Bjarne Stroustrup: C++

Bjarne Stroustrup is the creator of C++, a programming language that after 40 years is still one of the most popular and powerful languages in the world. Its focus on fast, stable, robust code underlies many of the biggest systems in the world that we have come to rely on as a society. If you’re watching this on YouTube, many of the critical back-end component of YouTube are written in C++. Same goes for Google, Facebook, Amazon, Twitter, most Microsoft applications, Adobe applications, most database systems, and most physical systems that operate in the real-world like cars, robots, rockets that launch us into space and one day will land us on Mars. This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter https://twitter.com/lexfridman, LinkedIn https://www.linkedin.com/in/lexfridman/, Facebook https://www.facebook.com/lexfridman, Medium https://medium.com/@lexfridman, or YouTube https://www.youtube.com/lexfridman where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts https://podcasts.apple.com/us/podcast/artificial-intelligence/id1434243584 or support it on Patreon https://www.patreon.com/lexfridman. Here’s the outline with timestamps for this episode (on some players you can click on the timestamp to jump to that point in the episode): 00:00 – Introduction 01:40 – First program 02:18 – Journey to C++ 16:45 – Learning multiple languages 23:20 – Javascript 25:08 – Efficiency and reliability in C++ 31:53 – What does good code look like? 36:45 – Static checkers 41:16 – Zero-overhead principle in C++ 50:00 – Different implementation of C++ 54:46 – Key features of C++ 1:08:02 – C++ Concepts 1:18:06 – C++ Standards Process 1:28:05 – Constructors and destructors 1:31:52 – Unified theory of programming 1:44:20 – Proudest moment

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Lex Fridman?

  The following is a conversation with Bjorn Strøm. He's the creator of C++ programming language that after 40 years is still one of the most popular and powerful languages in the world. Its focus on fast, stable, robust code underlies many of the biggest systems in the world that we have come to rely on as a society. If you're watching this on YouTube, for example, many of the critical backend components of YouTube are written in C++. Same goes for Google, Facebook, Amazon, Twitter, most Microsoft applications, Adobe applications, most database systems, and most physical systems that operate in the real world, like cars, robots, rockets that launch us into space and one day will land

• 0:44Lex Fridman?

  us on Mars. C++ also happens to be the language that I use more than any other in my life. I've written several hundred thousand lines of C++ source code. Of course, lines of source code don't mean much, but they do give hints of my personal journey through the world of software. I've enjoyed watching the development of C++ as a programming language, leading up to the big update in a standard in 2011 and those that followed in 14, 17, and toward the new C++ 20 standard, hopefully coming out next year. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, give it five stars on iTunes, support it on Patreon,

• 1:29Lex Fridman?

  or simply connect with me on Twitter at LexFriedman, spelled F-R-I-D-M-A-N. And now, here's my conversation with Bjorn Strøm. What was the first program you've ever written? Do you remember?

• 2:02Speaker 01

  It was my second year in university, first year of computer science. And it was in ALGOR60. I calculated the shape of a subbolips and then connected points on the perimeter, creating star patterns. It was with a wet ink on a paper printer.

• 2:28Lex Fridman?

  And that was in college, university?

• 2:30Speaker 01

  Yeah, yeah. I learned to program the second year in university.

• 2:35Lex Fridman?

  And what was the first programming language, if I may ask it this way, that you fell in love with?

• 2:43Speaker 01

  I think ALGOR60. And after that, I remember,

• 2:51Speaker 01

  I remember Snowball. I remember Fortran, didn't fall in love with that. I remember Pascal, didn't fall in love with that. It all got in the way of me. And then I discovered Assembler, and that was much more fun. And from there, I went to Micro, Microcode.

• 3:11Lex Fridman?

  So you were drawn to the, you found the low-level stuff beautiful?

• 3:18Speaker 01

  I went through a lot of languages and then I spent significant time in Assembler and Microcode. That was sort of the first really profitable things. And I paid for my masters, actually. And then I discovered Simula, which was absolutely great.

• 3:36Lex Fridman?

  Simula?

• 3:37Speaker 01

  Simula was the extension of ALGOR60, done primarily for simulation. But basically, they invented object-oriented programming at inheritance and runtime polymorphism when they were, while they were doing it. And that was the language that taught me that you could have the sort of the problems of a program grow with size of the program rather than with the square of the size of the program. That is, you can actually modularize very nicely. And that, that, that was a surprise to me.

• 4:17Speaker 01

  It was also a surprise to me that a stricter type system than Pascal's was helpful, whereas Pascal's type system got in my way all the time. So you need a, a strong type system to organize your code well, but it has to be extensible and flexible.

• 4:38Lex Fridman?

  Let's get into the details a little bit. What kind, if you remember, what kind of type system did Pascal have? What type system, typing system did Algol sixty have?

• 4:47Speaker 01

  Basically, Pascal was sort of the simplest language that Niklaus Wirth could define that served the needs of Niklaus Wirth at the time. And it, it has a sort of a highly moral tone to it. That is, if you can say it in Pascal, it's good. And if you can't, it's not so good. Whereas

• 5:14Speaker 01

  Simula allowed you basically to build your own type system. So instead of trying to fit yourself into Niklaus Wirth's world, Christ Nygor's language and Oliwan Dahl's language allowed you to build your own. So it's sort of close to the original idea of, of you, you, you build a domain-specific language. As a matter of fact, what you build is a set of types and relations among types that allows you to express something that's suitable for an application.

• 5:53Lex Fridman?

  So when you say types, stuff you're saying has echoes of object oriented programming.

• 5:59Speaker 01

  Yes, they invented it. Every language that uses the word class for type is a descendant of Simula.

• 6:09Speaker 01

  Directly or indirectly.

• 6:12Speaker 01

  Christen Nygaard and Ole Johandahl were mathematicians. And they didn't think in terms of types. But they understood sets and classes of elements. And so they called their types classes. And basically, in C++ as in Simula, classes are user-defined type.

• 6:35Lex Fridman?

  So can you try the impossible task and give a brief history of programming languages from your perspective? So we started with Algol 60, Simula, Pascal. But that's just the 60s and 70s.

• 6:50Speaker 01

  I can, I can try.

• 6:53Speaker 01

  The most sort of interesting and major improvement of programming languages was Fortran, the first Fortran. Because before that, all code was written for a specific machine. And each specific machine had a language. Assembly Language or Macro Assembly or some extension of that idea. But you're writing for a specific machine in the term, in the language of that machine. And

• 7:26Speaker 01

  Barcus and his team at IBM built a language that would allow you to, to write what you really wanted. That is, you could write it in a language that was natural for people. Now, these people happened to be engineers and physicists. So the language that came out was somewhat unusual for the rest of the world. But basically, they said formula translation because they wanted to have the mathematical formulas translated into the machine. And as a side effect, they got portability. Because now they are writing in the terms that the humans used and the way humans thought.

• 8:07Speaker 01

  And then they had a program that translated it into the machine's needs. And that was new and that was great. And it's something to, to remember. We want to raise the language to the human level, but we don't want to lose the efficiency.

• 8:26Speaker 01

  So.

• 8:27Lex Fridman?

  And that was the first step towards the human.

• 8:29Speaker 01

  That was the first step. Um, and of course, there were very particular kind of humans. Business people were different, so they got COBOL instead, et cetera, et cetera. And Simula came out, uh, no, let's not go to Simula yet. Let's go to Algor. Uh, Fortran didn't have at the time, the notions of, not a precise notion of type, not a precise notion of scope, uh, not a, um, a, a set of translation faces that was what we have today. Lexical syntax, semantics. It was sort of a bit of a model in the early days, but,

• 9:13Speaker 01

  hey, they had just done the biggest, uh, breakthrough in the history of programming, right? So you can't criticize them for not having gotten all the technical details right. So we got Algor. That was very pretty. And

• 9:29Speaker 01

  most people in commerce and science considered it useless because it was not flexible enough and it wasn't efficient enough and et cetera, et cetera. Uh, but that was a breakthrough from a technical point of view. Then Simula came along to make that idea more flexible. And you could define your own types. And that's where, where I got very interested. Christian Nugget, who's the main idea man behind, uh, Simula.

• 10:00Lex Fridman?

  That was late sixties.

• 10:02Speaker 01

  This was late sixties. Well, I was a visiting professor in, uh, OHS. And so I learned object oriented programming by sitting around and, well, in theory, discussing with, uh, with, with Christian Nugget. But.

• 10:21Speaker 01

  Mason, once you get started and in full flow, it's very hard to get a word in edgewise with.

• 10:26Lex Fridman?

  You're just listening.

• 10:27Speaker 01

  So it was great. I learned it from there.

• 10:31Lex Fridman?

  Not to romanticize the notion, but it seems like a big leap to think about object-oriented programming. It's really a leap of abstraction.

• 10:41Speaker 01

  Yes.

• 10:42Lex Fridman?

  And was that as big and beautiful of a leap as it seems from now in retrospect? Or was it an obvious one at the time?

• 10:55Speaker 01

  It was not obvious, and many people have tried to do something like that. And most people didn't come up with something as wonderful as Simula. Lots of people got their PhDs and made their careers out of forgetting about Simula or never knowing it. For me, the key idea was basically I could get my own types.

