Things nobody told me about being a software engineer
anaulin.org
anaulin.org
I don't write tests. Projects that already had tests, those tests caught a single bug in about 3.5 years of working on that code base.
Yes, 1 bug. We'd have picked it up anyway when actually testing it.
Why do you feel #1 or #16 are actually true?
Am I (and colleagues) a magic snowflake, or are tests a massive waste of time, or is it somewhere in the middle?
This is probably the key issue. You're either working by yourself or you are on small enough team projects that it's easy to recognize when you are breaking things with a change.
Tests are about rapidly detecting regressions in a programmatic way. It should not require manually testing every time you want to make a small change to the code base and if you depend on reviewers seeing that a change will break something, you are in for a world of hurt on any large project.
Every large project I've been on that has skipped tests has ended up turning into a shitshow where master is broken for days at a time and you can't even tell the cause without hours of manual testing with bisection.
I don’t agree with this at all. Here’s a counter example: Linux.
I think the real problem here is that people don’t take review seriously and/or just don’t care about the project. We build these complicated, expensive systems that do all the thinking for us, not because it’s better, but because we simply don’t care.
Having tests is better than letting sloppy developers run amok. In my experience though tests aren’t really needed on projects with a maintainer that actually gives a damn.
are you sure about that?
https://stackoverflow.com/questions/3177338/how-is-the-linux...
Within subsystems regressions sneak in all of the time that don't directly cause compile-time failures.
That said, automated tests catch a problem that would make it to production just about weekly in my experience. If you're trying to do any kind of HA/CI/CD they're really really helpful. Beyond that, isolated "unit tests" are somewhat helpful too in my experience, but only so far as they allow you to easily run your test suite (and rarely, find bugs faster).
I have a library that never had any tests until I wanted to re-architect it in a fundamental way whilst porting it from Python 2 to Python 3. Since it was a wire-protocol type of thing, the Python bytes–unicode distinction made this hard. So I wrote tests for each piece of functionality as I ported that piece. I keep the tests around nowadays even though the porting is complete, but am kind of lazy writing ones for new functionality.
Of course tests also seem really important when you're accepting 3rd party contributions to your codebase. I've made what I thought were totally innocuous pull requests to projects only to see in the CI tests that my code causes regressions.
1. During development: you code something, run it, see something fail and fix it. Most people don't consider this part of QA because it's coding/debugging.
2. Code review: a teammate reads your code and catches a bug or an opportunity for a bug to arise.
3. Manual QA: a teammate tries the new feature, finds a defect and reports it.
4. Production: a user reports the error.
5. Monitoring: tools like Sentry may warn you before a user reports the issue.
With your experience, you probably have learned to avoid patterns in your code that make #1 occur often. Maybe you use static typing, linters, an IDE or some other tools to help you avoid silly mistakes.
If you perform code review (#2), then you help less-experienced teammates avoid mistakes even if they haven't learned to avoid error-prone patterns or don't use tooling like you do. They spend more time in #1 than you do.
If you care (above average for developer standards) about your job, you probably manually test the software you make to see how your users experience your creation (#3) before checking-in code, while code-reviewing, and/or afterwards to help testers. This takes time and if you find mistakes, that means other teammates that did this before you invested time also.
If your company releases progressively (using feature flags) you get info from users (#4) and fix before it's considered an issue. Also, if using monitoring tools (#5) you may avoid users ever noticing there was an issue. These all lead to rework and are risky.
I don't have enough information about what process you follow, so I tried making references to generic practices. In theory, writing tests first reduces the amount of time reacting in situations 1-5. I have felt the benefits in my own team and seen them when coaching other teams.
If none of what I have written applies to you and your team, please let me know. Would love to buy you all a meal to hear about what you do to avoid defects in your software. I'm not being snarky here. Have genuinely been asking myself how do these developers I read about online manage to ship bug-free software really fast without writing tests.
Also a significant majority of my code has been statically typed as you say and I'm moving even more over to static typing now I'm using TS over JS in all new code.
