost double of everyone else but only for that metric. We had a look and it was due to how he wrote notes in tickets instead of putting all his findings in a comment he would do it incrementally as he went along. Neither of these ways were wrong it just inflated that stat for him.
This is a good example[1] at 64k LOC removal. We removed built-in support for C# + WinRT interop on Windows and instead required users to use a source-generation tool (which is still the case today). This was a breaking change. We realized we had one chance to do this and took it.
Before a recent annual performance review, I looked over my stats in the company monolith repo and found out I was net-negative on lines of code. That comes mostly from removing auto-generated API code and types (the company had moved to a new API and one of my projects was removing v1) but it was quite funny to think about going to work every day to erase code.
258 comments
[ 1.9 ms ] story [ 228 ms ] threadRecently I refactored about 8,000 lines of vibe-coded bloat down into about 40 lines that ran ten times as fast, required 1/20 as much memory, and eliminated both the defect I was tasked with resolving and several others that I found along the way. (Tangentially, LLM-generated unit tests never cease to amaze me.) The PHBs didn't particularly appreciate my efforts, either. We've got a very expensive Copilot Enterprise license to continue justifying.
There will be vibe and amateur banged out hustle trash, which will be the cheap plastic cutlery of the software world.
There will be lovingly hand crafted by experts code (possibly using some AI but in the hands of someone who knows their shit) that will be like the fine stuff and will cost many times more.
A lot of stuff will get prototyped as crap and then if it gets traction reimplemented with quality.
Pre-vibe-coding it was more like the difference between fine silverware and cheap stamped metal stuff.
Then as now, if you let the machine do the thinking for you, the result was a steaming mess. Up to you if that was accessible (and for many, it was).
An LLM is just displaying the next statistical token.
Completely different.
If the vision were true, we should see it happen with normal goods too. Quality physical goods do not beat the shit goods in the market : crap furniture is the canonical example (with blog articles discussing the issue).
Software (and movies) is free for subsequent copies, so at first sight you might think software is completely different from physical goods.
However for most factory produced goods, designing and building the factory is the major cost. The marginal cost of producing each copy of an item might be reasonably low (highly dependent on raw materials and labor costs?).
Many expensive physical goods are dominated by the initial design costs, so an expensive Maserati might be complete shit (bought for image status or Veblen reasons, not because it is high quality). There's a reason why the best products are often midrange. The per unit 2..n reproduction cost of cheap physical goods is always low almost by definition.
Some parts of iPhone software are high quality (e.g. the security is astounding). Some parts are bad. Apple monetisation adds non-optional features that have negative value to me: however those features have positive value to Apple.
Tangent but -- one furniture hack I've found is that if you don't want to pay a lot go for the simplest design you can find made of basic wood or metal. It'll be... a wood or metal kit that assembles into the basic form of what is needed. Wood is often unfinished or minimally finished. That stuff is pretty durable. Things that look "fancy" but are cheap tend to be utter trash, made of the worst materials with poor tolerances. A more elaborate or artistic design plus quality equals expensive.
When I say minimal I mean minimal. A cheap quality bed frame is a rack the mattress sits on. A cheap quality dresser is basically bins on tracks.
Ironically places like Amazon is where you find this cheap quality minimal stuff. Furniture stores are complete trash unless they are artisan, often local, like I live in Ohio and there are artisan Amish furniture sellers that sell good (but $$$) stuff that is literally hand made. But find one that is actually sourcing or even tied to an Amish community. You don't have to look into the store, just the stuff inside. It will be solid and build via obvious craft joinery, etc., and will weigh a ton. (and you're supporting a local community)
So I wonder if software will start to look like that. Pay a lot (like enterprise prices) for highly regarded pro software or find something minimal "hand made" by a 1-5 person shop. The world of quality native Mac apps comes to mind for the latter.
I mean, I like killing crappy code as much as the next guy, but I don't want that to be my daily existence. Ugggh.
In a good or bad way?
I've found AI pretty helpful to write tests, specially if you already have an existing one as a template.
I’m using AI a lot too. I don’t accept all the changes if they look bad. I also keep things concise. I’ve never seen it generate something so bad I could delete 99 percent of it.
In the case I saw, it was rust code and the LLM typed some argument as a Arc<Mutex<_>> when it absolutely did not need to, which caused the entire PR to inflate. The vibe coder apparently didn't catch this and just kept it vibing... Technically the code did what it needed to do but was super inefficient.
It would have been easy for me to just accept the PR. It technically worked. But it was garbage.
But it’s pretty obvious when it produces garbage. So you’d reject it there and then. At the very least code review will raise so many questions. How did 8000 lines make it into the code base?