• 11:20Speaker 01

  And that's the idea that goes further into C++ where I can get better types and more flexible types and more efficient types. But it's still the fundamental idea. When I want to write a program, I want to write it with my types that is appropriate to my problem and under the constraints that I'm under with hardware, software, environment, etc. And that's the key idea. People picked up on the class hierarchies and the virtual functions and the inheritance. And that was only part of it.

• 12:00Speaker 01

  It was an interesting and major part and still a major part and a lot of graphics stuff, but it was not the most fundamental. It was when you wanted to relate one type to another, you don't want them all to be independent. The classical example is that you. Don't actually want to write a city simulation with vehicles. Where you say, well, if it's a bicycle, uh, write the code for turning a bicycle to the left. If it's a normal car, turn right the normal car way. If it's a fire engine, turn right the fire engine way, da, da, da, da, da. You get these big case statements and bunches of if statements and such.

• 12:45Speaker 01

  Instead, you, you tell the, uh, the, the base class, the, uh, that, uh, uh, that's the vehicle and saying, turn, turn left the way you want to. And this is actually a real example. They, they used it to simulate, um, and optimize the emergency, the, the emergency services for, uh, somewhere in Norway, uh, back in the sixties.

• 13:11Lex Fridman?

  Wow.

• 13:12Speaker 01

  So this was one of the early examples for why you needed inheritance and, and you needed, um, a runtime polymorphism. Because you wanted to handle this set of, um, of vehicles in a manageable way. You, you, you, you can't just rewrite your code each time a new kind of vehicle comes along.

• 13:36Lex Fridman?

  Yeah, that's a beautiful, powerful idea. And of course it stretches through your work who C++ as we'll talk about. But I think you've structured it nicely. Um, what other breakthroughs came along in the history of programming languages? If we were to tell the history in that way.

• 13:56Speaker 01

  Obviously, I'm better telling the part of the history that, that is the path I'm on as opposed to, to all the path.

• 14:03Lex Fridman?

  Yeah, you skipped the hippie, uh, John McCarthy and Lisp, one of my favorite languages.

• 14:08Speaker 01

  Um, but Lisp is, but Lisp is not one of my favorite languages. It's obviously important. It's obviously interesting. Lots of people write code in it and then they rewrite it into C or C++ when they want to go to production.

• 14:23Lex Fridman?

  Yes.

• 14:24Speaker 01

  It's in the world I'm at, which are constrained by performance, reliability, um, issues, deployability, cost of hardware. Um, I, I don't like things to be too dynamic. It is really hard to write a piece of code that's perfectly flexible.

• 14:49Speaker 01

  That you can also deploy on a small computer. And that you can also put in, say, a telephone switch in Bogota. What's the chance? If you get an error and you find yourself in the debugger that the telephone switch in Bogota on late Sunday night has a programmer around.

• 15:08Lex Fridman?

  Right.

• 15:08Speaker 01

  The chance is zero. And so a lot of things I think most about

• 15:15Speaker 01

  can't afford that flexibility. Um, I'm quite aware that maybe seventy, eighty percent of all code are not under the kind of constraints I'm interested in. But somebody has to do the, the, the job I'm doing. Uh, because you have to get from these high level flexible languages to the hardware.

• 15:39Lex Fridman?

  The stuff that lasts for ten, twenty, thirty years is robust.

• 15:43Speaker 01

  Yeah.

• 15:44Lex Fridman?

  Operates under very constrained conditions. Yes, absolutely.

• 15:47Speaker 01

  That's right.

• 15:48Lex Fridman?

  And it's fascinating and beautiful in its own way. It's C++ is uh, one of my favorite languages. And so is Lisp. So I can, I can embody too for different reasons.

• 16:00Speaker 01

  Yeah.

• 16:00Lex Fridman?

  Uh, as a, as a programmer.

• 16:04Speaker 01

  I, I understand why Lisp is popular and I can see uh, the beauty of the ideas. And similarly with um, with Smalltalk. It's just not as relative. Thank, it is not as relevant in my world. And by the way, I distinguish between those and the functional languages. Where I go to things like ML and Haskell. Uh, different, different kind of languages. Uh, they have a different kind of beauty and they're very interesting. And I actually try to learn from all the languages I encounter. To see what is there that would make

• 16:46Speaker 01

  working on the kind of problems I'm interested in with the kind of constraints um, that, that I'm interested in. What, what can actually be done better? Because we can surely do better than we do today.

• 17:02Lex Fridman?

  You've you've said that it's good for any professional programmer to know at least five languages, speaking about a variety of languages that you've taken inspiration from. And you've listed yours as being, at least at the time, C++, obviously, Java, Python, Ruby, and JavaScript. Can you, first of all, update that list, modify it? You don't have to be constrained to just five, but can you describe what you picked up also from each of these languages? How you see them as inspirations for even when you're working with C++?

• 17:42Speaker 01

  This is a very hard question to answer. So about languages, you should know languages. I reckon I knew about 25 or thereabouts when I did C++. It was easier in those days because the languages were smaller and you didn't have to learn a whole programming environment and such to do it. You could learn a language quite easily. And it's good to learn so many languages.

• 18:13Lex Fridman?

  I imagine, just like with natural language for communication, there's different paradigms that emerge in all of them.

• 18:22Speaker 01

  Yeah.

• 18:23Lex Fridman?

  That there's commonalities and so on.

• 18:25Speaker 01

  So I picked five out of a hat.

• 18:28Lex Fridman?

  You picked five out of a hat.

• 18:29Speaker 01

  Obviously.

• 18:30Lex Fridman?

  Let's forget language.

• 18:31Speaker 01

  The important thing that the number is not one.

• 18:33Lex Fridman?

  That's right.

• 18:35Speaker 01

  It's like, I don't like, I mean, if you're a monoglot, you are likely to think that your own culture is the only one's, period, for everybody else's. A good learning of a foreign language and a foreign culture is important. It helps you think and be a better person. With programming languages, you become a better programmer, better designer with a second language. Now, once you've got two, the wait to five is not that long. It's the second one that's most important. And then, when I had to pick five, I sort of thinking what kinds of languages are there? Well, there's the really low level stuff.

• 19:18Speaker 01

  It's good, it's actually good to know machine code.

• 19:21Lex Fridman?

  Even still? Sorry, Tim.

• 19:23Speaker 01

  Even today.

• 19:24Lex Fridman?

  Even today.

• 19:26Speaker 01

  The C++ optimizers write better machine code than I do.

• 19:30Lex Fridman?

  Yes.

• 19:31Speaker 01

  But I don't think I could appreciate them if I actually didn't understand uh machine code and machine architecture. At least in in in my position, I have to understand a bit of it. Because you mess up the cache and you're off in performance by a factor of a hundred. Right? It shouldn't be that if you are interested in either performance or the size of the computer you have to deploy. Uh so so I would go S is simpler. Uh I used to mention C, but these days going low level is not actually what gives you the performance. It is to express your ideas so cleanly

• 20:13Speaker 01

  that you can think about it and the optimizer can understand what you're up to. My favorite way of optimizing these days is to throw out the clever bits and see if it still runs fast. And sometimes it runs faster. Um so I need the abstraction mechanisms or something like C++ to write compact, high-performance code. Uh there was a beautiful keynote by Jason Turner at the CPPCon a couple of years ago, where he decided he was going to program uh Pong on um um Motorola sixty uh eight hundred, I think it was. And he says, well, this is relevant because it looks like a microcontroller.

• 20:59Speaker 01

  It has specialized hardware, it has not very much memory and it's relatively slow. And so he shows in real time how he writes Pong, starting with fairly straightforward, low-level stuff, improving his abstractions. And what he's doing is writing C++ and it translates into.

• 21:23Speaker 01

  Into 86 assembler, which you can do with Clang and you can see it in real time. It's the compiler explorer which you can use on the web. And then he wrote a little program that translated 86 assembler into

• 21:40Speaker 01

  Motorola assembler. And so he types and you can see this thing.

• 21:45Lex Fridman?

  In real time, wow.

• 21:46Speaker 01

  You can see it in real time. And even if you can't read the assembly code, you can just see it. His code gets better. The code, the assembler gets smaller. He increases the abstraction level, uses C++ 11 as it were better. This code gets cleaner, it gets easier maintainable. The code shrinks and it keeps shrinking. And

• 22:12Speaker 01

  I could not in any reasonable amount of time write that assembler as good as the compiler generated from really quite nice modern C++. And I'll go as far as to say the thing that looked like C was significantly uglier and smaller when it became, and larger, when it became machine code. So the abstractions that can be optimized are important.

• 22:44Lex Fridman?

  I would love to see that kind of visualization in larger code bases.

• 22:47Speaker 01

  Yeah.

• 22:48Lex Fridman?

  That might be beautiful.

• 22:49Speaker 01

  You can't show a larger code base in a one hour talk and have it fit on the screen.

• 22:55Lex Fridman?

  Right, so that's C and C++.

• 22:57Speaker 01

  So my two languages would be machine code and C++. And then I think you can learn a lot from the functional languages. So Pig, Haskell, ML, I don't care which. I think actually you learn the same lessons of expressing especially mathematical notions really clearly and having the type system that's really strict.

• 23:24Speaker 01

  And then you should probably have a language for sort of quickly churning out something. You could pick JavaScript, you could pick Python, you could pick Ruby.

