The following is a conversation with Bjarn Strelstrom. He's a 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, 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 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 the 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, or simply connect with me on Twitter at Lex

Friedman, spelled F R I D M A N. And now here's my conversation with Bjorn Straussstroke.

What was the first program you've ever written? Do you remember?

It was my second year in university, first year of computer science and it was an Algor 60.

I calculated the shape of a super ellipse and then connected points on the perimeter,

creating star patterns. It was with a wedding on a paper printer.

And that was in college, university? Yeah. I learned to program the second year in university.

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

I think Algor 60 and after that I remember I remember Snowball. I remember Fortran didn't

fall in love with that. I remember Pascal didn't fall in love with that. It already got in the

way of me. And then I discovered Assembler and that was much more fun. And from there I went to

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

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 I paid for my masters actually.

And then I discovered Simula, which was absolutely great.

Simula? Simula was the extension of Algor 60 done primarily for simulation, but basically

they invented object oriented programming at inheritance and runtime polymorphism while

they were doing it. And that was a language that taught me that you could have the sort of the

problems of a program grow with the 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 was a surprise to me.

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 strong type system to organize your

code well, but it has to be extensible and flexible. Let's get into the details a little bit. What

if you remember what kind of type system did Pascal have? What type system typing system did Algor

60 have? Basically, Pascal was sort of the simplest language that Nicholas could define

that served the needs of Nicholas. We had at the time and 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, Simula, allowed you basically to build your own type system. So instead of trying to fit

yourself into Nicholas Vietz's world, Christen Nugol's language and Oliwann Dahl's language

allowed you to build your own. So it's sort of close to the original idea of 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.

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

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

directly or indirectly. Christen Nugol and Oliwann Dahl 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.

So can you try the impossible task and give a brief history of programming languages from

your perspective? So we started with Algal 60, Simula, Pascal, but that's just the 60s and 70s.

I can try. 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, a simply language or a core Simula or some extension

of that idea, but you are writing for a specific machine in the language of that machine.

And Barker and his team at IBM built a language that would allow you 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.

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 remember. We want to raise the language to the human level,

but we don't want to lose the efficiency. And that was the first step towards the human?

That was the first step. And of course, there were very particular kinds of humans,

business people who were different, so they got cobalt instead and et cetera, et cetera.

And Simula came out. No, let's not go to Simula yet. Let's go to Algor. Fortran didn't have,

at the time, the notions of not a precise notion of type, not a precise notion of scope,

not a set of translation phases that was what we have today, lexical, syntax, semantics. It was

sort of a bit of a model in the early days, but hey, they had just done the biggest breakthrough

in the history of programming. So you can't criticize them for not having gotten all the

technical details right. So we got Algor. That was very pretty. And 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. But that was the breakthrough from the technical point of view.

And then Simula came along to make that idea more flexible and you could define your own types. And

that's where I got very interested. Preston Nygo, who's the main idea man behind Simula.

That was late 60s.

This was late 60s. Well, I was a visiting professor in Aarhus. And so I learned object

oriented programming by sitting around and well, in theory, discussing with

Kaisen Nygo. But Kaisen, once you get started and in full flow, it's very hard to get a word in

edge ways with you just listen. So it was great. I learned it from there.

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. Yes.

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?

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. 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. It was an

interesting and major part and still a major part and a lot of graphic 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,

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, you get these big case statements and

bunches of if statements and such. Instead, you tell the base class that that's the vehicle and say,

turn left the way you want to. And this is actually a real example. They used it to simulate

and optimize the emergency services for somewhere in Norway back in the 60s.

Wow. So this was one of the early examples for why you needed inheritance and you needed

runtime polymorphism because you wanted to handle this set of vehicles in a manageable way.

You can't just rewrite your code each time a new kind of vehicle comes along.

Yeah, that's a beautiful, powerful idea. And of course, it is stretched through your work

with C++ as we'll talk about. But I think you structured nicely what other breakthroughs came

along in the history of programming languages. If we were to tell the history in that way.