Aggggressively "You can write Java in any language" style JavaScript (`Factory`, `Strategy`, etc) plus a whole mini state machine framework that was replaceable with judicious use of iterators.
(This was at Google, and I suspected it was a promo project gone metastatic.)
I get the sentiment though, "He blew management's mind so much they made an exception for him".
But, Folklore.org is a bit less onanistic than ESR's jargon file.
That was the first and last time we had to do it, as the soft drinks returned the following week.
(I skipped clarifying in the GP post that they took the soft drinks out of the fridge and emailed the new policy, rather than merely being a little slow in restocking.)
Too many forget that it's one of the few legal ways to supply your employees with performance enhancing drugs.
At that time at Apple, even as an IC, Bill had lines of communication to Steve and was extremely valued. There's absolutely no doubt he could get "middle manager shenanigans" gone simply by not complying or "maliciously complying". Hell, I've seen ICs far less valuable, or even close to negative value get away with stunts far worse than these, succeed and keep their jobs. Out of all the stories in Folklore.org, this is the one you have an issue with?!
The outcome where all of a sudden leadership just shit its pants and doesn't communicate at all and never followed up... It's like writing "and then everyone clapped" for programmers.
This is not only a possible outcome, it is a common one. When leadership realizes it was a mistake to instill one of these types of "productivity motivators", it is easier to disappear it and never (officially) speak of it again.
2. It’s a direct recollection from someone who was there, not an unnamed “my cousin’s best friend” or literal folklore that is passed down by oral tradition. Andy knew Bill and was there. There is no clear motivation to tell a fictional story when there were so many real ones.
3. The specifics line up very well with what we know about Bill Atkinson and some his wizardry needed to make the Mac work.
Given this, it’s much easier to assume that your assertion is what is made up.
For what it's worth, here's quicksort in 5 lines of haskell https://stackoverflow.com/questions/7717691/why-is-the-minim...
That's the problem with comparing lines of code: you're comparing apples and oranges. In this case you aren't even solving the same problem.
Lol - ok that's genuinely funny :). slow clap
How long would a quicksort (say, of integers) be in 68000 assembly? Maybe 20 lines? My 68000 isn't very good. The real advantage of writing it in Haskell is that it's automatically applicable to anything that's Ord, that is, ordered.
About 70 lines, once you strip out the comments and blank lines.
https://github.com/historicalsource/supermario/blob/9dd3c4be...
I'm trying to code up a version in ARM assembly to compare, and it looks like it'll be about 30 lines; when I get that working I can compare to see why the difference. In some ways the 68000 is more expressive than ARM, like being able to reference memory directly, even twice in one instruction.
(Am I misunderstanding this, or is this the source code to Apple System 7.1? There seems to have been a mailing list about this codebase from 02018 to 02021: https://lists.ucc.gu.uwa.edu.au/pipermail/cdg5/)
More or less, yes. It only encompasses the system (i.e. not applications like the Finder) and isn't entirely complete, but it's still a great window into the world of Apple pre-OS X.
> There seems to have been a mailing list about this codebase from 02018 to 02021: https://lists.ucc.gu.uwa.edu.au/pipermail/cdg5/
This mailing list was for a set of projects which focused on taking this code dump (among other things) and making it compile, ideally to reproduce released binaries.
https://github.com/elliotnunn/cdg5
QuickDraw was a graphics library, not a sorting algorithm
They couldn't. I would go find the code that caused a bug, fix it and discover that the bug was still there. Because previous students had, rather than add a parameter to a function, would make a copy and slightly modify it.
I deleted about 3/4 of their code base (thousands of lines of Turbo Pascal) that fall.
Bonus: the customer was the Department of Energy, and the program managed nuclear material inventory. Sleep tight.
In addition to not breaking existing code, also has added benefit of boosting personal contribution metrics in eyes of management. Oh and it's really easy to revert things - all I have to do is find the latest copy and delete it. It'll work great, promise.
I'm distrustful on unit testing as I've seen too many tests written to make code coverage numbers but that don't actually test the functions they are aimed at. A non-trivial number which run the function asynchronously and then report a successful run before the function even finishes executing, meaning that even throwing errors don't fail the tests (granted, part of that is on the testing framework for letting unexpected errors ever result in a pass).
It was so long ago it feels half mythical to me.
Are you sure there's anything needing cleaning up?
If you're talking about duplicate code showing up in 50 places then your problem is not code duplication but incompetent developers not being able to maintain a project.
If instead you're talking about code with a passing resemblance showing up in 2 or 3 places then odds are you're actually looking at more maintainable code straight in the eye and you're not able to understand how that makes the project more maintainable.
