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  • (relaxed music)

  • - So we're gonna be talking about memory layout in Swift.

  • As I'm sure you know, Swift is Apple's brand new,

  • magical, fancy programming language

  • and I'm gonna go dive into it a little bit

  • and talk about the bits and bytes

  • and how it's all put together

  • and what stuff looks like in memory

  • when you actually run the code on a computer.

  • Real brief about me, I'm online at mikeash.com,

  • I have a blog where I do all sorts of crazy stuff

  • like this, I like to take things apart

  • and see how they tick and I've got a bunch

  • of crazy Github projects which you should

  • probably never use for anything,

  • but are lots of fun to play with.

  • I'm on Twitter if you feel like following me.

  • There's a picture of my cat because, you know,

  • the internet is all about cats

  • and we're fundamentally all about the internet these days.

  • I fly gliders, just point of information,

  • it's a lot of fun.

  • And the arrow is kinda pointing over here

  • so that's me, you know, I always put a photo

  • of myself on these slides and then afterwards I'm like,

  • people can just look at me.

  • So I decided I'd stop doing that.

  • So here's the plan; first I just wanna give

  • a quick overview of what memory is.

  • I'm sure you all know what memory is,

  • but it can help to get a little bit of perspective

  • and just tear it down, you know, go to the foundations,

  • revisit the fundamental stuff.

  • Then I wrote a program that basically

  • is where I generated all this information,

  • it actually goes through, crawls, the program

  • starting from a particular value

  • and dumps everything out that are in those values in memory.

  • And then finally I'm gonna actually dive into

  • how Swift lays out stuff in memory,

  • what that program actually produces

  • and some contrast with how C does it and how C++ does it.

  • So what is memory?

  • And fundamentally memory is what stops this from happening.

  • So you gotta keep track of where you are essentially.

  • You've got a computational process

  • and you are at some state within that process at all times.

  • And if you can't keep track of that

  • then you will just never get anywhere.

  • So we don't wanna just endlessly repeat,

  • we wanna actually make progress

  • and that's what this is all about.

  • So figuring out how to actually build hardware

  • which can remember things and store information

  • and dig it out later is kinda one of the fundamental

  • problems in computing and there's

  • lots of technologies along the way.

  • Started out with vacuum tubes.

  • You can imagine these things are like this big

  • and they're essentially like an incandescent light bulb

  • and each one holds one bit.

  • So if you wanna actually store some reasonable

  • amount of data you're talking about

  • a room full of incredibly hot equipment.

  • Later on there were mercury delay lines,

  • this is kind of a cool technology of a pipe,

  • you basically fill it with mercury,

  • you have a speaker or something like that on one end

  • and something like a microphone on the other end

  • and you pulse your data through it.

  • And it takes time to travel and because of that

  • you can fit stuff in and store your information that way.

  • And there was a fun little proposal,

  • somebody decided that gin would make a good medium for this,

  • had all the right chemical properties and whatever.

  • As far as I can tell nobody ever built that,

  • but fun little aside.

  • Magnetic core memory was an advancement of this stuff,

  • it was a very neat technology, you got little rings

  • of iron and you run wires through them

  • and depending on the electrical current

  • you send through them you can store data

  • or retrieve data by storing it

  • in the magnetic field in those rings.

  • And so that was one ring per bit.

  • And the state of the art of this in the 60s or 70s

  • was basically a cube about this big

  • could hold 32,000 bits of information

  • and then you can imagine this thing I've got

  • in my hand can hold many gigabytes memory,

  • billions of bits.

  • And so things have advanced a lot since then.

  • So DRAM, dynamic RAM, basically silicon chips

  • is the state of the art today.

  • Which we should all be incredibly thankful for

  • because it really makes our lives a lot easier.

  • That fact that we can have these,

  • this allows us to store billion and billions

  • of bits of information all at once.

  • And my phone is misbehaving, if you can

  • pardon me for just a moment here, there we go.

  • Alright, so that's the hardware view of things,

  • we don't really care too much about hardware

  • most of the time if we're programming

  • because that all just works, we ignore it.

  • So how does it look for a programmer?

  • So we've got the fundamental unit of information

  • is the bit, that's a one or a zero.

  • Traditionally we organize bits in groups of eight,

  • those are bytes, and memory is essentially

  • just a long sequence of bytes one after the other

  • just heading off into the mist.

  • And they're arranged in a certain order,

  • every byte gets a number, that's called it's address.

  • So we start at zero and then one and then two

  • and then three and then an 8,000,000,000 byte system

  • we've got billions off in the distance.

  • It can be, you can view these things

  • in different directions, often we view it

  • like this, organized by word instead of by byte.

  • So a word is a vague term of the art

  • in computer science, but usually it means

  • a unit that's the size of a pointer.

  • So on modern devices it's 64 bits or eight bytes.

  • And it just heads off into infinity.

  • So here I've got the bytes addressed by eight.

  • And we like hexadecimal.

  • Hexadecimal is where you've got base 16 addressing

  • instead of base eight.

  • So zero through nine then A through F,

  • that's a nice multiple of two so everything

  • fits together nicely, it's kind of

  • the native language of computing.

  • So it's the natural language to use here.

  • And so I've got the addresses done

  • in hexadecimal instead, zero, eight, 16 is 10,

  • 24 and all that.

  • And this is just the big picture

  • of what this whole thing looks like.

  • If you zoomed out this is a Mac running on x86-64,

  • everything's a little bit different

  • and it's all very platform specific,

  • but essentially you've got a gap of stuff

  • that doesn't exist, the first four gigabytes of memory

  • is not mapped, this doesn't take up any physical space

  • it's just an addressing trick.

  • Then you've got the user, your program essentially,

  • your memory is the green stuff.

  • So you get a chunk that's for you

  • and then you've got a nice, big, empty space after that

  • and then finally the kernel is down at the bottom.

  • So you've got this two to the 64th power bytes

  • which get sliced up and organized like this.

  • And this is essentially how it looks

  • if you zoom in a little bit, so this is the same

  • picture as before except it's more realistic

  • because instead of starting at zero

  • we're starting at 4,000,000,000.

  • We've got pointers in memory, I'm sure you're all familiar

  • with the term pointer, references.

  • A pointer at this level is just a number.

  • And it's a number that just happens to correspond

  • to the address of something else in memory.