If you're working on a large team with a large suite of applications, this isn't the case. Very often I'll need to make changes to code that I don't explicitly own, or that I've never seen before today. If this code doesn't have tests, this is a recipe for disaster. I don't really understand what this code is supposed to do. How do I know that my change didn't break any existing functionality? Is it obvious how or even possible to test the functionality in this file manually? Maybe it's a background job that processes a file off of an SFTP server, how long will it take me to set up a manual test for that?
It's also about iteration time. Automated tests allow to you check the correctness of every single change nearly instantaneously. I don't want to need switch to a browser and wait for a form to submit just to check that my code still works after a minor refactor, or to ensure that my typo was fixed successfully. Tests mean that code is much more likely to be refactored often, and will lead to much cleaner and easier to maintain codebases.
Unit tests wouldn't catch the examples you gave:
> How do I know that my change didn't break any existing functionality?
You don't. And with many unit tests ... you still don't. A software engineer with a few years experience will know this.
> Maybe it's a background job that processes a file off of an SFTP server, how long will it take me to set up a manual test for that?
This especially, no unit test is ever going to catch. This behavior would depend on so many things: encryption, networking, scheduling, starvation, graceful error handling, retry logic ... Not something any amount of unit tests could reasonably verify.
So this must be an argument against unit tests ? And yet, I don't think so.
In practice, you see the opposite. These arguments are designed to force people to write unit tests, and actually used against integration tests (which are complex tests that require tweaking in intelligent ways every time you make a serious change). Of course integration tests and "instantaneous" are usually opposites.
So I don't understand this argument. It only makes sense on the surface. It does not actually work on real large code projects. So I don't understand that you make this argument.
And I especially do not understand that nearly every large company follows advice like this. I mean, I can come up with cynical reasons: "more pointless work with zero verifiable results, but nice "quantifiable" (if meaningless) numbers ! Of course we're in favor !". But really, I cannot come up with a coherent to explain the behavior seen in developers in a large company.
Most statistics about unit tests make no sense. Coverage for instance, says nothing about how many edge cases you handle. Says nothing about many guarantees (like bounded and reasonable allocation for "weird" inputs, same with cpu usage, that it still works together with the OS and other daemons on the system it'll be installed on, ...). Since tests have no "real" purpose for software (they're code that doesn't run) number of tests is meaningless too. Number of lines of test code ... that's beyond useless.
The bigger a piece of software, the more useless unit tests become and the more critical realistic integration tests become ... and the less likely you are to actually find them.
And frankly, for small pieces of code, I find that specialized ways to "test" them that provide actual guarantees of correctness (like Coq) actually work. Unit tests ... never catch edge cases, not even with the best of developers. Of course, even Coq sort-of only makes sure you KNOW about every edge case and requires you to verify it's correctness before letting you pass, so bugs in your understanding of the problem will still be bugs.
But at least you have a theoretical guarantee that a developer actually thought about every edge case. Also, it's pretty hard to use. The language could be clearer, but that's not really the problem. The problem is that Coq WILL show you that no matter how well you think you understand a problem, your understanding is not complete. Often in surprising, interesting ways.
A unit test for the processor would mock out all of the SFTP fetching, or move that to a different class, and focus on only the core business logic of processing the file. The core logic could easily be unit tested, and changes could be made to the file processor without needing to replicate the entire SFTP environment in order to determine if there were regressions in the core business logic.
The alternative is needing to spin up a test SFTP environment, or somehow do that mocking in my manual test, just in order to do something as simple as refactor the class or make a small business logic change. A unit test empowers any developer to make those changes, without needing much knowledge of the environment the code runs in.
Jep. And then it doesn't actually work. Because it tries to read every file at the same time. Because the strings it passes in to resolve the server don't work. Because it never schedules the thread reading from the socket. Because it uses a 100 byte buffer (plenty for tests, after all). Because ...
And even then, what you're describing is not a unit test. A unit tests tests a single unit of code. Just 1 function, nothing more, and mocks out everything else.