Obviously, I'm better telling the part of the history that that is the part that I'm on as

opposed to all the parts. Yeah, you skipped the hippie John McCarthy and Lisb, one of my favorite

languages. But Lisb 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 CSE++ when they want to

go to production. It's in the world I'm at, which are constrained by performance, reliability,

issues, deployability, cost of hardware. I don't like things to be too dynamic.

It is really hard to write a piece of code that's perfectly flexible

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?

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

most about can't afford that flexibility. I'm quite aware that maybe 70, 80% of all code

are not under the kind of constraints I'm interested in. But somebody has to do the job I'm doing

because you have to get from these high level flexible languages to the hardware.

The stuff that lasts for 10, 20, 30 years is robust, operates under very constrained conditions.

Yes, absolutely. That's right. And it's fascinating and beautiful in its own way.

It's C++ is one of my favorite languages and so is Lisp. So I can embody it too

for different reasons as a programmer. I understand why Lisp is popular and I can see

the beauty of the ideas and similarly with Smalltalk. It's just not as relevant in my world.

And by the way, I distinguish between those in the functional languages

where I go to things like ML and Haskell. Different kind of languages. 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

working on the kind of problems I'm interested in with the kind of constraints

that I'm interested in. What can actually be done better because we can surely do better than we do

today. 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++?

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 the language quite easily and it's good to learn so many languages.

I imagine just like with natural language for communication, there's different paradigms that

emerge in all of them. That there's commonalities and so on.

So I picked five out of a hat. Obviously. The important thing that the number is not one.

That's right. 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, a better designer with the second language.

Now, once you've got two, the way 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 a really low level stuff. It's good. It's actually good to know machine code.

Even still, sorry. Even today. Even today. The C++ optimizes right better machine code than I do.

Yes. But I don't think I could appreciate them if I actually didn't understand machine code and

machine architecture. At least in my position, I have to understand a bit of it. Because

you mess up the cash and you're off in performance by a factor of 100. Right? It shouldn't be that

if you are interested in either performance or the size of the computer you have to deploy.

Yeah. So I would go, that's a simpler. 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 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. So I need the abstraction mechanisms or something like C++ to write compact high

performance code. There was a beautiful keynote by Jason Turner at the CPP Con a couple of years ago

where he decided he was going to program Pong on Motorola 6800, I think it was. And he says,

well this is relevant because it looks like a microcontroller. 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, he's writing C++ and it translates 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 Motorola assembler. And so he

types and you can see this thing in real time. 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 to maintain what the code shrinks and it keeps shrinking. And 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 that 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. I would love to see that kind of

visualization in larger code bases. That might be beautiful. But you can't show a larger code base

in a one hour talk and have it fit on screen. Right. So that's C and C++. 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 has Goliom L. I don't care which. I think actually you learn the same lessons

of expressing especially mathematical notions really clearly and having a type system that's

really strict. 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.

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. That's right. JavaScript is used way beyond probably what it was designed for.

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. 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 more principles, language designs,

but they just couldn't do it right. And the nonprofessional 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 that's not

the biggest here. So what was the origin story of C++? You basically gave a few perspectives of

your inspiration of object oriented programming. You had a connection with C in performance,

efficiency was an important thing you were drawn to. Efficiency and reliability. You have to get

both. What's reliability? 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. And you don't want the system to be crashing. If you're doing a bank,

you mustn't crash. It might be 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'm interested in the combination of performance partly because of sort of speed

of things being done, part of being able to do things that is necessary to have reliable

reliability of larger systems. If you spend all your time interpreting 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. I mean they keep popping up in different ways because we tackle bigger and

bigger problems so efficiency remains always an important aspect. 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 reliability, is dependability. When I press the brake pedal of a car, it is not actually

connected directly to anything but a computer. That computer better work.

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

aspect of the control or driver assistance systems that steer the car, keeping the lanes on.

So how do you think, you know, I talked to regulators, people in the 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?

First of all, safety, like performance and like security is a systems 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.