• 23:37Lex Fridman?

  What do you make of JavaScript in general? So you're talking in the platonic sense about languages, about what they're good at, what their philosophy of design is. But there's also a large user base behind each of these languages and they use it in the way sometimes maybe it wasn't really designed for.

• 23:56Speaker 01

  That's right.

• 23:57Lex Fridman?

  JavaScript is used way beyond probably what it was designed for.

• 24:00Speaker 01

  Let me say it this way. When you build a tool, you do not know how it's going to be used. You try to improve the tool by looking at how it's being used and when people cut their fingers off and try and stop that from happening. But really, you have no control over how something is used. So I'm very happy and proud of some of the things C++ is being used at and some of the things I wish people wouldn't do. Bitcoin mining being my favorite example uses as much energy as Switzerland and mostly serves criminals.

• 24:37Lex Fridman?

  Yeah.

• 24:38Speaker 01

  But back to the languages, I actually think that having JavaScript run in the browser was an enabling thing for a lot of things. Yes, you could have done it better, but people were trying to do it better and they were using sort of more principles, language designs, but they just couldn't do it right. And the non-professional programmers that write lots of that code just couldn't understand them. So it did an amazing job for what it was. It's not the prettiest language and I don't think it ever will be the prettiest language, but let's not be bigots here.

• 25:24Lex Fridman?

  So what was the origin story of C++?

• 25:29Lex Fridman?

  You basically gave a few perspectives of your inspiration of object-oriented programming. That's you had a connection with C and performance. Efficiency was an important, a thing you were drawn to.

• 25:45Speaker 01

  Efficiency and reliability.

• 25:46Lex Fridman?

  Reliability.

• 25:47Speaker 01

  You have to get both.

• 25:49Lex Fridman?

  What, what, what's reliability?

• 25:51Speaker 01

  I, I, I really want my telephone calls to get through. And I want the quality of what I am talking coming out at the other end. The other end might be in London or wherever. Um, so, and, and you don't want the system to be crashing. If you're doing a bank, you mustn't crash. It might be your, uh, your bank account that is in trouble. There's different constraints, like in games, it doesn't matter too much if there's a crash. Nobody dies and nobody gets ruined. But I, I'm interested in the combination of performance.

• 26:31Speaker 01

  Partly because of sort of speed of things being done. Part of being able to do things that is necessary to, to, to have reliability uh, of larger systems. If you spend all your time interpreting a, a simple function call, you are not going to have enough time to do proper signal processing to get the telephone calls to sound right. Either that, or you have to have 10 times as many computers and you can't afford your phone anymore. It's a ridiculous idea in the modern world because we've solved all of those problems.

• 27:12Lex Fridman?

  I mean, they keep popping up in different ways. Because we tackle bigger and bigger problems, so efficiency remains always an important aspect.

• 27:20Speaker 01

  But you have to think about efficiency, not just as speed, but as an enabler to important things. And one of the things it enables is, uh, is reliability, is dependability. You, when, when I press the pedal, uh, the brake pedal of a car, it is not actually connected directly to, to anything but a computer. That computer better work.

• 27:48Lex Fridman?

  Let's talk about reliability just a little bit. So, modern cars have ECUs, have millions of lines of code today. So, this is certainly especially true of autonomous vehicles, where some of the aspects of the control or driver assistance systems that steer the car, that keep it in the lane and so on. So, how do you think? You know, I talk to regulators, people in government, who are very nervous about testing the safety of these systems of software. Ultimately, software that makes decisions that could lead to fatalities. So, how do we test software systems like these?

• 28:30Speaker 01

  First of all, safety, like performance and like security, is a system's property. People tend to look at one part of a system at a time and saying something like, "This is secure." "That's all right. I don't need to do that." "Yeah, that piece of code is secure. I'll buy your operator."

• 28:54Lex Fridman?

  Right.

• 28:55Speaker 01

  If you want to have reliability, if you want to have performance, if you want to have security, you have to look at the whole system.

• 29:03Lex Fridman?

  I did not expect you to say that, but that's very true, yes.

• 29:07Speaker 01

  I'm dealing with one part of the system and I want my part to be really good, but I know it's not the whole system. Furthermore, making an individual part perfect

• 29:21Speaker 01

  may actually not be the best way of getting the highest degree of reliability and performance and such. There's people who say C++ is type safe, not type safe, you can break it. Sure, I can break anything that runs on a computer. I may not go through your type system.

• 29:40Speaker 01

  If I wanted to break into your computer, I'll probably try SQL injection.

• 29:45Lex Fridman?

  It's very true. If you think about safety or even reliability at a system level, especially when a human being is involved,

• 29:55Lex Fridman?

  it starts becoming hopeless pretty quickly in terms of...

• 30:01Lex Fridman?

  Uh, proving that something is safe to a certain level.

• 30:06Speaker 01

  Yeah.

• 30:06Lex Fridman?

  Cause there's so many variables, it's so complex.

• 30:09Speaker 01

  Well, let's get back to something we can talk about. And, and actually make some progress on.

• 30:14Lex Fridman?

  Yes.

• 30:15Speaker 01

  Uh, we, we can look at C++ programs and we can try and make sure they, um, crash this often. The way you do that is largely by simplification. It is not, the first step is to simplify the code, have less code, have code that are less likely to go wrong. It's not by runtime testing everything. It is not by, um, big test frameworks that you're using. Yes, we do that also. But the first step is actually to make sure that when you want to express something,

• 30:53Speaker 01

  you can express it directly in code rather than going through endless loops and convolutions in your head before it gets down the code. That if, if, if the way you're thinking about a problem is not in the code, there is a missing piece that's just in your head. And the code, you can see what it does, but it cannot see what you thought about it unless you have expressed things directly. When you express things directly, you can maintain it. It's easier to find errors, it's easier to make modifications, it's actually easier to test it. And low and behold, it runs faster.

• 31:38Speaker 01

  And therefore you can use a, a smaller number of computers, which means there's less hardware that could possibly break.

• 31:47Speaker 01

  So I think the key here is simplification. But it has to be, um, to use the Einstein quote, as simple as possible and no simpler.

• 31:56Lex Fridman?

  Not simpler.

• 31:58Speaker 01

  There are other areas with under constraints where you can be simpler than you can be in C++. But in the domain I'm dealing with, that's the simplification I'm after.

• 32:10Lex Fridman?

  So how do you inspire or ensure that the Einstein level of simplification is reached? So can you do code review? Can you look at code? Is there? If I gave you the code for the Ford F-150 and said, "Here," is this a mess or is this okay? Is it possible to tell? Is it possible to regulate?

• 32:40Speaker 01

  An experienced developer can look at code and see if it smells. I mixed metaphors deliberately.

• 32:48Lex Fridman?

  Yes.

• 32:50Speaker 01

  The point is that

• 32:54Speaker 01

  it is hard to generate something that is really obviously clean and can be appreciated. But you can usually recognize when you haven't reached that point. And so if I, I've never looked at the F-150 code, so I wouldn't know. But I know what I ought to be looking for. I'll be looking for some tricks that correlates with bugs and elsewhere. And I have tried to formulate rules for what good code looks like.

• 33:36Speaker 01

  And the current version of that is called the C++ Core Guidelines.

• 33:44Speaker 01

  One thing people should remember is there's what you can do in a language and what you should do. In a language, you have lots of things that is necessary in some contexts, but not in others. There's things that exist just because there's 30-year-old code out there and you can't get rid of it. But you can't have rules that says, "When you create it, try and follow these rules."

• 34:11Speaker 01

  This does not create good programs by themselves, but it limits the damage and for mistakes, it limits the possibilities of mistakes. And basically, we are trying to say, what is it that a good programmer does? At the fairly simple level of where you use the language and how you use it. Now, I can make all the rules for Chisling and Marble. It doesn't mean that somebody who follows all of those rules can do a masterpiece by Michelangelo.

• 34:48Speaker 01

  That is, there's something else to write a good program. Just is there something else to create an important work of art? That is, there's some kind of inspiration, understanding, gift. But we can approach the sort of technical, the craftsmanship level of it.

• 35:16Speaker 01

  The famous painters, the famous sculptures, was among other things superb craftsmen. They could express their ideas using their tools very well. And so, these days, I think, what I'm doing, what a lot of people are doing, we are still trying to figure out how it is to use our tools very well. For a really good piece of code,

• 35:45Speaker 01

  you need a spark of inspiration, and you can't, I think, regulate that. You cannot say that I'll take a picture only, I'll buy your picture only if you're at least Van Gogh.

• 36:01Speaker 01

  There are other things you can regulate, but not the inspiration.

• 36:07Lex Fridman?

  I think that's quite beautifully put. It is true that there is, as an experienced programmer, when you see code that's inspired, that's like Michelangelo, you know it when you see it. And the opposite of that is code that is messy, code that smells, you know when you see it. And I'm not sure you can describe it in words, except vaguely through guidelines and so on.

• 36:37Speaker 01

  Yes. It's easier to recognize ugly than to recognize beauty in code. And for the reason is that sometimes beauty comes from something that's innovative and unusual. And you have to sometimes think reasonably hard to appreciate that. On the other hand, the messes have things in common. And you can, you can have static checkers and dynamic checkers that finds a large number of the most common mistakes. You can catch a lot of sloppiness mechanically.