The demanding / loud person can and should be ignored; as a developer, you are responsible for code quality and maintainability, not your / their manager.
For other code it's an absolute stink and i agree. But for data transforms... I've seen the alternative, a neatly abstracted in-house library of abstracted combinations of dataframe operations with different parameters and.. It's the most aesthetically pleasing unfathomable hell I've ever experienced.
So now, when munging dataframes, i will be much faster to reach for 'copy that function and modify it slightly' - maintenance headache, but at least the result is readable.
Are you sure it's code duplication?
I mean, read your own description: the new function does not need to support edge cases. Having to handle edge cases is a huge code smell, and a clear sign of premature generalization.
And you even admit the guy was more productive and added less bugs?
There is a reason why the mistakes caused by naive approaches to Don't Repeat Yourself (DRY) are corrected with Write Everything Twice (WET).
They just aren’t making changes to the shared function, so they don’t need to test existing functionality still works, just their single use case.
Source code for each portal was stored in a separate Git repository. I've asked the original authors how am I supposed to fix bugs that affect all the portals or develop new functionality for all the portals. The answer was to backport all fixes manually to all copies of the source code.
Then I've asked: isn't it possible to use a single source repository and use feature flags to customize appearance and features of each portals. Original authors said that it is impossible.
In 2-3 months I've merged the code of 4-5 portals into one repository, added feature flags, upgraded the framework version, release went flawlessly, and it was possible to fix a bug simultaneously for all the portals or develop a new functionality available across all the countries where the company operated. It was a huge relief for me as copying bugfixes manually was tedious and error-prone process.
These are my favorite (in a sense) programmer stories--that there's these incomprehensible piles of rubbish that somehow, like, run The World and things, and yet somehow things manage to work (in an outwardly observable sense).
Although, I recall two somewhat recent stories where this wasn't the case. The unemployment benefits fiascos during early Covid-era, and some more recent air traffic control-related things (one which effected me personally).
There were three performance optimizations in total, one which I rejected because the gain was minimal for typical use case and there are still some memory allocation optimization which I have deferred with because I'm in the middle of a major refactor of the code. The LLM has already written down plans to restart this process later when I more time.
Negative 2000 Lines of Code (1982) - https://news.ycombinator.com/item?id=33483165 - Nov 2022 (167 comments)
-2000 Lines of Code - https://news.ycombinator.com/item?id=26387179 - March 2021 (256 comments)
-2000 Lines of Code - https://news.ycombinator.com/item?id=10734815 - Dec 2015 (131 comments)
-2000 lines of code - https://news.ycombinator.com/item?id=7516671 - April 2014 (139 comments)
-2000 Lines Of Code - https://news.ycombinator.com/item?id=4040082 - May 2012 (34 comments)
-2000 lines of code - https://news.ycombinator.com/item?id=1545452 - July 2010 (50 comments)
-2000 Lines Of Code - https://news.ycombinator.com/item?id=1114223 - Feb 2010 (39 comments)
-2000 Lines Of Code (metrics == bad) (1982) - https://news.ycombinator.com/item?id=1069066 - Jan 2010 (2 comments)
Note for anyone wondering: reposts are ok after a year or so (https://news.ycombinator.com/newsfaq.html).In addition to it being fun to revisit perennials sometimes (though not too often), this is also a way for newer cohorts to encounter the classics for the first time—an important function of this site!
I've told this story to every client who tried schemes to benchmark productivity by some single-axis metric. The fact that it was Atkinson demonstrates that real productivity is only benchmarkable by utility, and if you can get a truly accurate quantification for that then you're on the shortlist for a Nobel in economics.
Bill Atkinson has died - https://news.ycombinator.com/item?id=44210606 - June 7, 2025 (277 comments)
I didn't see that post, but I'm glad we're able to remember Bill through humorous anecdotes and eternally relevant lessons like this.
https://forum.cursor.com/t/cursor-yolo-deleted-everything-in...
These 5 lines are probably my favorite example.
https://jsfiddle.net/gaby_de_wilde/c8bhcatj/7/
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.
Otherwise just downvote or flag I guess, but this comment of yours just reads as an insult to a person that maybe did not put the most effort into writing their comment, but seems genuine to me at least.
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.
uncatchable, so I won't even try.
:)
no worries.
it's "you [don't] know" all the way down.
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.
Yet, you ask someone "how do you build an efficient LFU" and get blank stares (I just LOVE the memcache solution of regions and probabilistic promotion/demotion).
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.
Although that's also often an invitation for hallucinations so you have to be even more careful than usual.
I've "invented" all sorts of old patents, all sorts of algorithms, including the PID algorithm. I think it helped form a very practically useful "intuition".