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

Yes. 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

may actually not be the best way of getting the highest degree of reliability and performance and

such. Those people say C++ 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. If I wanted to break into your

computer, I'll probably try SQL injection. It's very true. If you think about safety or even

reliability at a system level, especially when a human being is involved, it starts becoming

hopeless pretty quickly in terms of proving that something is safe to a certain level,

because there are so many variables. It's so complex.

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

We can look at C++ programs and we can try and make sure they crash less often.

The way you do that is largely by simplification. 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 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, you can express it directly in code rather than

going through endless loops and convolutions in your head before it gets down the code.

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, lo and behold, it runs faster. Therefore, you can use a smaller number of computers,

which means there's less hardware that could possibly break. I think the key here is simplification,

but it has to be to use the Einstein quote as simple as possible and no simpler.

Not simpler. 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.

How do you inspire or ensure that the Einstein level simplification is reached?

Can you do code review? Can you look at code? If I gave you the code for the Ford F150 and said,

here, is this a mess or is this okay? Is it possible to tell? Is it possible to regulate?

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

Yes. The point is that 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.

If I have never looked at the F150 code, so I wouldn't know, but I know what I would be looking

for. I would be looking for some tricks that correlate with bugs and elsewhere. I have tried

to formulate rules for what good code looks like. The current version of that is called the C++

core guidelines. 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 context,

but not in others. There are 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. This does not create good programs by themselves, but it limits the damage for

mistakes. It limits the possibilities of mistakes. 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 put all the rules for chiseling and marble. It doesn't mean that somebody who

follows all of those rules can do a masterpiece by Michelangelo. That is, there's something else

to write a good program. Is there something else to create important work of art? There's

some kind of inspiration, understanding, gift, but we can approach the technical, the craftsmanship

level of it. The famous painters, the famous sculptures was, among other things, superb

craftsmen. They could express their ideas using their tools very well. These days, I think what

I'm doing, what a lot of people are doing, we're still trying to figure out how it is to use our

tools very well. For a really good piece of code, you need a spark of inspiration and you

can't, I think, regulate that. You cannot say that I'll buy your picture only if you're,

at least, Van Gogh. There are other things you can regulate, but not the inspiration.

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.

The opposite of that is code that is messy, code that smells, you know when you see it.

I'm not sure you can describe it in words except vaguely through guidelines and so on.

Yes. It's easier to recognize ugly than to recognize beauty in code. 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 have static checkers and dynamic checkers that finds a large number of the

most common mistakes. You can catch a lot of sloppiness mechanically. 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. I think we will see much more static analysis in the

coming decade. Can you describe what static analysis is? 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. 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

function. They have to match. If you have them in a single function, you can usually do it very

easily. If there's a malloc here, there should be a free there. On the other hand, in between

can be showing complete code and then it becomes impossible. 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. For static analysis, you can run through a program

and you can try and figure out if there's any leaks. 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 the cleverness of your analyzer 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, such as 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 holding problem. The static analysis is looking at the code without running the code.

Not in production code, but it's almost like an education tool of how the language should be used.

It guides you at its best. It would guide you in how you write future code as well and you learn

together. Basically, you need a set of rules for how you use the language. Then you need

a static analysis that catches your mistakes when you violate the rules or when your code ends up

doing things that it shouldn't, despite the rules, because those are the language rules. We can go

further. 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. One of the hardest things to write in code is error handling code,

because you know something went wrong. 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 100%

sure what the problem was in many, many cases. This is part of it. Yes, we need good languages,

with good type systems. We need rules for how to use them. We need static analysis. The ultimate

for static analysis is course program proof, but that still doesn't scale to the kind of systems

we deploy. Then we start needing testing and the rest of the stuff. C++ is an object oriented

programming language that creates, especially with newer versions, as we'll talk about,

higher and higher levels of abstraction. Let's even go back to the origin 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,

relive all those things we've talked about. To me, there's a slight tension between

high level abstraction and efficiency. That's a good question. I could probably have a year's

course just trying to answer it. 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. My main tool for efficiency, for performance, actually is abstraction.