  • So here we've got this thing up there,

  • that stores the address of this bit down there

  • and I just indicate that with an arrow.

  • The arrow doesn't exist in reality,

  • it's just a number that we treat as if it were an arrow.

  • And one more detail on all of this,

  • whoops, went too far, we in the most modern systems

  • store things in little-endian order

  • which is essentially the least significant part

  • of the number comes first.

  • So it's as if you wrote 234 as 432,

  • everything's backwards, just one of those things

  • you just kinda have to learn to live with it

  • and read it that way, so.

  • Memory is organized into, as far as we see it,

  • is organized into three fundamental parts.

  • We've got at the hardware level

  • it's just a big list of stuff.

  • But the way we actually treat it,

  • parts of it have more specific purposes.

  • So we've got the stack which is where

  • all your local variables go when you write

  • variables that you're using in your computations

  • in a function, that goes on the stack

  • and it's called a stack because every time

  • you make a function call it adds that function's

  • local variables to it.

  • And when you make another call it goes up

  • and another call it goes up and then when you

  • return from a function it goes back down,

  • back down, back down.

  • So it's like a stack of things.

  • You've also got global data in your program.

  • Those are essentially things that came along

  • as part of the program when you loaded it.

  • So your global variables are part of that,

  • your string constants, your type metadata

  • in Swift, in other languages, just gets loaded

  • as part of that.

  • And then you've got the heap, and the heap is dynamically

  • allocated stuff, when you create a new object,

  • that allocates some memory that's on the heap.

  • And these are things where basically

  • they don't live permanently, they've got some lifetime

  • but they're not tied to a function, they're not

  • tied to your program, they come to life

  • and go away kind of arbitrarily.

  • And that's essentially everything else.

  • When you create a new object, when you allocate memory

  • manually, when you concatenate strings, whatever,

  • that's all on the heap.

  • So that's kinda the overview, remind you what memory is,

  • what the whole deal is that we're talking about here.

  • Let's get into dumping memory.

  • Actually diving in and inspecting the contents,

  • seeing what's actually in there.

  • So I'm gonna explore this program that I wrote,

  • how it works, that actually goes in

  • and traces all this stuff out.

  • If anyone wants to take a look at it

  • I've got it up on Github, the Github address

  • is there, or there's a tiny URL below,

  • or if anyone likes really huge URLs you can

  • use that one at the bottom, but I'm not

  • gonna wait for you to type it out.

  • Just real quick, this uses Xcode 8 and Swift 3.

  • If anyone's doing anything with Swift so far

  • you know that there have been a lot of versions

  • of it and they like to break compatibility.

  • So last year was Swift 2, starting a couple of weeks ago

  • we've got Swift 3 now and that's different.

  • So if you wanna use that code you need this.

  • So back to this.

  • The kind of fundamental unit of this program

  • is a function that looks like this.

  • And this is a function that works on an arbitrary type,

  • it takes a value and it's gonna return an array

  • of unsigned eight bit integers, or bytes.

  • And we'll just use it as in the demo above,

  • you create a variable containing something,

  • any arbitrary thing, and then you just call this

  • and it'll hand you back the bytes that make it up.

  • And that's going to serve as the foundation

  • for this whole program.

  • And the question is, how do we

  • write this in Swift specifically?

  • This is a real quick overview of one possible implementation

  • which is not what the program actually uses,

  • but it kinda gets the ball rolling

  • as far as how this works.

  • So the idea is you get the value,

  • you get it's size and because we know the type of the value,

  • this is a generic function in Swift

  • so it works on any type, but it knows

  • what type it's being called with at any given time.

  • This memory layout type allows us

  • to get the actual size, so that tells us

  • how many bytes it is, so we know how long it is in memory.

  • And then there's this built-in function in Swift

  • called with unsafe pointer.

  • So you call that, you give it a variable

  • and it comes back and gives you a pointer to that variable.

  • And once we have a pointer we can do things

  • like look at that pointer as if it were

  • a pointer of a different type.

  • So imagine you have a pointer to an int

  • and we do this with memory rebound call here

  • which says, okay, pretend that this is not

  • a pointer to an integer, pretend this is a pointer

  • to bytes, and just work with me on this,

  • it's the same thing but it's a different type.

  • Now go through and read it.

  • So what this does, this takes a pointer

  • to whatever arbitrary thing you've got

  • and says, alright, just pretend it's raw bytes,

  • interpret it that way.

  • And then once we have that we can go through

  • and just read one by one and that's

  • a bit of a shortcut here, I just tell the system

  • to read it for me, there's no loop or anything like that.

  • Unsafe buffer pointer basically lets me say

  • it's a container and then I can create an array from that

  • and it all just kind of happens.

  • Swift let's you write short stuff like that.

  • So real quick demo of what this produces.

  • I created a variable that contains

  • one, two, three, four, five, six, seven, eight

  • and then I just dumped out 42, and if I print these things

  • then I get these results here.

  • So you can see the first one prints out

  • exactly what we saw except it's backwards

  • because remember modern systems tend to do things backwards.

  • So it prints out eight, seven, six, five, four,

  • three, two, one, zero and then 42 comes out

  • as 42 with a bunch of zeros after it

  • because it's a 64 bit integer.

  • And just real quick, you don't need to actually follow this,

  • this is just some code I wrote

  • that I wanted to put up real quick.

  • Hexadecimal is again the natural language

  • of low level computing.

  • So this just takes an array of bytes

  • and dumps it out as a hexadecimal string

  • instead of as a sequence of decimal

  • integers like we saw before.

  • So if we use that then we get this instead.

  • Same basic thing except instead of printing

  • decimal we get hex.

  • So one, two, three, four, five, six, seven, eight

  • comes out just as it did before

  • and then 42 comes out as 2a, since that's what 42

  • is in hexadecimal, followed by a bunch of zeros.

  • So this let's us dump this stuff out

  • in a form that we can understand,

  • but that's still close to what the computer has.

  • Alright, so if you got this where we can take a value

  • and see what's in it, but real programs

  • are more complicated than single values, right,

  • they've got a lot more going on.

  • Real programs look more like this.

  • Okay, you've got a value which contains a bunch of bytes

  • and some of those bytes are actually pointers

  • which point to other stuff and those point

  • to other things and you get this whole tree thing going on.