So you can never test a refactor of code with a unit test. Because a refactor changes how different pieces of code work together, and unit tests by definition explicitly DON'T test that (all interactions should be mocked out). So a unit test would be useless.
And you can totally use unit tests for what I'm describing. Two classes
- SFTPHandler. Connects via SFTP, downloads latest files off the server, passes contents as a string to the processor class `FileProcessor.process(downloaded_file)`
- FileProcessor. Has one public function, process, which processes the file - doing whatever it needs to. This function can then very easily be unit tested, just passing strings for test files into the function. You can also refactor the `process` function as much as you like, not needing to worry about the SFTP connection at all. The `process` function probably calls a bunch of private functions within that class, but your unit tests don't need to worry about that.
I've used a setup like this in production, it works just fine, and allowed us to improve the performance of the file processing logic and make changes to it very easily and often - without worrying about regressions to the core business logic.
Now in the example given, performance does not matter, so I do wonder why you'd mention it at all.
How about you just answer me this question: Did you still see significant bug volumes after implementing the unit tests for the FileProcessor ?
Obviously I believe the answer to be "yes". I feel like your statement that changes were made "very easily and often" sort of implies that yes, there were many bugs.
Note that testing based on past bugs is not called unit testing. That is, as you might guess, regression testing (and has the important distinction that it's a VERY good practice to go back through your regression tests once a year, and throw out the ones that don't make sense anymore, which should be about half of them)
Besides, I've very rarely seen tests actually catch bugs. Bugs come from pieces of code not doing what developers expect them to do in 2 ways :
1) outright lack of understanding what the code does (this can also mean that they understand the code, but not the problem it's trying to solve, and so code and tests ... are simply both wrong)
2) lack of consideration for edge cases
3) lack of consideration for the environment the code runs in (e.g. scaling issues. Optimizing business logic that processes a 10M file then executing it on 50G of data)
None of these has a good chance of getting caught by unit tests in my experience.
But developers seem to mostly hate integration tests. Tests that start up the whole system, or even multiple copies of it, and then rapidly run past input through the whole system. When it fails, it takes a while to find why it fails. It may fail, despite all components, potentially written by different people, being "correctly written" just not taking each other into account. It may fail because of memory, cpu starvation, filesystem setup. It may fail occassionally because the backend database decided to VACUUM, and the app is not backing off. It may fail after a firmware upgrade on equipment it uses.
The problem I have with these "issues" is simple: they represent reality. They will occur in production.
And in some ways I feel like this is a fair description: unit tests are about "proving you're right", even, and perhaps especially, if you're wrong. "You see, it isn't my code ! Not my fault !".
> How about you just answer me this question: Did you still see significant bug volumes after implementing the unit tests for the FileProcessor ?
Kinda tricky to answer this, since there were test for this class from the start. But, overall the answer is "no" - we did not see significant bugs in that class. Occasionally we'd get a bug because the SFTP connection failed, or execution took to long and the connection closed - the type of bug that to you seems to negate the value of uniting testing the FileProcessor. But, without the unit tests for the FileProcessor, I'd have those bugs plus more bugs/bad behavior in the business logic. How is that better, exactly?
The idea that tests reduce performance is ridiculous. Improving performance requires making changes to a system while ensuring it's behavior hasn't changed. This is exactly what testing provides. Without tests, you can't optimize the code at all without fear of introducing regressions.
Nope. My argument is twofold:
1) unit tests don't actually provide the guarantees that people keep putting forward as reasons to write them
2) this makes them a dangerous, as they provide "reassurance" that isn't actually backed by reality
> But, without the unit tests for the FileProcessor, I'd have those bugs plus more bugs/bad behavior in the business logic. How is that better, exactly?
So the tests failed to catch problems with the program's behavior. Maybe it's just me, but I call that a problem.
Testing the business logic as a whole is not a unit test, except in the marginal cases where all your business logic fits neatly in a single function, or at least a single class. If it's actually a few algorithms, a few files, a bunch of functions and you test everything together, that's an integration test and not a functional test.
If you use actual (or slightly changed) data to test that business logic, as opposed to artificially crafted data, that again makes it not a unit test.