• 37:19Speaker 01

  I'm a great fan of static analysis in particular, because you can check for not just the language rules, but for the usage of language rules. And I think we will see much more static analysis in the coming decade.

• 37:35Lex Fridman?

  Can you describe what static analysis is?

• 37:37Speaker 01

  You represent a piece of code so that you can write a program that goes over that representation and look for things that are right and not right. So for instance, you can analyze a program to see if resources are leaked. That's one of my favorite problems. It's not actually all that hard in modern C++ but you can do it. If you are writing in the C level, you have to have a malloc and a free, and they have to match.

• 38:21Speaker 01

  If you have them in a single function... You can usually do it very easily if there's a um malloc here, there should be a free there. On the other hand, in-between can be showing complete code and then it becomes impossible.

• 38:36Lex Fridman?

  Yeah.

• 38:36Speaker 01

  If you pass that pointer to the memory out of a function and then want to make sure that the free is done somewhere else. Now it gets really difficult. And so for static analysis, you can run through a program and you can try and figure out if there's any leaks. And what you will probably find is that you will find some leaks and you'll find quite a few places where your analysis can't be complete. It might depend on runtime, it might depend on um the cleverness of your analyzer.

• 39:19Speaker 01

  And it might take a long time, some of these programs run for a long time. But if you combine such analysis with a set of rules that says how people could use it, you can actually see why the rules are violated. And that stops you from getting into the impossible complexities. You don't want to solve the halting problem.

• 39:45Lex Fridman?

  So static analysis is looking at the code without running the code?

• 39:49Speaker 01

  Yes.

• 39:49Lex Fridman?

  And thereby it's almost

• 39:54Lex Fridman?

  not a production code, but it's almost like an educational tool of how the language should be used. It guides you, like it at its best, right? It would guide you in how you write future code as well and you learn together.

• 40:09Speaker 01

  Yes, so basically you need a set of rules for how you use the language. Then you need a static analysis that catches um your mistakes when you violate the rules or when your code ends up doing things that it shouldn't despite the rules, because there is the language rules, we can go further. And again, it's back to my idea that I would much rather find errors before I start running the code. If nothing else, once the code runs, if it catches an error at runtime, I have to have an error handler. And one of the hardest things to write in code is error handling code. Because you know something went wrong.

• 40:53Speaker 01

  Do you know really exactly what went wrong? Usually not. How can you recover when you don't know what the problem was? You can't be a hundred percent sure what the problem was in many, many cases. And this is, this is part of it. So, yes, we, we, we, we need good languages, we're good type systems. We need rules for how to use them. We need static analysis. Uh, and the ultimate for static analysis is of course program proof. But that still doesn't scale to the kind of systems we deploy. Then we start needing, uh, testing and, uh, the rest of the stuff.

• 41:32Lex Fridman?

  So C++ is an object-oriented programming language that creates, especially with its newer versions, as we'll talk about, higher and higher levels of abstraction. So how do you design? Let's even go back to the origin of C++. How do you design something with so much abstraction? That's still efficient? And is still something that you can manage? Do static analysis on, you can have constraints on, they can be reliable, all those things we've talked about. So create the, the, to me, slightly, there's a slight tension between high-level abstraction and efficiency.

• 42:18Speaker 01

  That's a good question. I could probably have a year's course, uh, just trying to answer it.

• 42:25Speaker 01

  Yes, there's a tension between efficiency and abstraction. But you also get the interesting situation that you get the best efficiency out of the best abstraction. And my main tool for efficiency for performance actually is abstraction.

• 42:45Speaker 01

  So let's go back to how C++ got there. Yeah. You said it was object-oriented programming language. I actually never said that.

• 42:54Speaker 01

  It's always quoted, but I never did. I said C++ supports object-oriented programming. But it's not. And other techniques. And that's important, because I think that the best solution to most complex, interesting problems require ideas and techniques from things that has been called object-oriented, data abstraction, functional, traditional C-style code. All of the above. And so, when I was designing C++, I soon realized I couldn't just add features.

• 43:40Speaker 01

  If you just add what looks pretty, or what people ask for, or what you think is good, one by one, you're not going to get a coherent whole. What you need is a set of guidelines that guides your decisions. Should this feature be in, or should this feature be out? How should a feature be modified before it can go in and such? And there's a, in the book I wrote about that, that's signed Evolution of C++, there's a whole bunch of rules like that. Most of them are not language-technical. They're things like, don't violate the static type system, because I liked static type

• 44:23Speaker 01

  system for the obvious reason that I like things to be reliable on reasonable amounts of hardware.

• 44:34Speaker 01

  But one of these rules is the zero overhead principle. The what kind of principle? The zero overhead principle. It basically says that if you have an abstraction, it should not cost anything compared to write the equivalent code at a lower level.

• 44:56Speaker 01

  So if I have, say, a matrix multiply, it should be written in such a way that you could not drop to the C level of abstraction and use arrays and pointers and such and run faster. And so people have written such matrix multiplications. They've actually gotten code that ran faster than Fortran because once you had the right abstraction, you can eliminate you can eliminate temporaries and you can do loop fusion and other good stuff like that. That's quite hard to do by hand and in a lower level language.

• 45:38Speaker 01

  And there's some really nice examples of that. And the key here is that that matrix multiplication, the matrix abstraction, allows you to write code that's simple and easy. You can do that in any language. But with C++, it has the features so that you can also have this thing run faster than if you hand-coded it. Now, people have given that lecture many times, I and others. And a very common question after the talk, where you have demonstrated that you can outperform Fortran for dense matrix multiplication, people come up and says, "Yeah, but that was C++. If I rewrote your code in C, how much faster would it run?"

• 46:22Speaker 01

  The answer is much slower. This happened the first time, actually back in the 80s, with a friend of mine called Doc McElroy, who demonstrated exactly this effect. And so the principle is you should give programmers the tools so that their abstractions can follow the serial word principle. Furthermore, when you put in a language feature in C++ or a standard library feature, you try to meet this. It doesn't mean it's absolutely optimal, but it means if you hand code it with the usual facilities in the language in C++ in C, you should not be able to better it.

• 47:08Speaker 01

  Usually, you can do better if you use embedded assembler for machine code for some of the details to utilize part of a computer that the compiler doesn't know about. But you should get to that point before you beat to the abstraction.

• 47:26Lex Fridman?

  So that's a beautiful ideal to reach for.

• 47:29Speaker 01

  And we meet it quite often.

• 47:31Lex Fridman?

  Quite often. So where's the magic of that coming from? There's some of it is the compilation process. So the implementations in C++, some of it is the design of the feature itself, the guidelines. So I've recently and often talked to Chris Latner, so Clang. What, just out of curiosity, is your relationship in general with the different implementations in C++ as you think about you and committee and other people in C++ think about the design of new features or design of previous features?

• 48:11Lex Fridman?

  In trying to reach the ideal of zero overhead, does the magic come from the design, the guidelines, or from the implementations?

• 48:23Speaker 01

  And.

• 48:24Lex Fridman?

  And.

• 48:24Speaker 01

  Not all. You go for programming technique, program language features, and implementation techniques. You need all three.

• 48:35Lex Fridman?

  And how can you think about all three at the same time?

• 48:40Speaker 01

  It takes some experience, it takes some practice, and sometimes you get it wrong, but after a while, you sort of get it right. I don't write compilers anymore, but.

• 48:53Speaker 01

  Brian Kernyhan pointed out that one of the reasons C++

• 48:59Speaker 01

  succeeded was some of the craftsmanship I put into the early compilers. And of course, I did the languages sign, and of course, I wrote a fair amount of code using this kind of stuff. And I think most of the successes involves progress in all three areas together. A small group of people can do that. Two, three people can can work together to do something like that. It's ideal if it's one person that has all the skills necessary. But nobody has all the skills necessary in all the fields where C++ is used. So if you want to approach my ideal in, say, concurrent programming,

• 49:43Speaker 01

  you need to know about algorithms of concurrent programming. You need to know the the trigger of lock-free programming. You need to know something about the compiler techniques. And then you have to know some of the program areas, sorry, the application areas where this is. Like some forms of graphics or some forms of, what we call,

• 50:10Speaker 01

  web server and kind of stuff. And that's very hard to get into a single head, but small groups can do it too.

• 50:17Lex Fridman?

  So is there differences in your view? Not saying which is better or so on, but differences in the different implementations of C++? Why are there several sort of maybe naive questions for me?

• 50:35Lex Fridman?

  GCC, clang, so on?

• 50:38Speaker 01

  This is a very reasonable question. When I designed C++

• 50:45Speaker 01

  Most languages had multiple implementations. Because if you want on IBM, if you run on Sun, if you want on Motorola, there was just many, many companies and they each have their own compilation structure, their own compilers. It was just fairly common that there was many of them. And I wrote C front assuming that other people would write compilers with C++ if I was successful. And furthermore, I wanted to utilize all the backend infrastructures that were available. I soon realized that my users were using 25 different linkers. I couldn't write my own linker.