Let's go back to how C++ got there. You said it was object oriented programming language. I

actually never said that. It's always quoted, but I never did. I said C++ supports object oriented

programming and other techniques. That's important because I think that the best solution to most

complex interesting problems require ideas and techniques from things that have been called

object oriented, data abstraction, functional, traditional C style code, all of the above.

When I was designing C++, I soon realized I couldn't just add features.

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? In the book I wrote about that,

that's signed an evolution of C++. There's a whole bunch of rules like that. Most of them are not

language technical. There are things like don't violate static type system because I like static

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

hardware. One of these rules is 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. 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.

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 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. There's some really nice examples of that. 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. With C++, it has the features so that you can also have this thing

run faster than if you hand coded it. People have given that lecture many times, I and others,

and a very common question after the talk where you have demonstrated that you're going

to perform Fortran for dense matrix multiplication, people come up and say, yeah,

but that was C++. If I rewrote your code and see how much faster would it run, the answer is much

slower. This happened the first time actually back in the ages with a friend of mine called

Doug McElroy who demonstrated exactly this effect. The principle is you should give programmers the

tools so that the abstractions can follow the zero word principle. Furthermore, when you put in a

language feature on 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. 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 the abstraction.

That's a beautiful idea to reach for. And we meet it quite often.

Quite often. Where's the magic of that coming from? Some of it is the compilation process,

so the implementation is C++. Some of it is the design of the feature itself, the guidelines.

I've recently often talked to Chris Ladner, so Clang. 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 in trying to reach the ideal of zero overhead? Does the magic come from the

design, the guidelines, or from the implementations? And not all. You go for programming technique,

program language features, and implementation techniques. You need all three.

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

It takes some experience, 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 Brian Kernighan pointed out that

one of the reasons C++ succeeded was some of the craftsmanship I put into the early compilers.

And of course, I did the languages sign. 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 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, you need to know about algorithms on concurrent programming. You

need to know the trigger of lock free programming. You need to know something about the compiler

techniques. And then you have to know some of the application areas where this is,

like some forms of graphics or some forms of what we call a web serving kind of stuff.

And that's very hard to get into a single head. But small groups can do it too.

So is there differences in your view? Not saying which is better or so on, but difference in

the different implementations of C++? Why are there several sort of maybe naive questions for me?

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

most languages have multiple implementations. Because if you run on an IBM, if you run on a

Sun, if you run on a Motorola, there was just many, many companies and they each have their

own compilation structure, the old compilers. It was just fairly common that there was many of them.

And I wrote Cfront assuming that other people would write compilers with C++ if they were

successful. And furthermore, I wanted to utilize all the back end infrastructures that were available.

I soon realized that my users were using 25 different linkers. I couldn't write my own linker.

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 front ends,

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 said a Vax. So basically, I assumed there

would be lots of compilers. It was not a decision that there should be many compilers. It was just

the fact that's the way the world is. And yes, many compilers emerged. And today, there's

at least four front ends, Clang, GCC, Microsoft, and EDG. It is the sign group. They supply a lot

of the independent organizations and the embedded systems industry. And there's lots and lots of

back ends. We have to think about how many dozen back ends there are 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. Monocultures. 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 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. Competition is good. Microsoft is much better

now. So at least a low number of front ends puts a lot of pressure on

standards compliance and also on performance and error messages and compile time speed,

all of this good stuff that we want. 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? Well, Clang and the LLVM is more or less written

from scratch. But there's been C++ 11, 14, 17, 20. 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. 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 and what features

got added? Let's first get a principle or an aim in place. C++ is for people who want to use

hardware really well and then manage the complexity of doing that through abstraction.

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. It doesn't mean I dislike C. If I disliked C, I wouldn't have

built on it. 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 ideal 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, in the way you get the memory

and you can do just as well. So in C++ there's an int. As in C, you should be able to build

an abstraction, a class, which we can call capital int, that you can 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. 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.

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

in terms of efficiency and so on. So what else is there? And flexibility.

I don't know. For people who are not familiar with object joining programming,

there's inheritance. There's a hierarchy of classes. You can, just like you said,

create a generic vehicle that can turn left. So what people found was that you don't actually

know. 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. That's how you get the traditional object oriented

programming coming out of Simula 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.