> The idea that tests reduce performance is ridiculous
If you use tests to optimize code you're optimizing a piece of code in isolation, without taking the rest of the system into account. That works for trivially simple initial optimization, but falls completely on it's face when you're actually writing programs that stress the system.
> Improving performance requires making changes to a system while ensuring it's behavior hasn't changed.
The system as a whole, sort of. Individual units ? Absolutely not.
Besides, tests merely provide FALSE assurance behavior hasn't changed. Time and time again I've had to fix "I've optimized it" bugs. TLDR is always the same. Unit tests pass so the code "must be right" (meaning they don't run the code outside of unit tests, and the unit tests only directly test the code, not blackbox). Then in the actual run edge cases were hit.
And "edge cases" makes it sound like you hardly ever hit this. Just yesterday we had a big issue. What happened ? Well we had a method that disables an inbound phone line (e.g. for maintenance, or changes). All unit tests passed. Unfortunately we really should have tested that it does NOT disable anything else (method was essentially "go through list, if it matches, disable". Needless to say, it disabled every line). Regression testing added.
We had someone optimize the dial plan handling. He didn't realize that his "cache" was in fact recreated at the very beginning of every request, when the code evaluated a dial plan, in other words, it was a serious performance regression rather than an improvement. Really looked like an improvement though. Unit tests ... passed. Of course, "the behavior hadn't changed". About 2 calls got through for ~6 minutes (normally thousands). Now we have a test that turns up the whole system, with the actual production dial plan, and then goes through 10000 calls. If it takes more than 1 minute, test fails. Developers hate it, but it's non-negotiable at this point.
I can go on for quite a while enumerating problems like this. Billing files erased (forgot to append). Entire dialplan erased on startup (essentially same problem). Lots of ways to trigger cpu starvation. Memory exhaustion. Memory leaks (the system is mostly Java). Connecting unrelated calls together (that was pretty fun for the first 2-3 minutes). Ignoring manager signals (one server having to do all calls ... which is not happening)
This is a repeating pattern in our failures. Unit tests ... essentially always pass. And time and time again someone tries to make the point that this must mean the code is correct.
And that's bullshit. That's the problem.
What do you propose instead of testing? Manually QA every single piece of the system for every change? Not a lot of companies have the headcount for a the fleet of QA people that would require.
I'm inclined to believe that some of the exhaustive unit testing culture can provide a false sense of security, and the work involved to write them can get in the way of writing proper integration tests (or 'degrees of' if you see it as a spectrum).
Provided that proper test coverage includes both integration tests and unit tests, it probably won't hurt to do both. I like unit tests as part of my process (the red-green TDD process can be quite addictive and useful), but under pressure I'd prioritize integration tests, knowing that the more time I spend unit testing, the less I'll spend integration testing.
If the project is small, fits in one skull, and not critical enough to be maintained/redesigned for years on end tests buy you less.
Also, technology can prevent some classes of problems, such as type checkers, linters, etc. One hopes you are at least using these.
#1 gives the impression the author is using a dynamic "scripting" language, which may require a higher ratio of tests per line as a project matures.
Why not automate the tests you often run?
- complex code that will change with definable inputs/outputs that won't
- large projects
I've found they're not nearly as helpful in
- small projects
- UI intensive code
- code where the requirements are ill defined and change often
Tests are definitely a massive waste of time if you never need them. Write and forget code exists and can certainly run happily for years. On the other hand, frequently changing something in a large existing codebase, especially without static typing, is almost certainly going to end up more expensive without automated tests.
If the testing advocates are using something with even a basic compiler/type-system (e.g. Java), then IME it often comes down to not being fluent with the design patterns, tricks, IDE shortcuts/plugins, tools, etc. that compilers and type-systems can provide to work with you to catch bugs at build time. I mention Java because it's a language that allows you to keep writing "dynamic" code and avoid the compiler/type-system to a good degree if you want (and boy do people want to). E.g. passing top-level Object types around and casting, using HashMaps instead of a proper Class, heavy reflection use, "stringly" typing, etc. Unlike say Haskell or Rust which force correctness down your throat to a much higher degree.