But, I've noticed that some people are passionately against this type of self exploration.
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.
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.
These days it's very different, mostly large-ish distributed systems.
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.
the select-a-bunch-of-code-and-then-zap-it-with-the-Del-key is the best hardware algorithm.
Jokes aside, could I get a layman's explanation of the graph theory stuff here? Sounds pretty cool but the terminology escapes me
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.
I oversimplified the problem :). Really it was about generating an isomporhic-ish view, based on some user defined rules, of an existing graph, itself generated by a subgraph isomorphism by a query language.
Think a computer network as a graph, with various other configuration items like processes, attached drives, etc (something also known as a CMDB). Query that graph to generate a subgraph out of it. Then use rules to make that subgraph appear as a tree of layers (tree but in each layer you may have additional edges between the vertices) because trees are efficient, non-complex representation on 2d space (i.e. monitors).
However, a child node in that tree isn't necessarily connected directly to the parent node. E.g. one of the rules may be "display the sub network and the attached drives in a single layer", so now the parent node, the gateway, has both network nodes (directly connected to it) and attached drives (indirectly connected to it) as direct descendants.
Extend this to be able to connect through any descendant, direct or indirect (gateway -> network node -> disk -> config file -> config value - but put the config value on the level of the network node and build a link between them to represent the compound relationship).
Walk through the original subgraph while evaluating the rules and build a "trace back" stack to let you understand how to build each layer even in the presence of compound links while performing a single walkthrough instead of nm (original vertices rules for generation).
As I said, that was a lot of fun. I miss those days.
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.
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?
These background tasks are all database calls. That means the cpu is just waiting on the database for the majority of the call. Most modern servers can handle 10k of these calls concurrently. And you can do this off of one not so powerful CPU. Even half a cpu can handle this. Of course it depends on the CPU but you get my point.
The database is the bottleneck. The database is the thing that needs to be scaled first before you scale servers. This is the most common web application pattern. One way is providing more compute to the database (sharding is better then increasing cpu power as the bottleneck in the database is usually filesystem access not cpu power). Another way is to have a queue buffer the traffic spikes. Both of these are addressing an issue with the database first.
In most web apps. All the server does is wait for a database. The database is doing compute. You never want the server to do compute as that becomes what we call a “blocking call.” These blocking calls are the ones you offload to an external service as these calls “block” entire cpu threads. database calls do not “block” as the server will context switch to another green thread during database calls.
If you work somewhere where you’re scaling crud servers but not after scaling a central database it usually means you’re in a company that doesn’t get it and overemphasizes on “architecture” over common sense. It’s actually extremely common in lower tier small companies to have not so smart people build things like this that don’t make any sense. They aren’t thinking coherently and I’ve seen tons of people who just miss this common sense notion.
I’ll be Frank. It’s stupid and defies common sense. It’s likely you are doing this? But it’s also extremely commonplace.
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?
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?
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.
I was thinking in terms of finding all subgraph isomorphisms. But this definitely is O(N) if all you need is one solution.
But then I thought about it even further and this reduces to sliding window problem. In this case you still need to travel to each node in the window to see if there’s a match.
So it cannot be that you traverse each node once. Not if you want to find all possible subgraph isomorphisms.
Imagine a string that is a fractal of substrings:
And the other one: Right? The sliding window for rrrrrrr will be 7 in length and you need to traverse that entire window every time you move it. So by that fact alone every node is traversed at least 7 times.I couldn't believe my eyes. I was working in my own project beside this team with the list, so thankfully I was left out of the whole disaster.
A guy I knew wasn't that lucky. I saw how he suffered from this harmful list. Then I told him a story about the Danish film director Lars von Trier I recently had heard. von Trier was going to be chosen to appear in a "canon" list of important Danish artists that the goverment was responsible for. He then made a short film where he took the Danish flag (red with a white cross) and cut out the white lines and stitched it together again, forming a red communist flag. von Trier was immediately made persona non grata and removed from the "canon".
Later that day my friend approached the bugs caused/fixed list, cut out his own line, taped it together and put it on the wall again. I never forget how a PL came in the room later, stood and gazed at the list for a long time before he realized what had happened. "Did you do this?" he asked my friend. "Yes", he answered. "Why?", said the PL. "I don't want to be part of that list", he answered. The next day the list was gone.
A dear memory of successful subversion.
Simple, to the point, love it. "I'm not playing your stupid management games".
One of the early Ruby Koans, IIRC, circulated on comp.lang.ruby around 2002
My manager has it pinned on the breakroom wall.
[0]: https://thedailywtf.com/articles/The-Defect-Black-Market
[1] https://github.com/dotnet/runtime/pull/36715/files