  • So we want to be able to actually chase all this stuff down

  • in an automated fashion.

  • The program needs to be able to actually

  • find all of this stuff.

  • So how do we do that?

  • We start off with the knowledge that pointers

  • are just integers, alright, a pointer

  • is just an address, it's just a number

  • which we interpret as another location in memory.

  • So I wrote a quick struct which gets used in the program,

  • all it is is it just contains an address

  • which is an unsigned integer, pointer sized integer.

  • And wrapping it in a struct helps me keep things apart

  • so you don't confuse which parameters

  • are actually integers and which parameters

  • are integers which we are treating as pointers, right.

  • Just make a new type so that the type system

  • helps us write program correctly.

  • And then this bit of code essentially

  • takes an array of bytes, which we already know

  • how to obtain, we just wrote that function,

  • and it takes that array of bytes

  • and tries to scan for pointers in it.

  • So again, a pointer is just an integer

  • that you happen to treat as an address.

  • And we can't know how stuff is being treated

  • at this level because we just get

  • a bunch of bytes and we don't know what they mean.

  • So we're just gonna kind of optimistically go through

  • and slice it up into chunks of eight bytes

  • and pull them all out and pretend, say,

  • what if these were pointers, what would that mean?

  • So that's what this does, we take this array of bytes

  • and we say, instead of treating it

  • as an array of bytes gives me a pointer

  • to it's contents and treat it as a pointer

  • to pointers, okay, which means that we can

  • essentially go through and say, read the first pointer

  • size chunk, read the second pointer size chunk,

  • read the third pointer size chunk.

  • And then we take all of that and return it as an array.

  • So this code essentially will just go through

  • this big array of bytes that we get from the thing before

  • and divide it up, which, like this.

  • So this is a visual indication

  • of what's going on with that code.

  • So we give it a value, it returns

  • a bunch of bytes then we go through,

  • slice it up and get the individual pieces.

  • And then we can start chasing those down.

  • So we can read a value, grab all of it's bytes,

  • then we can grab all of the pointers

  • that those bytes might indicate.

  • And then we can take those pointers

  • and repeat the process and essentially

  • that gives you the tree, you can in a loop

  • keep going through as long as you've got pointers

  • to explore, you read their contents

  • and then you spit them out.

  • The problem with this approach,

  • we don't know which pointers are actually pointers

  • and which pointers are just integers,

  • it might be the player's high score,

  • it might be the number of people who dislike you

  • or something like that and we don't know what they mean.

  • And normally in a program when you try

  • to read from a pointer that's not actually a pointer,

  • it just is some illegal piece of memory,

  • then your program crashes which is good

  • in normal code because you don't want

  • to proceed when your program is that confused,

  • you want it to just stop and produce a crash log

  • or something like that.

  • But in this code we want to be able

  • to keep going so we can explore this stuff.

  • So we wanna be able to read from pointers

  • without crashing if they're bad.

  • So on the Mac and on iOS we've got this nice

  • low level function, Apple platforms use

  • a mach kernel highly modified and added onto stuff,

  • but the low level mach calls are still there

  • and there's a mach call called mach vm read overwrite.

  • And essentially it's a system call

  • where you give it two pointers

  • and you say, I wanna copy this many bytes

  • from that pointer to this pointer.

  • If you're familiar with the memcpy function

  • from the C standard library, it's exactly like that

  • except that if you give memcpy a bad pointer

  • your program crashes and if you give

  • mach vm read overwrite a bad pointer it's okay,

  • it returns an error because it's a system call,

  • it happens at the kernel level,

  • the kernel level can do all this checking safely

  • and so it can come back and say,

  • I couldn't do that because that is not a real pointer,

  • that was just a bunch of junk

  • and the address there doesn't exist.

  • And so based on that we can go through

  • and reliably follow this tree without crashing

  • because we can essentially optimistically try

  • every pointer, pass it to this function

  • and then if it comes back and says there was an error,

  • that's fine, we just say, okay, couldn't follow that,

  • keep on going.

  • This is a real quick, this is just a function prototype

  • what looks like it takes a task,

  • which is like a process, if you've got the right permissions

  • on the Mac you can actually read from other processes

  • not your own which is sort of the foundations

  • of how you can build a debugger.

  • It takes an address, it takes a length,

  • it takes a destination address

  • and it takes a pointer to something

  • where it will tell you how many bytes it actually read.

  • So back at the beginning I showed

  • a function that would read from a pointer,

  • but it would crash if you gave it a bad pointer,

  • this will read from a pointer safely.

  • So essentially it's just a wrapper around that mach call.

  • It takes the pointer you give it,

  • it does a little bit of casting

  • to get it into the form that the system wants

  • and then it just makes that call.

  • If it succeeds it returns and says,

  • hey, we did it, and if it doesn't

  • then it returns false, the caller can know

  • that it didn't work.

  • And so that way based on this we can build

  • this whole recursive scanning system.

  • Let's see, there we go, alright.

  • So we can read this stuff safely,

  • but we need to know how much to read.

  • The first value we read we can get the size of the type

  • because we know the type it compile time,

  • it's a generic function, we get that metadata

  • from the compiler, but after we start chasing pointers

  • we can't do that anymore because we're dealing

  • with arbitrary bags of bytes, we don't know

  • what this stuff is so we need to know,

  • we need to be able to at least guess

  • how many bytes to read at any given time,

  • when you chase these pointers through.

  • For stuff that's on the heap, there's

  • the malloc size function, at least on the Mac

  • and on iOS, where you give it a pointer

  • and it comes back and says, there were actually

  • 32 bytes allocated on the heap here.

  • So we can call that and it comes back

  • and tells us exactly how much we can read.

  • Which is great.

  • And even better, this function

  • is tolerant of bad data, so if you give it something

  • that's not a pointer or you give it

  • a pointer to something that's legitimate,

  • but not allocated on the heap,

  • or you give it a pointer to something

  • in the middle of something else,

  • whatever, it doesn't care, it'll give you back zero.

  • So it doesn't crash, which is really convenient

  • for our purposes.

  • And finally, we've got global variables,

  • code, things like that.

  • Those are symbols in your app, there's the dladder function

  • where you give it an address and it comes back

  • and tells you what symbol is nearby.