Obviously no matter the language choice, their comes a point where automated testing becomes cost-effective (e.g. safety-critical software). At that point however there should be formal methods and such in play also. And I'd say for the majority of us working on CRUD apps, we're not at that cost-effectiveness point.
What you want is E2E tests: test that your product conforms to its specifications. Automate the test procedure your testers have.
I usually focus on end-to-end tests: when I had a new feature or do some refactoring I don't have to try things manually. I just launch my test suite go prepare some coffee and if the suite passes I'm confident in not having broken anything. Also writing new tests for new features helps thinking about the edge-cases you'll encounter.
When someone reports a bug I reproduce it. Then I write a test reproducing the problem. And at last I correct it. Now I know 6 months or one year from now I won't have a regression and see this bug coming back. People really hate when something they reported months ago is a problem again.
I still maintain various code bases for multiple clients that are over 10 years old, at varying levels of TLOC (10k, 100k, million k).
The truth is bugs almost never come back like that. I know because of the thousands, maybe 10s of thousand, of bugs I've fixed over the years.
Whether that matters or not (to you or your end users) is your grey ground in the middle.
It's possible you've only ever worked on things that are simple or obvious enough to not have the need for tests, and that code that never changes. Especially if that's UI code, where you're testing it manually as you write it, you may be able to live with this on small code bases.
If you have never worked in an environment where the benefit of at least some level of automated testing is not blindingly obvious, my advice to you is to stop doing the same thing over and over and find a new job.
I have absolutely no respect for your attitude or your comment. Sanctimonious zealotry like yours should have no place in our industry.
It's disgusting that you think you can tell someone they're shit or trivialize their work because you disagree with their workflow.
And in my experience projects with unit tests are far _less_ riddled with bugs, which is the whole point, no?
And I don't know understand why on earth you think I'm telling anyone they are "shit". I'd advise someone to broaden their horizons if they said they thought functional programming was worthless, or that assembly language was always pointlessly low level, or any one of a number of possible assertions that wouldn't sit well with me. That is far from "you are shit" - it's much more assuming they are not shit, but haven't had the right context yet.
Testing basic class re-use (I'm thinking about serializers, or ViewSets like in django) doesn't make much sense to me, and in fact was 100% automatised.
Those "simple" test end-up being useful when you start hitting your app with the hammer to change a lot of stuff in it. I havn't had any use for these otherwhise.
I'm questioning how true this is, especially in today's world of whiteboard interviews and open office spaces. My personal experience seems to suggest that better people skills suggest better technical skill, especially to management.
I sucked at white boarding(still do because I don't like grinding leetcode before interviews, and I usually make it known). When I first started interviewing I needed like 10 minutes to come up with palindrome solution even though I did it in school so many times. That time I also received an offer.
Now, that I think of it I my success rate is 75% and that includes a fortune 1k company. However, it is a pretty small sample size. Now, that I think of it I need to interview more.
The most common through is assuming that someone with bad social skills is genius in coding with zero grounds for it. Without seeing code or even talking with those who know his code closely, anything like that. Assumption was that that those people are better in coding because got knows why. I suspect part of it is wish to compensate, but part is stereotype.
Open offices have nothing with it, except making people with poor social skills more actively annoying. Which can cancel some of effect I guess.
People with poor people skills incidentally act similar to other people with poor people skills. People with good people skills can choose to act similar to people with poor people skills.
Does there exist any body of proof around this one? Would like to see it and add it to my corpus of knowledge
Other data points are gathered by studying success at finding internships. A recent study found a rather staggering difference - names indicating local ethnicity got a place in 1-2 letters, while some other ethnicities had to write over 20 (if memory serves).
You'll want to find studies for the country you're living in, as the parameters inevitably vary (e.g. which ethnicities to compare). I don't think the outcomes cary much, but i didn't do a comparative study on the literature.