• 51:29Speaker 01

  Yes, I could, but I couldn't write 25 linkers and also get any work done on the language. And so it came from a world where there was many linkers, many optimizers, many compiler frontends, not to start, but many operating systems. The whole world was not an 86 and Linux box or something. Whatever is the standard today, in the old days, they set a X. So basically, I assumed there would be lots of compilers. It was not a decision that there should be many compilers. It was just a fact, that's the way the world is.

• 52:13Speaker 01

  And yes, many compilers emerged. And today, there's at least four frontends, Clang, GCC, Microsoft, and EGG, it is Design Group. They supply a lot of the independent organizations and the embedded systems industry. And there's lots and lots of backends. We have to think about how many dozen backends there are.

• 52:48Speaker 01

  Because different machines have different things, especially in the embedded world. The machines are very different, the architectures are very different. And so having a single implementation was never an option. Now, I also happen to dislike monocultures.

• 53:10Lex Fridman?

  Monocultures?

• 53:11Speaker 01

  They are dangerous. Because whoever owns the monoculture can go stale and there's no competition and there's no incentive to innovate. There's a lot of incentive to put barriers in the way of change. Because, hey, we own the world and it's a very comfortable world for us. And who are you to to mess with that? So I really am very happy that there's four front ends for C++. Clang's great, but GCC was great, but then it got somewhat stale. Clang came along and GCC is much better now.

• 53:54Lex Fridman?

  Competition is good.

• 53:55Speaker 01

  Microsoft is much better now. So at at least a low number of front end puts a lot of pressure on

• 54:07Speaker 01

  standards compliance and also on performance and error messages and compile time speed, all this good stuff that we want.

• 54:18Lex Fridman?

  Do you think, crazy question, there might come along? Do you hope there might come along implementation of C++ written, given all of its history, written from scratch? So written today from scratch?

• 54:35Speaker 01

  Well, Clang and the LLVM is more or less written by from scratch.

• 54:41Lex Fridman?

  But there's been C++ 11, 14, 17, 20. You know, there's been a lot of.

• 54:47Speaker 01

  Sooner or later, somebody is going to try again. There has been attempts to write new C++ compilers and some of them has been used and some of them has been absorbed into others and such. Yeah, it'll happen.

• 55:02Lex Fridman?

  So what are the key features of C++? And let's use that as a way to sort of talk about the evolution of C++ the new feature. So at the highest level, what are the features that were there in the beginning? What features got added?

• 55:21Speaker 01

  Let's first get a principle or an aim in place.

• 55:27Speaker 01

  C++ is for people who want to use hardware really well and then manage the complexity of doing that through abstraction.

• 55:38Speaker 01

  And so the first facility you have is a way of manipulating the machines at a fairly low level. That looks very much like C. It has loops, it has variables, it has pointers like machine addresses. It can access memory directly. It can allocate stuff in the absolute minimum of space needed on the machine. There's a machine facing part of C++ which is roughly equivalent to C. I said C++ could beat C and it can. Doesn't mean I dislike C. If I disliked C, I wouldn't have built on it.

• 56:23Speaker 01

  Furthermore, after Dennis Ritchie, I'm probably the major contributor to modern C. And well, I had lunch with Dennis most days for 16 years and we never had a harsh word between us. So these C versus C++ fights are for people who don't quite understand what's going on. Then the other part is the abstraction. And there the key is the class, which is a user defined type. And my idea for the class is that you should be able to build a type that's just like the built in types in the way you use them, in the way you declare them,

• 57:08Speaker 01

  in the way you get the memory. And you can do just as well. So in C++ there's an int.

• 57:16Speaker 01

  As in C, you should be able to build an abstraction, a class, which we can call capital INT, that you could use exactly like an integer and run just as fast as an integer. There's the idea right there. And of course, you probably don't want to use the INT itself, but it has happened. People have wanted integers that were range-checked so that you couldn't overflow and such, especially for very safety critical applications, like the fuel injection for a marine diesel engine for the largest ships. This is a real example, by the way. This has been done.

• 57:57Speaker 01

  They built themselves an integer that was just like integer, except that it couldn't overflow. If there was an overflow, you went into the error handling. And then you built more interesting types. You can build a matrix, which you need to do graphics, or you could build a gnome for a video game.

• 58:21Lex Fridman?

  And all of these are classes and they appear just like the built-in types.

• 58:25Speaker 01

  Exactly.

• 58:25Lex Fridman?

  In terms of efficiency and so on. So what else is there?

• 58:28Speaker 01

  And flexibility.

• 58:29Lex Fridman?

  So, I don't know. For people who are not familiar with object-oriented programming, there's inheritance. There's a hierarchy of classes. You can, just like you said, create a generic vehicle that can turn left.

• 58:45Speaker 01

  So what people found was that you don't actually... No, how do I say this? A lot of types are related. That is, the vehicles, all vehicles are related. Bicycles, cars, fire engines, tanks. They have some things in common and some things that differ. And you would like to have the common things common and having the differences specific. And when you didn't want to know about the differences, like, just turn left. You don't have to worry about it.

• 59:28Speaker 01

  That's how you get the traditional object-oriented programming coming out of C++, adopted by Smalltalk and C++ and all the other languages. The other kind of obvious similarity between types comes when you have something like a vector.

• 59:45Speaker 01

  Fortune gave us the vector as called array of doubles. But the minute you have a vector of doubles, you want a vector of double precision doubles and for short doubles for graphics and why should you have not have a vector of integers while you're added or a vector of vectors and a vector of vectors of chess pieces. Now you have a board, right? So this is you express the commonality as the idea of a vector and the variations come through parameterization. And so here we get the two fundamental ways

• 1:00:30Speaker 01

  of abstracting of having similarities of

• 1:00:36Speaker 01

  types in C++ there's the inheritance and there's a parameterization, there's the object-oriented programming and there's the generic programming.

• 1:00:45Lex Fridman?

  With the templates for the generic programming. So you you've presented it very nicely, but now you have to make all that happen and make it efficient. So generic programming with templates, there's all kinds of magic going on, especially recently that you can help catch up on. But it feels to me like you can do way more than what you just said with templates. You can start doing this kind of meta programming, this kind of.

• 1:01:15Speaker 01

  You can do meta programming also. I didn't go there in that explanation. We're trying to be very basics, but go back on to the implementation.

• 1:01:24Lex Fridman?

  Implementation.

• 1:01:25Speaker 01

  If you couldn't implement this efficiently, if you couldn't use it so that it became efficient, it has no place in C++ because it will violate the zero overhead principle. So when I had to get object-oriented programming inheritance, I took the idea of virtual functions from Simula. Virtual functions is a Simula term, class is a Simula term. If you ever use those words, say thanks to Christian Nygo and Ole Johan Dahl.

• 1:02:00Speaker 01

  And I did the simplest implementation I knew of, which was basically a jump table. So you get the virtual function table, the function goes in, does an interaction through a table and get the right function. That's how you pick the right thing there. And I thought that was trivial. It's close to optimal. And it was obvious. It turned out the simulator had a more complicated way of doing it, and therefore was slower. And it turns out that most languages have something that's a little bit more complicated, sometimes more flexible, but you pay for it. And one of the strengths of C++ was that you could actually do this object-oriented stuff.

• 1:02:44Speaker 01

  And your overhead compared to ordinary functions, there's no interactions, sort of in 5, 10, 25%. Just the core, it's down there, it's not 2. And that means you can afford to use it. Furthermore, in C++, you have the distinction between a virtual function and a non-virtual function. If you don't want any overhead, if you don't need the interaction that gives you the flexibility in object-oriented programming, just don't ask for it.

• 1:03:19Speaker 01

  So the idea is that you only use virtual functions if you actually need the flexibility. So it's not zero overhead, but it's zero overhead compared to any other way of achieving the flexibility.

• 1:03:33Speaker 01

  Now, auto parameterization.

• 1:03:37Speaker 01

  Basically, the compiler looks at

• 1:03:43Speaker 01

  the template, say the vector, and it looks at the parameter and then combines the two and generates a piece of code that is exactly as if you had written a vector of that specific type. So that's the minimal overhead. If you have many template parameters, you can actually combine code that the compiler couldn't usually see at the same time. And therefore get code that is faster than if you had handwritten the stuff. Unless you are very, very clever.

• 1:04:21Lex Fridman?

  So the thing is, parameterized code, the compiler fills stuff in during the compilation process, not during runtime.

• 1:04:31Speaker 01

  That's right. And furthermore, it gives all the information it's gotten, which is the template, the parameter, and the context of use. It combines the three and generates good code.

• 1:04:48Lex Fridman?

  But it can generate, now it's a little outside of what I'm even comfortable thinking about, but it can generate a lot of code.

• 1:04:57Speaker 01

  Yes.

• 1:04:58Lex Fridman?

  And how do you, I remember being both amazed at the power of that idea and how ugly the debugging looked.

• 1:05:10Speaker 01

  Yes, debugging can be truly horrid. Come back to this because I have a solution. Anyway, the debugging was ugly. The code generated by C++ has always been ugly because there's these inherent optimizations. A modern C++ compiler has front-end, middle-end, and back-end optimizations. Even Cfront back in eighty-three had front-end and back-end optimizations. I actually took the code, generated an internal representation, munched that implementation to generate good code. So people say, it's not a compiler that generates C.