  • And so we can use that to check

  • to see if something is actually a symbol

  • and we can also use it to kind of extract

  • the size by essentially scanning.

  • It gives you the symbol that comes

  • immediately before the pointer you give it.

  • So you start from here and you say,

  • give me the symbol information

  • and if it comes back and says, yes,

  • I have symbol information, then advance it by one byte

  • and say, how 'bout here, how 'bout here,

  • how 'bout here, and just keep doing that

  • until it gives you a different answer

  • and then you know exactly how long that thing was.

  • And as a bonus, it also gives you the names.

  • So your function names, your global variable names,

  • things like that, those all pop out

  • of this API, and so we can use them

  • to annotate our scan and help us understand what's going on.

  • Those names in Swift and also in C++ tend to

  • come up mangled because the compiler

  • tries to embed information about what the type is

  • besides just the name.

  • So in C for example, if you have a function

  • called summon, the symbol name that it spits out

  • just says summon, and in Swift

  • if you have a function called summon

  • the symbol name comes out more like this

  • where you've got a bunch of extra stuff on it

  • because it will not only include that name,

  • but it will also include the fact

  • that it takes two integers and returns a string

  • or whatever it actually is.

  • So in order to help with that

  • there's the Swift demangle command that comes with Xcode.

  • I imagine it's available in the Swift

  • open source tools as well.

  • You give it a mangled symbol and it comes back

  • with something like this which is more readable.

  • So in my code I just dump everything through that.

  • Swift demangle is a very nice program

  • because if you give it something it doesn't understand

  • it just gives it back to you unmodified.

  • So I could just feed everything through it

  • without having to fear that it would explode

  • or crash or something like that

  • on data that wasn't actually mangles Swift symbols.

  • And then C++ has the same thing,

  • there's a tool called C++filt

  • which does the same job for C++ names

  • and it has the same semantics

  • where if you give it something it doesn't understand

  • it gives it back to you without changing it.

  • So I could just pass every name

  • that I came across to these two tools.

  • A lot of the data that we come across in memory

  • is actually strings, alright, textual information

  • like method names, like user input,

  • and it's useful to be able to find these.

  • And the trouble is again, we're working

  • with these bags of bytes, we don't know what's going on

  • with them, they're just a sequence of data

  • and we want to be able to at least guess

  • at which sequences of data actually

  • represent text and which don't.

  • And there's no way to do this reliably,

  • but a decent heuristic is to look for ASCII characters

  • and look for printable ASCII characters,

  • so zero through 31 in ASCII are control characters

  • which we don't expect to find

  • as part of text in a program, at least

  • not the text that we're interested in.

  • And then stuff beyond 126 is either the delete character

  • in ASCII, or it's non-ASCII characters.

  • So we look for printable ASCII characters

  • and we look for sequences of at least four.

  • So the idea is that if you just have one

  • or two or three then it's likely

  • that's just some other data that just

  • coincidentally happened to look like text.

  • And once you get up to four there's a decent chance

  • that it's something textually interesting,

  • and it's not a guarantee, but it's a decent

  • heuristic, it gives you good results.

  • And this is code that just goes through

  • and implements that heuristic here.

  • You give it an array of bytes

  • and it goes through, it splits that array

  • into chunks of continuous printable ASCII characters

  • and then filters out all the short ones

  • and gives you back the long ones.

  • So we can run this on the byte arrays

  • that we get out of the scanner to see

  • what's going on in them.

  • Alright, so those are the foundations of the program,

  • there's a bunch of bookkeeping that goes on in it

  • if you're interested in that part

  • look it up on Github, but those are the fundamental

  • pieces and we now know how to build all of that.

  • And so we can read all of this stuff,

  • but we wanna be able to actually output it

  • in some form that's nice for the human to look at.

  • So we could just dump it all in text form

  • or something like that, but it's gonna take

  • a lot of work to interpret.

  • Ideally we want something more like this.

  • And as an intermediate step I produce something like this

  • which is not very readable at all.

  • But this is an open source program called Graphviz

  • and essentially you give it a list of nodes

  • and you give it a list of connections

  • and you say this node has this label

  • and it's connected to these nodes

  • and this node has this label and it's connected

  • to these nodes.

  • And when you hand it over to that program

  • it hands you back stuff like this

  • which is really cool and readable

  • and you can go through and look.

  • This is, I wrote a simple C program

  • that creates a little structure in memory

  • and then hands it off to my dumper program

  • and that generates the Graphviz stuff

  • and then Graphviz turns it into a PDF

  • which looks like this.

  • So we can go through, we can read,

  • we can see we started off with a pointer up at the top,

  • that pointer points to some malloc memory

  • which contains this and those point to more

  • malloc memory which point to more malloc memory

  • and we've got a couple of strings at the bottom

  • and we can go through and you can just see

  • this whole structure visually, which is cool,

  • so that helps us figure out what's going on.

  • So that's the theory of how we're looking at these things.

  • So let's actually go through and look at them

  • and see what's going on with this stuff.

  • How does Swift represent things in memory?

  • How does C represent things in memory?

  • How does C++ represent things?

  • So quick notes, this is all very architecture specific,

  • I did this stuff on Mac on x86-64,

  • iOS 64 bit is likely to be very similar,

  • Swift on Linux 64 bit is likely to be similar,

  • but this is stuff that's very useful

  • for debugging, it's very useful for understanding

  • how the system works, it is not a good idea

  • to write any code that relies on this stuff

  • unless it's kind of a hobby project

  • or an experimental thing.

  • You don't wanna write any production code

  • that relies on this stuff because offsets,

  • sizes, the meaning of various fields

  • is all subject to change from one release to the next.

  • So it's really useful stuff, but you don't

  • want to incorporate this into that library

  • that you're writing for work that's gonna ship to users.

  • Oh, my phone is not cooperating with me today.

  • There we go.

  • Alright, let's take a look at some C structs.

  • C is very simple in how it lays things out in memory,

  • that's kind of it's appeal.

  • And we'll take a look at this real quick,

  • I made a C struct which just contains three long fields,

  • x, y and z, I wrote a little bit of code

  • that fills them with one, two and three

  • and then I dumped out that memory

  • using my nice graphical dumper

  • and that's what we get up here in the bubble.

  • And you can see that it essentially

  • just lays them out sequentially.