Inline excerpts:
> The test-retest reliability (repeatability) of the Race IAT is only .42, which falls well below the psychometric standard of .80. Your score on the IAT can fluctuate significantly from one testing to the next. Hart Blanton, a psychologist at the University of Connecticut, has noted the ease with which people can decrease their racial bias score “by simply exposing people to pictures of African-Americans enjoying a picnic.”
> The validity of IAT scores has also come under scrutiny. In 2013, Frederick Oswald and his research team published a meta-analysis of 46 studies.[1] They found that IAT scores are poor predictors of actual behavior and policy preferences. They also found that IAT scores predicted behaviors and policy preferences no better than scores on simple paper-and-pencil measures of prejudice.
> Perhaps the most interesting feature of the debate concerns how to interpret IAT scores. Some social psychologists believe the IAT measures prejudice, while others believe the IAT measures our knowledge of common stereotypes.
> They then took a version of the Race IAT with Noffians and Fasites standing in for Blacks and Whites, respectively. The students showed a consistent bias against Noffians, not because they perceived Noffians as bad but because they perceived them as bad off.
>White applicants get about 50 percent more call-backs than black applicants with the same resumes; college professors are 26 percent more likely to respond to a student’s email when it is signed by Brad rather than Lamar; and physicians recommend less pain medication for black patients than white patients with the same injury.
https://www.scientificamerican.com/article/how-to-think-abou...
> Almost a third of naturalizing immigrants abandoned their first names by 1930 and acquired popular American names such as William, John or Charles. [...] Widespread name Americanization prompts the question of whether it had an impact on migrants’ economic success. Figure 1 provides a preliminary answer to this question. Name Americanization into the most popular names - e.g. the top quartile - was associated with an occupation-based earnings increase of above 10%. These gains were larger than those experienced by migrants Americanizing into less popular names - e.g. the first quartile - and even more so than those experienced by migrants who kept their original name or changed to a more distinctive name.
As to speculation on why that is, could be as simple as the fact that the brain capacity is rather limited. Handling unfamiliar letter/phoneme sequences requires more energy. As entropic creatures, we simply take the lowest energy path whenever possible.
This will happen every time you meet someone new, even when the person belongs to the same group as you.
The question is: what do you want to do about it? Is it a reasonable ask for society to suppress how it identifies you? Should you acknowledge the reality and work with it?
Different groups and communities have approached this issue in different ways: band together and support each other, organize politically, organize protests, use guilt, stay low and work hard, use another strength to gain leverage, etc. Some of these strategies and tactics will gain the community respect. Others will strengthen the stereotype - they may get what they want but will lose something else.
Also regarding presentation improving the perceived quality of work, I noticed that when I started writing my homework assignments in LaTeX in grad school (math), I started getting better grades. I don't think my actual quality of work increased, but I was able to get away with less convincing arguments.
The kind of clothes that they wear. Which is probably not the same kind of clothes.
On a more general note the book Lean In by Sheryl Sandberg is a good read if you're interested in learning about biases you (whether man or woman) might have. The book is thoroughly cited and aims to be productive rather than an attack on men and does a great job in my opinion. It points out certain things such as how certain traits are seen as positive in men and negative in women and how this manifests itself in the workplace. It definitely helped me spot things I was guilty of without even realising before
That's mutation testing and it the next big thing for tests.
However, Rule #2 is true for me. Accidentally pressing those keybindings in a textfield that does not accept them has become common.
A thousand times this. I used to be amazed by people's intelligence. Now I am amazed by their kindness.
Come again?
Even among and within large companies. Somewhat less so within, usually. But one element of that is the (US?) taboo around sharing compensation info.
And that programmers would get a reputation almost as bad as bankers ...
I think we have to stop with those things I wish i was told/nobody told me/I would told my younger self. We just decide some points are salient with experience, and I'm pretty sure the list is different after every decade in life.
After nearly three decades writing software, I'd say if that's the case, you're probably at the wrong place. With such circumstances I'd suspect a whole lot of other bad things are probably true, too.
I also can see the other side: life is often not fair, particularly in the short-run. Life constraints such as geography are real barriers for many people.