• 1:05:54Speaker 01

  The reason it generated C was I wanted to use C's code generators that were really good at back-end optimizations. But I needed front-end optimizations, and therefore the C I generated was optimized C. The way a really good, handcrafted optimizer, human, could generate it, and it was not meant for humans. It was the output of a program, and it's much worse today. And with templates, it gets much worse still. So it's hard to, it's hard to combine simple debugging with simple, with the optimal code because the idea is to drag in information from different parts of the code

• 1:06:39Speaker 01

  to generate good code, machine code. And that's not readable. So.

• 1:06:48Speaker 01

  What people often do for debugging is they turn the optimizer off. And so you get code that when you, when, when something in your source code looks like a function call, it is a function call. When the optimizer is turned on, it may disappear, the function call, it may inline. And so one of the things you can do is you can actually get code that is smaller than the function call because you eliminate the function preamble and return. And there's just the operation there. One of the key things when I did

• 1:07:30Speaker 01

  uh templates was I wanted to make sure that if you have a, say, a sort algorithm and you give it a sorting criteria.

• 1:07:43Speaker 01

  If that sorting criteria is simply comparing things with less than, the code generated should be the less than, not a indirect function call to a comparison uh object, which is what it is in the source code. But we really want down to the single instruction. And um but anyway, turn off the optimizer and, and you can, you can debug. The first level of debugging can be done, and I always do without the optimization on. Because then I can see what's going on.

• 1:08:18Lex Fridman?

  And then there's this idea of concepts.

• 1:08:22Speaker 01

  Yes.

• 1:08:22Lex Fridman?

  That puts some. Now, I've never even, I don't know if it was ever available in any form, but it puts some constraints on the stuff you can parameterize essentially.

• 1:08:37Speaker 01

  Uh, let me try and explain.

• 1:08:38Lex Fridman?

  Yeah.

• 1:08:39Speaker 01

  Um, so, yes, it wasn't there ten years ago. We have had versions of it that actually work.

• 1:08:49Speaker 01

  For the last four, five years, it was a design by Gabby Dos Reyes, Andrew Sodden and me. We were professors and postdocs in Texas at the time. And the implementation by Andrew Sodden has been available for that time. And it is part of C++ 20. And there's a standard library that uses it. So this is becoming really, very real. It's available in Clang and GCC, GCC for a couple of years. And I believe Microsoft is soon, soon going to do it.

• 1:09:34Speaker 01

  We expect all of C++ 20 to be available, so in all the major compilers in 20. But this kind of stuff is available now. I'm just saying that because otherwise people might think I was talking about science fiction. And so what I'm going to say is concrete, you can run it today. And there's production uses of it. So the basic idea is that when you have a generic component, like a sort function, the sort function will require at least two parameters.

• 1:10:13Speaker 01

  One, a data structure with a given type and a comparison criteria. And these things are related, but obviously you can't compare things if you don't know what the type of things you compare. And so you want to be able to say, I'm going to sort something and it is to be sortable. What does it mean to be sortable? You look it up in the standard. It has to have, it has to be a sequence with a beginning and an end. There has to be random access to that sequence. And there has to be, the element types has to be comparable.

• 1:10:55Lex Fridman?

  Which means less than operator can operate on. Yes. Less than logical operator can operate.

• 1:10:59Speaker 01

  Basically, what concepts are? They're compile time predicates. They're predicates you can ask, are you a sequence? Yes, I have begin and end. Are you a random exit sequence? Yes, I have subscripting and plus.

• 1:11:18Speaker 01

  Is your element type something that has a less than? Yes, I have a less than, it's... So basically, that's the system. And so, instead of saying, "I will take a parameter of any type", it'll say, "I'll take something that's sortable", and it's well-defined. And so, we say, "Okay, you can sort with less than", "I don't want less than", "I want greater than or something I invent", so you have two parameters, the sortable thing and the comparison criteria. And the comparison criteria will say, "Well, I can..." You can write in saying, "It should operate on the element type", and it has the comparison operations.

• 1:12:02Speaker 01

  So that's simply the fundamental thing. It's compile time predicates. "Do you have the properties I need?" So it specifies the requirements of the code on the parameters that it gets. It's very similar to types, actually.

• 1:12:20Lex Fridman?

  But operating in the space of concepts.

• 1:12:24Speaker 01

  Concepts? The word "concept" was used by Alex Stefanov, who is sort of the father of generic programming in the context of C++. There's other places that use that word, but the way we call generic programming is Alex's. And he called them "concepts", because he said, "They're the sort of the fundamental concepts of an area", so they should be called "concepts". And we've had concepts all the time. If you look at the KNR book about C, C has arithmetic types and it has integral types. It says so in the book. And then it lists what they are,

• 1:13:08Speaker 01

  and they have certain properties. The difference today is that we can actually write a concept that will ask a type, "Are you an integral type? Do you have the properties necessary to be an integral type? Do you have plus, minus, divide and such?"

• 1:13:25Lex Fridman?

  So maybe the story of concepts, because I thought it might be part of C++ 11, C O X, whatever it was at the time. What was the, why didn't it, like what, we'll talk a little bit about this fascinating process of standards, because I think it's really interesting for people. It's interesting for me. But why did it take so long? What shapes the idea of concepts take? What were the challenges?

• 1:14:00Speaker 01

  Back in eighty seven or thereabouts.

• 1:14:04Lex Fridman?

  Nineteen eighty seven?

• 1:14:06Speaker 01

  Nineteen eighty seven or thereabouts. When I was designing templates, obviously, I wanted to express the notion of what is required by a template of its arguments. And so I looked at this. And basically, for templates, I wanted three properties. I wanted to be very flexible. It had to be able to express things I couldn't imagine. Because I know I can't imagine everything and I've been suffering from languages that try to constrain you to only do what the designer thought good. Didn't want to do that. Secondly, it had to run faster,

• 1:14:48Speaker 01

  as fast or faster than handwritten code. So basically, if I have a vector of T and I take a vector of char, it should run as fast as you built a vector of char yourself without parameterization. And thirdly, I wanted to be able to express the constraints of of the arguments. I had proper type checking of the interfaces. And neither I nor anybody else at the time knew how to get all three. And I thought for C++ I must have the two first. Otherwise, it's not C++.

• 1:15:31Speaker 01

  And it bothered me for another couple of decades that I couldn't solve the third one. I mean, I was the one that put function argument type checking into C. I know the value of good interfaces. I didn't invent that idea. It's very common. But I did it. And I wanted to do the same for templates, of course, and I couldn't. So it bothered me. Then we tried again, 2002, 2003. Gabby, Dresz and I started analyzing the problem, explained possible solutions. It was not a complete design. A group in University of Indiana, an old friend of mine,

• 1:16:18Speaker 01

  they started a project at Indiana. And

• 1:16:25Speaker 01

  we thought we could get a good system of concepts in another two or three years.

• 1:16:34Speaker 01

  That would have made C++ 11 to C++ 06 or 07. Well, it turned out that I think we got a lot of the fundamental ideas wrong. They were too conventional. They didn't quite fit C++ in my opinion. Didn't serve implicit conversions very well. Didn't serve mixed type arithmetic, mixed type computations very well. A lot of stuff came out of the functional

• 1:17:11Speaker 01

  community and it,

• 1:17:15Speaker 01

  that community didn't deal with multiple types in the same way as C++ does. Had more constraints on what you could express and didn't have the draconian performance requirements. And basically, we tried, we tried very hard, we had some successes. But it just in the end wasn't.

• 1:17:42Speaker 01

  Didn't compile fast enough, was too hard to use, and didn't run fast enough unless you had optimizers that was beyond the state of the art. They still are. So we had to do something else. Basically, it was the idea that a set of parameters has defined a set of operations, and you go through an interaction table, just like for virtual functions. Then you try to optimize the interaction away to get performance. And we just couldn't do all of that.

• 1:18:23Speaker 01

  But get back to the standardization. We are standardizing C++ under ISO rules, which are very open process. People come in, there's no requirements for education or experience.

• 1:18:37Lex Fridman?

  So you've started to develop C++ and there's a hope. When was the first standard established? What is that like? The ISO standard, is there a committee that you're referring to? There's a group of people. What's that like? How often do you meet? What's the discussion like?

• 1:18:56Speaker 01

  I'll try and explain that. So sometime in early 1989,

• 1:19:06Speaker 01

  two people, one from IBM, one from HP, turned up in my office and told me I would like to standardize C++.

• 1:19:17Speaker 01

  This was a new idea to me and I pointed out that it wasn't finished yet, it wasn't ready for formal standardization and such. And they say, no, Biana, you haven't gotten it. You really want to do this.

• 1:19:33Speaker 01

  Our organizations depend on C++. We cannot depend on something that's owned by another corporation that might be a competitor. Of course, we could rely on you, but you might get run over by a bus.

• 1:19:48Lex Fridman?

  Right, the old bus.

• 1:19:50Speaker 01

  We really need to get this out in the open. It has to be standardized under formal rules. And we are going to standardize it under ISO rules. And you really want to be part of it because basically, otherwise, we'll do it ourselves.

• 1:20:11Speaker 01

  And we know you can do it better. So through a combination of arm twisting and flattery.

• 1:20:21Lex Fridman?

  Carrot and steak.

• 1:20:22Speaker 01

  So in late.