  • We've got one followed by two followed by three

  • and there's a bunch of empty space

  • because long is an eight byte value

  • and these are small numbers, so they have

  • a lot of leading zeroes and just puts them out one by one.

  • It gets more interesting when you get different sizes.

  • So this is a struct that has a bunch of fields

  • of different sizes, a through h, some of them are one byte,

  • that's a character, some of them are two bytes,

  • those are short, some of them are four, that's integers,

  • and some of them are eight bytes, that's long.

  • And again, the compiler just lays them out one by one,

  • you can see one, two, three, four,

  • five, six, seven, eight, but if you look closely

  • you'll see that some of them take up more space

  • than they maybe ought to.

  • Number three for example, three is one byte,

  • corresponds to c, that's a one byte field,

  • but if you look here you've got three followed by zero

  • followed by four, so there's extra space in there.

  • The reason for that is that struct fields get padded.

  • The idea is that it's more efficient to access data

  • when it's on a memory address which is divisible

  • by it's size, or at least which is divisible

  • by whatever the hardware architecture likes for it to have.

  • Typically it's its size.

  • So a two byte value wants to be on an even

  • numbered address, four byte value wants

  • to be on an address divisible by four.

  • And what the compiler does, this essentially wastes memory,

  • but it trades off memory against time

  • by expanding these fields a little bit,

  • adding some space between them when necessary

  • to make sure they all line up nicely

  • so that they're fast to access.

  • And that's really it for C.

  • C kinda has structs and that's about it

  • and it just lays things out sequentially

  • and there's no metadata, there's no

  • implicit pointers or anything like that.

  • C, what you see is what you get.

  • C++ gets more interesting though,

  • here's a simple C++ class, I've got three

  • virtual methods on it.

  • It's got one field, I create one and initialize it

  • and dump it out, and this is what I get.

  • So we can see now it's not just one bubble,

  • it's got a bunch of different stuff.

  • And I'll zoom it in so we can actually see

  • what's going on here.

  • Up at the top is the actual object

  • and that's the thing I created which contains,

  • in it's single field it contains the value one.

  • And we can see that it's got more than that.

  • So it just had one field, but here

  • we've got more stuff at the top.

  • And the program explored this

  • and found that that thing at the top is a pointer

  • which points here, and then that points to more stuff.

  • And so that thing at the top is a vtable pointer.

  • So in C++ the way you do virtual method dispatch

  • is the first pointer sized chunk of an object

  • is a pointer to a vtable, which is a table

  • of function pointers.

  • So when you call through to something like

  • object.x, what it actually does

  • is it uses that table to look up

  • the implementation of x for that object.

  • And that's how inheritance is implemented.

  • If you subclass something and override,

  • then that generates a new table

  • and that new table contains new entries

  • for those method implementations

  • so that the code knows what it needs to call.

  • So here's an example of that.

  • Quick C++ subclass, it inherits from the previous one,

  • it adds a new field, it adds a couple of new methods.

  • And when you dump that out you get a little more stuff.

  • And again, I'll zoom in.

  • So here we've got the object at the top,

  • like before you've got this vtable pointer

  • and then you've got the fields.

  • And if you'll remember, field number one

  • was from the super class, field number two

  • is from the subclass, it just puts them sequentially.

  • So the idea is that when the super class is doing stuff

  • it can look at it and it sees what it thinks

  • is itself and then the subclass data

  • gets laid out afterwards so there's no conflict there,

  • but they're just efficiently packed

  • in memory just the same.

  • And then the vtable for the subclass gets longer

  • because there were five methods now,

  • we had three from the super class, two from the subclass

  • and then it just lists them sequentially.

  • So every method just gets an index in this table.

  • And the subclasses get the same table

  • as their super class, except they can be

  • potentially longer if there are more methods added

  • and entries get replaced to indicate overriding.

  • Let's take a look at multiple inheritance,

  • this is where things get interesting.

  • C++ allows a class to subclass

  • multiple classes simultaneously.

  • So here's a second super class to go

  • along with our original.

  • And here is a subclass of both.

  • So each super class some methods,

  • each super class has a field, subclass has a field,

  • create it, fill it out with some data

  • and this is what we get.

  • It's a little bit more complicated.

  • The good news is that most of that

  • is runtime type information stuff

  • that we can kind of not look at too hard.

  • Let's zoom in and see what's going on.

  • So again, object is at the top

  • and we can see that it starts out similar.

  • So it's got a vtable pointer followed by

  • that first field, which is one,

  • but then something interesting happens.

  • Instead of doing just one, two, three,

  • laying out all the fields sequentially,

  • we get another vtable pointer

  • right in the middle of the object.

  • And so this is how C implements multiple inheritance.

  • We've got one vtable pointer at the top,

  • we've got another one over there.

  • And the idea is that it's kind of like

  • two objects glued together.

  • So if you take this first one here,

  • that's the vtable that indicates

  • it's an instance of that first super class,

  • and then the second super class gets laid out below it.

  • And what happens normally in C and with simple C++ classes

  • if you cast between types it's got an instance

  • of a subclass, you say, treat this as if it

  • were an instance of its super class.

  • This is just like some bookkeeping trickery, right,

  • you've got the exact same pointer

  • and you just say, okay, pretend this means something else.

  • But when you get multiple inheritance involved

  • suddenly things get a little more complicated.

  • And if you say, take this pointer

  • and interpret it as a pointer to its super class,

  • what it will actually do is it will move

  • that pointer a little bit.

  • So in this case it's going to add 16 to that address

  • and give you a pointer into the middle of this object.

  • And because that vtable is right there,

  • it all just kinda works out.

  • And it's a bit of a crazy system,

  • but it gets the job done.

  • And so you can see the effect here

  • where you've got essentially the vtable

  • for the subclass and each part of this object,

  • you've got two vtables in the object,

  • each one points to a different part of this vtable

  • and everything just kinda lines up

  • with these multiple super classes

  • so it all just works out.

  • Lots of compiled time trickery

  • and then the end effect is at runtime

  • everything is nicely laid out, friendly, and quick.

  • Friendly for the computer, not for us,

  • but that's usually okay.

  • So that's C++, you get crazy stuff with multiple

  • inheritance, but it's usually straightforward.

  • Again, you get that vtable at the top

  • which tells you what kind of object it is

  • and then all the fields are just laid out.