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 at it? Or that vector of

vectors and a vector of vectors of chess pieces. Now we 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 of abstracting of having similarities of

types in C++. There's the inheritance and there's a parameterization. There's the

object oriented programming and there's the generic programming with the templates for

the generic programming. So 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 metaprogramming.

You can do metaprogramming also. I didn't go there in that explanation. We're trying to be

very basics. But go back on to the implementation. 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 Nugor and Oli Handal.

And I get the simplest implementation I knew of, which was basically a jump table. So you get the

virtual function table, the function goes in, do it, 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 Simula 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 and your overhead compared to

ordinary functions. There's no indirection. It's sort of in 5, 10, 25 percent. Just the

core. It's down there. It's not two. 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. 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.

Now, auto parameterization. Basically, the compiler looks at

at 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're ridden a vector of that specific type.

Yes. So that's the 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 were very, very clever.

So the thing is parameterized code, the compiler fills stuff in during the compilation process,

not during runtime. 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. 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. Yes. And how do you remember being both

amazed at the power of that idea? And how ugly the debugging looked? 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 C front,

back in 83, had front end and back end optimizations. I actually took the code,

generated an internal representation, munched that representation to generate good code.

So people say it's not a compiler, it generates C. The reason it generated C was I wanted to use

a C code generator that was 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 combine

simple debugging with the optimal code, because the idea is to drag in information from different

parts of the code to generate good code, machine code. And that's not readable. So what people

often do for debugging is they turn the optimizer off. And so you get code that when something in

your source code looks like a function core, it is a function core. When the optimizer is turned on,

it may disappear. The function core, it may inline. And so one of the things you can do

is you can actually get code that is smaller than the function core, because you eliminate the

function preamble and return. And there's just the operation there. One of the key things when I did

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

sorting criteria, if that sorting criteria is simply comparing things with less than,

the code generated should be the less than, not a indirect function core to a comparison

object, which is what it is in the source code. But we really want down to the single instruction.

But anyway, turn off the optimizer and 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.

And then there's this idea of concepts that put 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. Let me try and explain. So yes, it wasn't there 10 years ago.

We have had versions of it that actually work for the last four or five years.

It was a design by Gabbidas Rays, Drew Sodden and me. We were professors in 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 Klangen and GCC, GCC for a couple of years. And I believe Microsoft is soon

going to do it. 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 it's 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.

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.

Yeah. 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 be a sequence with a

beginning and an end. There has to be random access to that sequence. And the element types

has to be comparable. Which means less than operator can operate on. Yes, less than logical

operator can operate. Basically, what concepts are their compile time predicates, their predicates

you can ask, are you a sequence? Yes, I have a beginning and end. Are you a random access sequence?

Yes, I have a subscripting and plus. Is your element type something that has a less than?

Yes, I have a less than. And 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, you can write in saying it should

operate on the element type. And it has the comparison operations. So that's just 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 gets. It's very similar to types, actually.

But operating in the space of concepts. The word concept was used by Alex Stefanov,

who is sort of the father of generic programming in the context of C++.

You know, 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 K&R 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, 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? So maybe the story of concepts, because I thought

it might be part of C++11, C0X, whatever it was at the time. 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? Back in 1987 or thereabouts. 1987?

Well, 1987 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. I didn't want to do that.

Secondly, it had to run faster, 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 build

a vector of char yourself without parameterization. And thirdly, I wanted to be able to express

the constraints of the arguments, have 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++. 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 could. So it bothered

me. Then we tried again, 2002, 2003. Gaby just raised 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, they started a project at Indiana. And we thought we could get

a good system of concepts in another two or three years. That would have made C++ 11 to C++

0607. 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. It didn't serve mixed type arithmetic, mixed type computations very well.

Well, a lot of stuff came out of the functional community. 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. Basically, we tried. We tried very

hard. We had some successes, but it just in the end wasn't. 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 defines 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. We just couldn't

do all of that. But get back to the standardization. We are standardizing C++ under ISO rules,

which is a very open process. People come in. There's no requirements for education or experience.