• 1:20:25Speaker 01

  In late eighty nine, there was a meeting in DC at the. Actually, no, it was not ISO then, it was ANSI, the American National Standard. We're doing.

• 1:20:40Speaker 01

  We met there, we were lectured on the rules of how to do an ANSI standard. There was about twenty five of us there, which apparently was a new record for that kind of meeting. And some of the old C guys that has been standardized, C was there, so we got some expertise in. So the way this works is that it's an open process. Anybody can can sign up if they pay the minimum fee, which is just about a thousand dollars. There was less than, it's a little bit more now. And I think it's twelve hundred and eighty dollars. It's not, it's not going to kill you. And we have three meetings a year. This is fairly standard.

• 1:21:25Speaker 01

  We tried two meetings a year for a couple of years that didn't work too well. So three, three one week meetings a year. And you meet and you have technical meet, technical discussions. And then you bring proposals forward for votes. The votes are done, one person per. One vote per organization. So you can't have, say, IBM come in with ten people and dominate things. That's not allowed.

• 1:21:59Lex Fridman?

  And these are organizations that extends to the UC++.

• 1:22:03Speaker 01

  Yes.

• 1:22:04Lex Fridman?

  Because it's basically.

• 1:22:04Speaker 01

  Or individuals.

• 1:22:05Lex Fridman?

  Or individuals. I mean, it's a, it's a bunch of people in a room deciding the design of a language based on which a lot of the world's systems run.

• 1:22:17Speaker 01

  That's right. Well, I think most people would agree it's better than if I decided it. Or better than if a single organization like AGNC decides it.

• 1:22:28Lex Fridman?

  I don't know if everyone agrees to that, by the way. Bureaucracies have their critics too.

• 1:22:34Speaker 01

  Yes, they, they're that, look. Standardization is not pleasant. It's horrifying.

• 1:22:42Lex Fridman?

  It's like democracy.

• 1:22:43Speaker 01

  But we, exactly. As Churchill says, democracy is the worst way except for all the others, right? And it's, I would say, the same with formal standardization. But anyway, so we meet and we have these votes. And that determines what the standard is. Couple of years later, we extended this, so it became worldwide. We have standard organizations that are active in currently fifteen to twenty countries. And another fifteen to twenty are sort of looking and voting based on the rest of the work on it.

• 1:23:28Speaker 01

  And we meet three times a year. Next week, I'll be in Cologne, Germany, spending a week doing standardization, and we'll vote out the committee draft, or C++ twenty, which goes to the national standards committees for comments and requests for changes and improvements. Then we do that, and there's a second set of votes where hopefully everybody votes in favor. This has happened several times. The first time we finished, we started in, the first technical meeting was in nineteen ninety. The last was in ninety-eight.

• 1:24:10Speaker 01

  We voted it out, that was the standard that people used till eleven, or a little bit past eleven. And it was an international standard. All the countries voted in favor. It took longer with eleven, I'll mention why, but all the nations voted in favor.

• 1:24:31Speaker 01

  And we work on the basis of consensus. That is, we do not want something that passes sixty forty. Uh, because then we're getting get dialects and opponents and people complain too much. Uh, they all complain too much, but uh, basically it has no real effect. The the standards has been obeyed. They have been working to make it uh easier to use many compilers, many computers and all of that kind of stuff. And so the first, the the it was traditional with ISO standards to take ten years. We did the first one in eight, brilliant.

• 1:25:12Speaker 01

  Uh, and we thought we were going to do the next one in six because now we are good at it.

• 1:25:17Lex Fridman?

  Right.

• 1:25:18Speaker 01

  It took thirteen.

• 1:25:21Lex Fridman?

  Yeah, it was uh named O X.

• 1:25:23Speaker 01

  It was named O X.

• 1:25:25Lex Fridman?

  Hoping uh that you would at least get it in within the single, within the odds, the single digits.

• 1:25:29Speaker 01

  I I thought we would get, I I thought would get six, seven or eight.

• 1:25:34Lex Fridman?

  The confidence of youth.

• 1:25:36Speaker 01

  Yes, right. Well, the point is that this was sort of like a second um system effect. That is, we now knew how to do it and so we're going to do it much better and we got more ambitious.

• 1:25:47Lex Fridman?

  Ambitious.

• 1:25:48Speaker 01

  And it took longer. Furthermore, there is this tendency because it's a ten year cycle.

• 1:25:56Speaker 01

  Or eight, doesn't matter.

• 1:25:59Speaker 01

  Just before your vantage ship, somebody has a bright idea.

• 1:26:06Lex Fridman?

  Yeah.

• 1:26:06Speaker 01

  And so we really, really must get that in.

• 1:26:12Speaker 01

  We we did that successfully with the STL.

• 1:26:16Lex Fridman?

  Yeah.

• 1:26:16Speaker 01

  We got the the the standard library that gives us all the STL stuff that that. I basically, I think it saved C plus plus. It was beautiful.

• 1:26:25Lex Fridman?

  Yes.

• 1:26:25Speaker 01

  Uh, and then people tried it with other things and it didn't work so well. They got things in, but it wasn't as as dramatic and it took longer and longer and longer. So after C plus plus eleven, which was a huge improvement and uh what, basically what most people are using today. We decided never again.

• 1:26:50Speaker 01

  And so how do you avoid those slips? And the answer is that you ship more often. So that if you if you if you have a slip on a 10 year cycle, by the time you know it's a slip, there's 11 years till you get it.

• 1:27:06Lex Fridman?

  Yeah.

• 1:27:07Speaker 01

  Now with a three year cycle, there is about three, four years till you get it. Like the delay between feature freeze and shipping. So you always get one or two years more. And so we shipped 14 on time. We shipped 17 on time and we ship, we will ship 20 on time. It's it it'll happen. And furthermore, this allow, this gives a predictability that allows the implementers, the compiler implementers, the library implementers, to they have a target and they deliver on it.

• 1:27:47Speaker 01

  11 took two years before most compilers were good enough. 14, most compilers were actually getting pretty good in 14. 17, everybody shipped in 17.

• 1:28:02Lex Fridman?

  Wow.

• 1:28:03Speaker 01

  We are going to have at least almost everybody ship almost everything in 20. And I know this because they're shipping in 19. Predictability is good. Delivery on time is good. And so, yeah.

• 1:28:19Lex Fridman?

  That's great.

• 1:28:19Speaker 01

  That's how it works.

• 1:28:22Lex Fridman?

  There's a lot of features that came in in C++ 11. There's a lot of features at the birth of C++ that were amazing and ideas with concepts in 2020. What to you is the most? Just just to you personally, beautiful or?

• 1:28:45Lex Fridman?

  Just you sit back and think, wow, that's just nice and clean feature of C++.

• 1:28:53Speaker 01

  I have written two papers for the History of Programming Languages Conference, which basically asked me such questions. And I'm writing a third one, which I will deliver at the History of Programming Languages Conference in London next year. So I've been thinking about that. And there is one clear answer: constructors and destructors. The way a constructor can establish the environment for the use of a type, for an object, and the destructor that cleans up any messes at the end of it. That is the key to C++. That's why we don't have to use garbage collection. That's how we can get predictable performance.

• 1:29:38Speaker 01

  That's how you can get the minimal overhead in many, many cases and have really clean types. It's the idea of constructor-destructor pairs. Sometimes it comes out under the name RII, Resource Acquisition is Initialization, which is the idea that you grab resources in the constructor and release them in the destructor. It's also the best example of why I shouldn't be in advertising. I get the best idea, and I call it Resource Acquisition is Initialization. Not the greatest naming I've ever heard.

• 1:30:21Lex Fridman?

  So it's types, abstraction of types. You said, "I want to create my own types." So types is an essential part of C++. And making them efficient is the key part.

• 1:30:38Lex Fridman?

  And to you, the, this is almost getting philosophical, but the construction and the destruction, the creation of an instance of a type and the freeing of resources from that instance of a type is what defines the object. Is, uh, that's almost like birth and death is what defines human life.

• 1:31:03Speaker 01

  Yeah, that's right. By the way, philosophy is important. You can't do good language design without philosophy because what you are determining is what people can express and how. This is very important. By the way, constructors, destructors came into C++ in seventy nine, in about the second week of my work with what was then called C with classes. It is a fundamental idea. Next comes the fact that you need to control copying because once you control, as you said, birth and death, you have to control taking copies, which is another way of creating an object.

• 1:31:46Speaker 01

  And finally, you have to be able to move things around. So you get the move operations and that's a set of key operations you can define on a C++ type.

• 1:31:58Lex Fridman?

  And so to you, those things are just a beautiful part of C++ that is at the core of it all.

• 1:32:08Speaker 01

  Yes.

• 1:32:09Lex Fridman?

  You mentioned that you hope there will be one unified set of guidelines in the future for how to construct a programming language. So perhaps not one programming language, but a unification of how we build programming languages. If you remember such statements.

• 1:32:27Speaker 01

  I, I have some trouble remembering it, but I know the origin of that idea.

• 1:32:31Lex Fridman?

  So maybe you can talk about sort of C++ has been improving. There's been a lot of programming language. Do you, where does the arc of history taking us? Do you hope that there is a unification about the languages with which we communicate in the digital space?