  • Sometimes you get padding depending on their sizes,

  • but it's just one after the other, after the other.

  • Just in line.

  • So let's move on the Swift now.

  • And Swift starts out very simple like C and like C++.

  • So just to get the ball rolling

  • I created an empty struct and you'll never guess

  • what it looks like, an empty struct contains nothing at all,

  • it's a zero size object.

  • Interesting feature of this, it does still have an address

  • in memory even though it doesn't contain anything.

  • The compiler still gives it an address

  • which I thought was kinda funny.

  • It probably doesn't make a whole lot of sense

  • for the compiler to optimize for zero size structs

  • since we don't use those very much.

  • Move on to a more realistic example,

  • more useful example, here's a struct with three fields.

  • This is essentially the Swift equivalent

  • of that C example I did with the beginning.

  • Three fields, one, two and three,

  • and it looks, this is the result, the output,

  • the way it's laid out in memory

  • looks a lot like the way it was laid out in memory in C.

  • And in fact it doesn't just look like it,

  • it is exactly the same.

  • These two are laid out in exactly the same way.

  • So Swift is just laying it out one, two, three

  • in a row like that.

  • There's no fancy metadata going on,

  • there's no extra stuff, it's just your fields.

  • And then I did the same thing that I did before

  • with the multiple sizes.

  • And again, we get the exact same result.

  • So this is a complicated struct

  • with different fields of different sizes

  • and the output is exactly the same as it was in C.

  • With one exception, you'll notice that after three,

  • you get one, two, three and then there's

  • this five f thing before four, that's just because

  • the padding that gets inserted

  • does not have to contain any particular value

  • because it doesn't mean anything.

  • The padding is ignored.

  • So before when I ran the thing on C

  • it just happened to contain zero

  • and when I ran it on this it just happened

  • to contain five f.

  • So this is kinda like the junk DNA inside your program.

  • But again, it's just laid out

  • exactly the same way C is, so there's no overhead,

  • it's very straightforward.

  • Let's look at a little more complicated thing,

  • let's see how a Swift class looks.

  • So simple thing, complicated result.

  • It's not as bad as it looks.

  • Essentially what you're getting in there

  • is that Swift has this whole hierarchy of stuff

  • and it knows what types mean at runtime.

  • And I wanna zoom in a little bit so we can see the object,

  • but what all this other stuff is going on

  • is essentially it's saying that your class

  • is actually a subclass of this heap in

  • the Swift object class and then that class

  • has a metaclass and all that stuff.

  • So there's all this metadata that's going on

  • that you can use to inspect objects

  • and things like that.

  • But we can mostly ignore it.

  • So if we ignore all that other stuff

  • and kind of zoom in, we look at the instance

  • of the object here and we can see the data

  • laid out in memory, one, two, three,

  • and there's a header above it which is similar

  • to the way C++ was.

  • In C++ we had a vtable and then there were the fields,

  • and in Swift we have an isa pointer,

  • which is essentially the Swift equivallent

  • of a vtable, it points to the object's class,

  • then we've got some other stuff

  • which I'll talk about in a moment

  • and then you've got the fields.

  • So you've got the same arrangement of a header

  • followed by the fields just packed in memory.

  • Nice, linear, fast, hardware friendly.

  • And let's take a look at a little bit more

  • complicated class, this is the class equivalent

  • of that struct that I showed.

  • And it ends up being the exact same thing

  • with that sort of header put at the top.

  • So you've got that isa pointer,

  • you've got this other stuff which I'll get to.

  • And then all the fields are just laid out

  • the exact same way they would be in a struct.

  • Sequentially with some padding to make

  • everything line up nicely.

  • So this is sort of the visual representation,

  • the abstract representation 'cause those hexadecimal

  • things get painful to read after awhile.

  • So this is what they mean if you actually

  • go in and interpret it.

  • You've got the isa pointer, that other header field

  • that I didn't mention yet, those are retain counts,

  • you may or may not know Swift operates

  • using automatic reference counting.

  • So it needs to count the number of references

  • to each object and in Swift those counts are stored

  • in the object itself as that second header field.

  • And then your stored properties just get laid out

  • after that, the compiler just puts them one by one.

  • And I did say retain counts, plural,

  • so there are actually two counts in a Swift object,

  • this is in interesting little feature

  • of the way the system works.

  • There's the strong count and the weak count.

  • So when you make a normal reference to a Swift object

  • that increments the strong count

  • and then if you make a weak reference

  • to an object that increments the weak count.

  • And the idea is that when the strong count

  • goes to zero, if the weak count is non-zero

  • then the object is destroyed, but it's not deallocated

  • and that could be a talk by itself.

  • I got a blog article about it if anyone

  • cares about exactly how that works.

  • But that's essentially what we're seeing there.

  • So there are two separate counts

  • packed into the same field.

  • Each one I think is like 31 bits or something like that.

  • And then let's look at that isa structure.

  • So that isa structure in C++ the vtable

  • was just a list of method pointers.

  • In Swift it's a little bit more complicated

  • partly because of Objective-C interopp.

  • Swift has to work with Apple's Objective-C stuff

  • and in fact all Swift classes in memory

  • are also Objective-C classes.

  • This fact is hidden from us sometimes.

  • If you explicitly subclass in Objective-C class

  • then you can see it, if you use the at obj C

  • annotation you can see it.

  • But even if you do none of that and you do

  • what looks like a pure Swift class,

  • it's actually an Objective-C class just the same.

  • And just to be a little bit more accurate,

  • the first part of an object is not necessarily

  • the isa pointer, sometimes it's the isa pointer

  • along with some other junk.

  • This is just a way to sort of efficiently pack

  • some metadata in there.

  • Apple does this on iOS 64 bit,

  • I don't believe they do this on the Mac currently.

  • This is all subject to change,

  • but basically they can put little

  • extra bits of information in there

  • like whether this object has ever had

  • any associated objects with it

  • that need to be cleaned up when its deallocated

  • and things like that.

  • Just real quick detail there.

  • So what do these class structures look like?

  • Since every Swift class is also an Objective-C class,

  • that means that we can look at Objective-C

  • class definitions to see what's going on.

  • And Objective-C class definitions

  • are part of the Objective-C runtime

  • which is open source, that's convenient.