So you've started to develop C++. 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? I'll try and explain that. So sometime

in early 1989, two people, one from IBM, one from HP turned up in my office and told me I would like

to standardize C++. This was a new idea to me. I pointed out that it wasn't finished yet and it

wasn't ready for formal standardization and such. They said, no, Bjarne, you haven't gotten it.

You really want to do this. 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 boss. We really need to get this out in the open. It has to be

standardized under formal rules. We are going to standardize it under ISO rules. You really want

to be part of it because, basically, otherwise, we'll do it ourselves. We know you can do it better.

Through a combination of arm twisting and flattery, it got started. In late

in late 89, 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. We met there. We were lectured on the rules of

how to do an ANSI standard. There was about 25 of us there, which apparently was a new record for

that kind of meeting. Some of the old C guys that has been standardizing C was there, so we

got some expertise in. The way this works is that it's an open process. Anybody can sign up if they

pay the minimum fee, which is about $1,000. They're less than, it's a little bit more now. I think

it's $1,280. It's not going to kill you. We have three meetings a year. This is fairly standard.

We tried two meetings a year for a couple of years. That didn't work too well. Three one

week meetings a year, and you meet and you have technical meetings, technical discussions,

and then you bring proposals forward for votes. The votes are done one person per,

one vote per organization. You can't have, say, IBM come in with 10 people and dominate things

that's not allowed. These are organizations that extensively use C++? Yes.

All individuals. It's a bunch of people in the room deciding the design of a language based

on which a lot of the world's systems run. 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 H&C decides it.

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

Yes, look, standardization is not pleasant. It's horrifying. It's like democracy.

But exactly. As Churchill says, democracy is the worst way except for the others.

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. A couple of years later, we extended

this so it became worldwide. We have standard organizations that are active in currently 15

to 20 countries. And another 15 to 20 are sort of looking and voting based on the rest of the work

on it. And we meet three times a year. Next week, I'll be in Cologne, Germany, spending a week

doing standardization. And then we will vote out the committee draft of C++20, 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 1990. The last was in 98. We voted it out. That was the standard that people used

till 11 or a little bit past 11. And it was an international standard. All the countries voted

in favor. It took longer with 11. I'll mention why, but all the nations voted in favor. And we

work on the basis of consensus. That is, we do not want something that passes 6040,

because then we're getting getting a dialects and opponents and people complain too much.

They all complain too much. But basically, it has no real effect. The standards has been obeyed.

They have been working to make it easier to use many compilers, many computers,

and all of that kind of stuff. And so the first, it was traditional with ISO standards to take

10 years. We did the first one in eight, brilliant. And we thought we were going to do the next one

in six, because now we're good at it. It took 13. Yeah, it was named OX. It was named OX.

Hoping that you would at least get it within the single, within the arts, the single digits.

I thought we would get, I thought we would get the six, seven or eight. The confidence of youth.

Yeah, that's right. Well, the point is that this was sort of like a second system effect.

That is, we now knew how to do it. And so we're going to do it much better. And we've got more

ambitious and it took longer. Furthermore, there is this tendency because it's a 10 year cycle,

or it doesn't matter. Just before you're about to ship, somebody has a bright idea.

And so we really, really must get that in. We did that successfully with the STL.

We got the standard line that gives us all the STL stuff that that I basically,

I think it saved C++. It was beautiful. And then people tried it with other things.

And it didn't work so well. They got things in, but it wasn't as dramatic and it took longer and

longer and longer. So after C++ 11, which was a huge improvement and what basically what most

people are using today, we decided never again. And so how do you avoid those slips? And the

answer is that you ship more often so that 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. 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 shipped, we will ship 20 on time. It'll happen. And furthermore,

this allows, this gives a predictability that allows the implementers, the compiler implementers,

the library implementers, to, they have a target and they deliver on it. 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. 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. That's great. So that's how it works. 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 to you personally, beautiful or

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

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 key to C++. That's why we don't have to use garbage collection. That's how we can

get predictable performance. 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 RIAII. Resource acquisition is initialization, which is the idea that you

grab resources and the constructor and release them and 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. So it's types, abstraction of types.