Good luck finding a job then. All companies of all sizes and locations do this.
I remember there a site I saw here HN that listed companies without whiteboard interviews. Can't think of the name.
As far as evidence for a hiring decision goes, all of the things you listed are things that can either be easily faked, are hard to verify, or require implicitly trusting another organization. How am I supposed to spend the time reading all the code on your github account and forming a judgment of your ability based on that? Even if I do that, how can I be sure that you're the one who wrote that code? How do I know that your previous employers and clients weren't all bozos or that you didn't slack off and let your teammates do all the work? Even if I call your references, they'll probably just say, "yes, this guy definitely worked here, and by HR policy I'm not allowed to say more". Even if they do say more, how am I supposed to trust them? There's not nearly enough information there to make a hiring decision.
Easy - spend the 45 minutes that you had allotted for whiteboard challenges.
> how can I be sure that you're the one who wrote that code?
You can't be, if the Github account has a single repo with a single commit. But impressive OSS has a history of commits, maybe even a community working with the applicant.
As a random example, do you really think it would be possible for someone to fake an account like this? https://github.com/pedronauck
Even if someone went through the trouble to clone someone else's repo, modify all the commit messages to re-attribute them, and modify the code and commit messages enough to make it not obvious plagiarism, do you really think they could bullshit their way through a quick conversation about the code? Spend 20 minutes digging into it, and then ask pertinent questions about decisions made in the architecture. It'll become clear if this person is the author.
It's theoretically possible that someone could put in all the work to pull off a convincing fraud, but do you really think that's likely?
> How do I know that your previous employers and clients weren't all bozos or that you didn't slack off and let your teammates do all the work?
It's true that there is no perfect signal here, but the odds of this being true are not 50/50. It's not 100% accurate, but having references and employment history is better than nothing.
---
To be clear, I don't think OSS inspection is perfect as a hiring tool - it biases towards folks with the privilege to spend their free time working on passion projects - and I'd object to it being the sole determining factor. But I think the signal is far stronger than it is from whiteboarding, where the false negative rate is super high (I doubt most competent programmers would accurately showcase their skill in this environment).
There is no perfect hiring practice, but to immediately disregard anything that has even a negligible potential for fraud feels a bit silly to me.
1. Some people are really good talkers and some people are really bad talkers, especially in an interview setting. That said, all the software companies that people usually complain about do have part of the interview process dedicated to past experience, more the more senior you are.
2. It doesn't scale. To ask really pertinent questions that can trip up a good talker you usually need someone with a lot of experience. But you also don't want them to spend all day doing interviews. You need some type of interview that more junior employees can collect signal from.
Someone who could do that might be worth hiring anyway.
If you specifically wanted to hire people who were skilled at dishonesty. Dishonesty seems like a disqualifier most of the time, though.
That's going to be a single-digit percentage of the entire developer community and an even smaller minority of developers who go looking for jobs.
> As a random example, do you really think it would be possible for someone to fake an account like this? https://github.com/pedronauck
No, but it would also take a lot longer than an hour for me to judge, from that Github account, whether that guy is a bozo.
> It's not 100% accurate, but having references and employment history is better than nothing.
Which is why they merit the dozen or so man-hours involved in an interview process.
> To be clear, I don't think OSS inspection is perfect as a hiring tool - it biases towards folks with the privilege to spend their free time working on passion projects - and I'd object to it being the sole determining factor.
There are even more flaws than that. Unless you only hire people who make a lot of OSS contributions, you need some other measurement. And it's fairer and more accurate to use the same measurement for everyone, so if you need some other measurement anyway, you should just use it.
Another issue is that OSS contributions are a good signal if and only if you are hiring people to do the same type of work. If you're investing in a specific open-source project and you want to hire the primary maintainer to maintain that project, fine. Otherwise, you have to rely on finding someone who has a rich OSS contribution history in the same basic stuff you're hiring them to do, which is really hard when e.g. most OSS is on the platform level and you're developing products, or if you want to hire generalists rather than specialists.