• 1:32:49Speaker 01

  Well, I, I think that languages should be designed not by clobbering language features together and doing slightly different versions of somebody else's ideas, but through the creation of a set of principles, rules of thumbs, whatever you call them. I, I made them for C++ and we're trying to teach people in the standards committee about these rules because a lot of people come in and says, "I've got a great idea, let's put it in the language." And then you have to ask, "Why does it fit in the language? Why does it fit in this language?

• 1:33:32Speaker 01

  It may fit in another language and not here, or it may fit here and not the other language." So you have to work from a set of principles and you have to develop that set of principles. And

• 1:33:47Speaker 01

  one example that, that I sometimes remember is I was sitting down with some of the designers of Common Lisp. And we were talking about languages and language features and obviously we didn't agree about anything. Because, well, Lisp is not C++ and vice versa. Too many parentheses. But suddenly we started making progress.

• 1:34:17Speaker 01

  I said, "I had this problem and I developed it according to these ideas." And they said, "Why, why?" We had that problem, different problem, and we developed it with the same kind of principles. And so we worked through large chunks of C++ and large chunks of Common Lisp and figured out we actually had similar sets of principles of how to do it.

• 1:34:45Speaker 01

  But the constraints on our designs were very different. And the aims for the usage was very different. But there was commonality in the way you reason about language features and the fundamental principles you are trying to do.

• 1:35:03Lex Fridman?

  So do you think that's possible to... So there, just like there is perhaps a unified theory of physics, of the fundamental forces of physics, that I'm sure there is commonalities among the languages. But there's also people involved that help drive the development of these languages. Do you have a hope or an optimism that there will be a unification? If you think about physics and Einstein towards a simplified language, do you think that's possible?

• 1:35:41Speaker 01

  Let's remember, sort of, modern physics, I think, started with Galileo in the 1300s. So they've had 700 years to get going. Modern computing started in about 49. We've got, what is it, 70 years. They have 10 times.

• 1:36:03Lex Fridman?

  Yeah.

• 1:36:03Speaker 01

  Furthermore, they are not as bothered with people using physics the way we are worried about programming is done by humans. So each have problems and constraints the others have, but we are very immature compared to physics. So I would look at sort of the philosophical level and look for fundamental principles. Like, you don't leak resources, you shouldn't. You don't take errors at runtime that you don't need to. You've...

• 1:36:44Speaker 01

  Don't violate some kind of type system. There's many kinds of type systems, but when you have one, you don't break it. Um, et cetera, et cetera. Uh, there, there will be quite a few. And it will not be, be the same for all languages. But I think we, if we step back at some kind of philosophical level, we can, we would be able to agree on sets of principles that applied to, to, to sets of problem areas. And within

• 1:37:17Speaker 01

  an area of use, like in C++'s case, uh, what used to be called systems programming, the area between the hardware and the, the, the, the fluffier parts of the system. You, you might very well see a convergence. So these days you see Rust having a, uh, adopted RAII. And sometime accuses me for having borrowed it 20 years before they discovered it. But, um, it's, uh, uh, we, we're seeing some kind of conversion, uh, conver- convergence here. Instead of, um, relying on garbage collection all the time. The garbage collection languages are, are doing things like the, uh,

• 1:38:00Speaker 01

  uh, dispose patterns and such that imitates, uh, some of the, uh, construction destruction stuff. And they're trying not to use the garbage collection all the time and things like that. So there's, there, there, there's a conversion. But I think we have to step back to the philosophical level, agree on principles. And then we'll see some conversions, co- convergences. And it will be application domain specific.

• 1:38:29Lex Fridman?

  So a crazy question, but I work a lot with machine learning, with deep learning. I'm not sure if you touch that world much. But you, you could think of programming as a thing that takes some input. Uh, uh, programming is the task of creating a program. And a program takes some input and produces some output. So machine learning systems train on data.

• 1:38:53Lex Fridman?

  In order to be able to take an input and produce output. But they're messy, fuzzy things, much like

• 1:39:02Lex Fridman?

  we as children grow up. You know, we take some input, we make some output, but we're noisy. We mess up a lot. We're definitely not reliable. Biological system are a giant mess. So there's a sense in which machine learning is a kind of way of programming, but just fuzzy. It's very, very, very different than C++. Because C++ is a like, it's just like you said, it's extremely reliable. It's efficient. It's, you know, you can, you can measure, you can test in a bunch of different ways. With biological systems or machine learning systems, you can't say

• 1:39:43Lex Fridman?

  much, except sort of empirically saying that 99.8% of the time, it seems to work.

• 1:39:51Lex Fridman?

  What do you think about this fuzzy kind of programming? And do you even see it as programming? Is it solely, totally another kind of world?

• 1:40:00Speaker 01

  I, I think it's a different kind of world. And it is fuzzy. And in my domain, I don't like fuzziness. That is, people say things like they want everybody to be able to program. But I don't want everybody to program my my, my, my, my airplane controls or the car controls. I want that to be done by engineers. I want that to be done with people that are specifically educated and trained for doing

• 1:40:35Speaker 01

  building things. And it is not for everybody. Similarly, a language like C++ is not for everybody. It is generated to be a sharp and effective tool for professionals, basically, and definitely for people who, who, who aim at some kind of precision. You don't have people doing calculations without understanding math. Right? Counting on your fingers is not going to cut it if you want to fly to the moon. And so there are areas where

• 1:41:13Speaker 01

  An eighty-four percent accuracy rate, a sixteen percent uh false positive rate, is perfectly acceptable and where people will probably get no more than seventy. You said ninety-eight percent, I, um, what I have seen is more like eighty-four and by, by really a lot of blood, sweat and tears, you can get up to ninety-two and a half. Right. Uh, so this is fine if it is, say, pre-screening uh stuff before the human look at it. It is not uh good enough for, for life-threatening situations.

• 1:41:54Speaker 01

  And um, so there's lots of areas where, where the falseness is, is perfectly acceptable and good and better than humans, cheaper than humans. But it's not the kind of engineering stuff I'm mostly interested in. I, I worry a bit about machine learning in the context of cars. You know much more about this than I do. I worry too. But I'm, I, I'm, I'm sort of a, an amateur here. I've read some of the papers, but I've not ever done it. And the, the, the, the idea that scares me the most is the one I have heard, and I don't know how common it is, that

• 1:42:38Speaker 01

  you have this AI system, machine learning, all of these trained uh neural nets. A- and when there's something that's too complicated, they ask the human for help.

• 1:42:54Speaker 01

  But the human is reading a book or asleep and he has thirty seconds or three seconds to figure out what the problem was that the AI system couldn't handle and do the right thing. This is scary. I mean, how do you do the cutaway between the machine and the human?

• 1:43:15Lex Fridman?

  Very, very difficult. And for the designer of one of the most reliable, efficient and powerful programming languages, C++ I can understand why that world is actually unappealing. It is for most engineers. To me, it's extremely appealing because we don't know how to get that interaction right, but I think it's possible, but it's very, very hard.

• 1:43:42Speaker 01

  It is. And now is stating a problem, not a solution.

• 1:43:47Lex Fridman?

  I would much rather never rely on a human. If you're driving a nuclear reactor, if you're or an autonomous vehicle, it's much better to design systems written in C++ that never ask human for help.

• 1:44:01Speaker 01

  Let's just get one fact in.

• 1:44:04Lex Fridman?

  Yeah.

• 1:44:05Speaker 01

  All of this AI stuff is on top of C++. So that's one reason I have to keep it whether I am or what's going on in that field, but I will never become an expert in that area. But it's a good example of how you separate different areas of applications and you have to have different tools, different principles. And then they interact. No major system today is written in one language. And there are good reasons for that.

• 1:44:37Lex Fridman?

  When you look back at your life work, what is a moment, what is a event creation that you're really proud of? They say, damn, I did pretty good there. Is it as obvious as the creation of C++?

• 1:44:57Speaker 01

  It's obvious. I've spent a lot of time with C++ and it's a combination of a few good ideas, a lot of hard work and a bit of luck. And I've tried to get away from it a few times, but I get dragged in again, partly because I'm most effective in this area and partly because what I do has much more impact if I do it in the context of C++. I have four and a half million people that pick it up tomorrow if I get something right. If I did it in another field, I would have to start learning, then I have to build it and then we'll see if anybody wants to use it.

• 1:45:39Speaker 01

  One of the things that has kept me going for all of these years is, one, the good things that people do with it, and the interesting things they do with it. And also, I get to see a lot of interesting stuff and talk to a lot of interesting people.

• 1:46:00Speaker 01

  I mean, if it has just been statements on paper, on a screen, I don't think I could have kept going. But I get to see the telescopes up on Mauna Kea, and I actually went and see how Ford built cars, and I got to JPL and see how they do the Mars Rovers. There's so much cool stuff going on, and most of the cool stuff is done by pretty nice people, and sometimes in very nice places. Cambridge, Sofia, Antipolis, Silicon Valley. There's more to it than just code. But code is central.

• 1:46:45Lex Fridman?

  On top of the code are the people in very nice places. Well, I think I speak for millions of people, Yarn, in saying thank you for creating this language that so many systems are built on top of that make a better world. So, thank you, and thank you for talking today.

• 1:47:06Speaker 01

  Yeah, thanks, and we'll make it even better.

• 1:47:09Lex Fridman?

  Good.