You said, I want to create my own types. Types is an essential part of C++ and making them

efficient is the key part. To you, 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. It's almost like birth and death is what defines

human life. 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 1979

in about the second week of my work with what was then called C++. 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.

Finally, you have to be able to move things around so you get the move operations. That's

a set of key operations you can define on a C++ type. To you, those things are just a beautiful

part of C++ that is at the core of it all. Yes. You mentioned that you hope there will be one

unified set of guidelines in the future for how to construct the programming language.

So perhaps not one programming language, but a unification of how we build programming languages

if you remember such statements. I have some trouble remembering it, but I know the origin

of that idea. Maybe you can talk about, C++ has been improving. There's been a lot of programming

language. Where does the archer history taking us? Do you hope that there is a unification about

the languages with which we communicate in the digital space?

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 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 say,

I've got a great idea. Let's put it in the language. Then you have to ask, why does it fit in the

language? Why does it fit in this language? 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. One example 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. I said, I had this problem

and I developed it according to these ideas and they said, 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. 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 were trying to do.

So do you think that's possible? So they're 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 language

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 in Einstein towards

a simplified language? Do you think that's possible? 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.

And furthermore, they are not as bothered with people using physics the way we are worried about

programming. It's 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 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, etc. etc.

There will be quite a few and it will not be the same for all languages. But I think if we step

back at some kind of philosophical level, we would be able to agree on sets of principles

that applied to sets of problem areas. And within an area of use, like in C++'s case,

what used to be called systems programming, the area between the hardware and the fluffier

the fluffier parts of the system, you might very well see a convergence. So these days you see

Rust having adopted RAII and some time accuses me for having borrowed it 20 years before they

discovered it. But we're seeing some kind of convergence here instead of relying on garbage

collection all the time. The garbage collection languages are doing things like the dispose

patterns and such that imitate some of the construction, destruction stuff. And they're

trying not to use the garbage collection all the time and things like that. So 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, convergences, and it will be application domain specific.

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 could think of programming as a thing that takes some

input. Programming is the task of creating a program, and the program takes some input and

produces some output. So machine learning systems train on data in order to be able

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

we as children grow up, we take some input, we make some output, but we're noisy, we mess up a

lot, we're definitely not reliable biological system or 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 much, except sort of

empirically saying that 99.8% of the time, it seems to work. What do you think about this fuzzy

kind of programming? Do you even see it as programming? Is it solely and totally another

kind of world? 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 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 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 an 84% accuracy rate,

16% false positive rate is perfectly acceptable and where people will probably get no more than

70. You said 98%. I, the, what I've seen is more like 84. And by, by really a lot of blood,

sweat and tears, you can get up to the 92 and a half. So this is fine if it is, say,

pre screening stuff before the human look at it. It is not good enough for, for life

threatening situations. And so there's lots of areas where, where the fuzziness 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 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'm, I'm sort of an

amateur here. I've read some of the papers, but I've not ever done it. And 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

you have this AI system, machine learning, all of these trained neural nets. And when there's

something that's too complicated, they ask the human for help. But the human is reading a book

or sleep. And he has 30 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 cut over

between the machine and the human? It's very, very difficult. And for the designer of one of the most

reliable, efficient and powerful programming languages, C plus plus, 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. It is. And now it's stating a problem, not a solution.

That is impossible. I mean, 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 plus

plus that never ask human for help. Let, let, let's just get one fact in. Yeah. All of this AI

stuff is on top of C plus plus. So, so that's one reason I have to keep a weather eye out on

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. When you look back at your life work,

what is a, 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 plus plus?

It's obvious. I've spent a lot of time with C plus plus and there'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 plus plus, 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.

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. I mean, if it has just been statements

on paper or 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 and Tbilisi, Silicon Valley.

Yeah, there's more to it than just code. But code is central.

On top of the code are the people in very nice places. Well, I think I speak for millions of

people. We are 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.

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