  • So we can just look in runtime.h

  • in the open source dump there.

  • And if we look there and we see what's going on,

  • this is what we get.

  • So every class is also a valid object in memory.

  • So if you remember an object starts

  • with an isa pointer, so that means every class

  • starts with an isa pointer as well.

  • So every class is also an object,

  • a class has a class, that's called the metaclass

  • and you can follow that rabbit hole

  • all the way down until you get very confused.

  • The class also stores super class.

  • So that allows you to follow the chain up

  • and essentially explore the class hierarchy.

  • Class stores its name, it stores a bunch of other stuff,

  • it stores how big it's objects are,

  • it stores a list of instance variables

  • and methods and it's got a cache

  • which speeds up methods dispatch.

  • And then Swift classes take all of that

  • and they add more stuff because Swift

  • has more stuff going on.

  • So if you look in the Swift open source

  • to see what's involved there,

  • we've got some flags, we've got this offsets,

  • a lot of bizarre stuff.

  • But essentially a Swift class is the Objective-C class

  • with more stuff on the end.

  • And then, this is an interesting part,

  • after all of those fields it's a list of methods again,

  • an array of method implementation.

  • So essentially it's the C++ vtable approach again

  • with some extra stuff at the top that we can ignore.

  • And so what that means is that when you do

  • a method call in Swift it translates

  • into essentially an array lookup.

  • So you write obj.method up here

  • and that translates into code like this down here.

  • So essentially you take to object,

  • you get that isa field out of it

  • and then you just index into it

  • to get the method pointer and then you jump to it.

  • You essentially make a function call based on that.

  • And so it's quick, it's efficient at runtime.

  • Let's take a look at what an object

  • looks like when you subclass a bunch of stuff.

  • So I made a class, a subclass,

  • a subclass of that and so forth four levels deep.

  • And it looks exactly the same.

  • So you've got that isa pointer at that top

  • which tells you what it is, you've got

  • the retain counts below that and then the field

  • of all those classes just gets laid out sequentially.

  • Just like in C++ we saw before.

  • So at runtime it's very simple.

  • Even though the class hierarchy we looked at

  • was kind of long and complex.

  • Let's take a look at arrays in Swift.

  • Arrays in Swift are value types

  • which means that they act like primitives essentially

  • when you assign x equals y that conceptually creates

  • a new array which is codally separate from the original,

  • this dump reveals that's essentially a lie,

  • they are, in fact, reference types under the hood

  • the way they're implemented.

  • So this array, one, two, three, four, five,

  • if you actually look at it it's just a single pointer.

  • And that points to one, two, three, four

  • and then five after that which ran off the end

  • so it got truncated.

  • And so what's going on with that is every array

  • that you work with is actually a pointer

  • to the storage and when you make a new array

  • you just get a new pointer to the storage,

  • nothing really happens and it's only

  • when you actually modify it, it will go in

  • and it will see, oh, someone else references this,

  • I will create a copy and then modify that copy.

  • So it still references under the hood,

  • you just don't see it until you run

  • a program like this, then you see it.

  • Let's take a look at protocol types,

  • this is an interesting aspect of Swift.

  • So here's a Swift protocol, it's got three methods in it.

  • Here is a struct, which holds three instances

  • of that protocol, right, you can use

  • a protocol as a type itself and that can hold

  • an instance of anything that implements that protocol.

  • Here is a struct which implements it,

  • it's just got empty implementations of those three methods.

  • It's also got a field which is just an integer

  • containing the strange hex value,

  • that hex value will spell out the word small in ASCII,

  • basically that's there so that when I do the dump

  • we can identify it because it will search

  • for that string, it will show it in the printing.

  • Here's another struct, this is a larger one,

  • it's got four fields.

  • The first one spells out large

  • and the other ones just contain one, two, and three

  • repeated just so that they show up nicely.

  • And finally, here is a class, if this wants to advance,

  • yeah, my wifi is not cooperating.

  • There's a class which, same as the struct essentially

  • except it spells out class instead.

  • And so we wanna see how these get represented.

  • So here we create an instance of that protocol holder

  • containing one instance of the small struct,

  • one instance of the large struct

  • and one instance of that class.

  • And if we dump it out here's what we get.

  • The larger view of this is very complicated,

  • but we can see that struct in the list of strings

  • that it found, it found small.

  • So we can tell from this that that small struct

  • actually gets stored inline, that protocol,

  • that field of protocol type is able to store

  • that struct inline, but the large struct

  • does not get stored inline and of course

  • the class doesn't because the class is a reference.

  • And where did that large struct go?

  • Because structs normally get stored inline,

  • but this one was large, it ends up getting stored

  • off on the side here if you chase the arrows around.

  • And essentially what happens is it's too big to fit.

  • The compiler can't know how big

  • these things are gonna be so it places

  • an arbitrary size limit and when you go over that limit

  • then the compiler behind your back boxes it up,

  • allocates something dynamically and stores it over here.

  • So here large gets stored off in the weeds somewhere.

  • If you chase it down you actually look

  • at how these things are implemented.

  • A value of protocol type holds five fields.

  • It holds three arbitrary data fields

  • and then it holds some type metadata

  • which essentially tells you what it is

  • and then it holds a witness table

  • which is like a vtable for the protocol.

  • And those three data fields are given over

  • to whatever the type needs them for.

  • So if you've got a struct which holds

  • that much stuff or less it gets stored inline

  • very efficiently and everything is quick

  • and as soon as you go over that limit,

  • suddenly it has to get broken out,

  • it gets boxed up, it gets allocated dynamically

  • and you loose a lot of efficiency.

  • And this is all hidden from you,

  • you don't notice it util your code gets slow.

  • So the witness table is basically a vtable,

  • it's just an array of implementations

  • just like the C++ vtable.

  • And so that means that when you make a method call

  • on a protocol type it looks a lot like

  • a method call on an object 'cause you've got

  • this special table just for the protocol.

  • So when you make a call you get a protocol

  • type like that, you do p.g, make a call,

  • it translates into something like this.

  • You just take that, you look up the table

  • by looking up the fourth word in the protocol

  • and then you use the offset in the table

  • that you know about because the compiler

  • just knows that it's that method

  • and then you just make the call

  • based on the function pointer.

  • And then if you have a struct that's too big

  • it ends up looking like this, instead of having

  • data fields, that first data field

  • is actually a pointer to the real data.

  • So everything gets stored off over here,

  • you've got the table over there.

  • And then the methods here know

  • that when they need to do their stuff

  • they have to go up and chase that pointer

  • and it's all just handled behind your back.

  • And this is not cooperating again, indeed, there we go.

  • Enums are a very interesting case in Swift.

  • So Swift has these high level enumeration types

  • where you can have associated data and all that

  • or they can just be very simple things.

  • Here is a simple case, just five cases,

  • nothing associated with them, just A, B, C, D, and E.

  • Here's a struct which will hold those.

  • And the result is those get laid out very succinctly,

  • zero, one, two, three, four, each one

  • gets a different number, they're one byte long

  • because we don't need more than one byte

  • to represent five values and it's all

  • very nice and compact.

  • Here is a version with a raw value

  • so you can actually go through and tell Swift,

  • I want my cases to correspond to specific values.

  • So what this does is it says A is one, B is two,

  • C is three, D is four, E is five.

  • And let's see what that looks like.

  • And an interesting thing, it does not change.

  • It doesn't go one, two, three, four, five,

  • it still goes zero, one, two, three, four.

  • Alright, running out of time here.

  • Real quick, if we just go through (clicks)

  • for a string, you can do string raw values.

  • So A is whatever and then B, C, D, and E

  • get defaults, those are just B, C, D, and E.

  • And those still are zero, one, two, three, four.

  • And essentially what's going on here

  • is the raw value can be stored

  • off in a separate table somewhere,

  • the compiler knows about it, there's no per instance

  • raw value of any kind, so it can just be

  • zero, one, two, three, four and somewhere else

  • there's a table that says zero is whatever,

  • one is B, two is C, and so forth.

  • Alright, let's look at associated objects real quick.

  • This is just an enum, the first case

  • has an object associated with it and the others do not.

  • And if we dump that out we find that it has expanded

  • because it needs to be able to store that object pointer,

  • but it has expanded intelligently.

  • So the first thing is just a raw object pointer

  • and then the other ones are just small integers.

  • And the compiler's able to pack these

  • so that it knows zero, two, four, and six

  • can never be a valid pointer.

  • So it's able to use that to distinguish between those.

  • And then if we make it larger we have an enum

  • with A, B, C, D, and E where they all

  • have objects associated with them

  • and suddenly everything gets bigger.

  • Every entry is a pointer followed by an integer.

  • So object pointer zero, object pointer one,

  • object pointer two, object pointer three.

  • So the number that gets assigned to each enum case

  • and the associated value essentially get laid out

  • next to each other.

  • The compiler's able to pack them compactly

  • for that one specific case, but not in the general sense.

  • Alright, so wrapping up, I'm just gonna kinda

  • skip through these real quick since we're behind on time.

  • We've got real physical memory, we've got conceptual memory

  • and then we've got sort of the actual,

  • the architecture of it all.

  • C just lays things out nice and straightforward

  • with a little padding.

  • C++ objects get a vtable at the top.

  • Swift objects get the same sort of thing,

  • but with more stuff going on.

  • Protocol values end up taking up five words of memory,

  • sometimes they can store data inline,

  • but if you get too big they don't.

  • And enums end up being packed in many different ways

  • depending on what's going on.

  • There's our quick sum up which I just said.

  • And so you can learn a lot by poking around.

  • It's a lot of fun and sometimes it's useful.

  • And as they asked me to remind you,

  • and as I did before, remember to rate

  • the session in the app and that's it.

  • So if there's questions we can,

  • or if we have no time for questions or (laughs),

  • okay, can you use Swift demangle

  • with PO in Xcode when debugging?

  • I don't think there's any built in way to do that,

  • but what you can do is just copy, paste

  • onto the command line, Swift demangle should be

  • available in the terminal.

  • If you wanted to I'm sure you could

  • build a little script, LLDB is scriptable through Python

  • so you could do that if that turned out to be useful.

  • Yes.

  • Okay, so the question is, any versus any object

  • in Swift three and whether there are changes

  • based on whether you import foundation?

  • I don't think there would be changes in the layout

  • based on what you import because there needs

  • to be cross-compatibility between files

  • that import foundation to files that don't.

  • So they would still need to be the same.

  • But any, in Swift 3 Objective-C objects

  • as untyped objects now come in

  • as any instead of any object, so there's definitely

  • a change there, I believe that's just

  • essentially a translation phase.

  • Any I think looks like one of the protocol types

  • where it's a five word thing, it's got three

  • inline and whatever and it's essentially

  • storing things that way.

  • And then there's just a step where it takes

  • that Objective-C pointer that comes in

  • and just kind of puts it in one of those things.

  • The source code is online for my thing,

  • it should run more or less out of the box,

  • so if you wanna experiment and see what it does feel free.

  • Anything else?

  • No?

  • Alright, oh, yes?

  • (inaudible)

  • Sure.

  • Yeah, so question is about the new

  • memory debugging facilities in Xcode 8

  • and how it compares to my stuff.

  • So that new memory debugging stuff

  • is really cool, you can go through

  • and it will just essentially show you

  • kind of graphs like I showed here

  • except they're live which is really neat.

  • And I haven't played with it a ton,

  • but I'm sure it's gonna be really useful.

  • It's a little bit more limited from what little

  • I have done with it, in that it tries to,

  • well it's gotta work at runtime,

  • so it has to be kind of limited in that respect.

  • I believe it will not trace like, C pointers

  • and things like that, at least not

  • beyond a certain point.

  • It's not gonna be tracing global symbols

  • and things like that.

  • But as far as like, looking at plain Swift objects,

  • it's really cool, it'll show you the trees,

  • it'll show you this object points to that object.

  • And I think it's gonna skip over things

  • like the pointers up to the classes,

  • so it doesn't give you everything.

  • But for what you care about day to day,

  • it looks really cool, really useful.

  • Alright, looks like that's it.

  • Thank you very much for coming

  • and enjoy the rest of the conference.

  • (applause)

(relaxed music)

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GOTO 2016 - 探索Swift內存佈局--Mike Ash (GOTO 2016 • Exploring Swift Memory Layout • Mike Ash)

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    colin 發佈於 2021 年 01 月 14 日
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