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  • [MUSIC PLAYING]

  • DAVID J MALAN: All right.

  • This is CS50, Harvard University's introduction

  • to the intellectual enterprises of computer science

  • and the art of programming.

  • And ordinarily we would all be here on campus in this beautiful Sanders

  • Theater together.

  • This, of course, is a little bit different this year,

  • for more than one reason.

  • But we're here instead in the Loeb Drama Center at Harvard University.

  • Thanks to our friends in collaboration with the American Repertory Theater,

  • we have this new space, including even such amenities as a prop shop in back,

  • where we've been working with an amazingly talented team

  • over the course of the summer to prepare for this semester and CS50.

  • And so I daresay we'll have some new and improved demonstrations along the way.

  • So our thanks to our hosts, the American Repertory Theater.

  • Now we wanted to evoke memories, at least,

  • or some imagery of the campus itself, particularly

  • for the many of you who could not be here in person this semester.

  • And so we went into the Harvard Archives, where among their collections

  • was this watercolor painting, painted by a Harvard graduate student

  • over 200 years ago in the year 1794.

  • Jonathan Fisher, who sat in what is now Harvard Square,

  • looking in on some of the earliest buildings of Harvard's campus.

  • And thanks to technology, we took what is a relatively small watercolor

  • that this graduate student painted some 200 years ago,

  • and now adorns the stage here in the Loeb Drama Center.

  • So if unfamiliar, we have Holden Chapel here at left,

  • Hollis Hall to its right, which is one of the undergraduate dormitories

  • in Harvard Yard, Harvard Hall, which is one of the classroom

  • buildings on campus, and then Massachusetts Hall,

  • where both first years and Harvard's president live and work respectively.

  • So welcome, then, to CS50.

  • And I can say that not quite as long ago,

  • but, nonetheless, feels rather long ago, some 20 years ago,

  • did I take the same class.

  • But as you know, I myself had some trepidation

  • when it came to studying CS50, when it came to studying computer science.

  • Because it was a very unfamiliar field.

  • I had followed a path when I got to college of sticking within my comfort

  • zone, studying government early on, thinking I would major

  • or concentrate in government.

  • And it wasn't until I got up the nerve to shop, that is, sit in

  • on this class CS50, that I realized that homework can actually be fun.

  • And I found that computer science and CS50 is not about programming per se,

  • even though that's how many of us perceive it in high school,

  • whether it's us or our classmates taking the class.

  • But it really is about problem solving.

  • And as such, it's so very applicable not only

  • to computer science and the engineering fields,

  • but really to the arts, humanities, social sciences, sciences, and beyond.

  • And so if you're feeling a little uncomfortable

  • with the idea of taking a class like CS50,

  • know that almost every year, nearly two thirds of the students who take CS50

  • have never taken a computer science course before.

  • So if you look up, down, left, right, right now, odds are more than many

  • of the classmates joining you here today are in a very similar position.

  • You're indeed in very good company.

  • And what's ultimately important in CS50 too, we emphasize, as in the syllabus,

  • that what ultimately matters in this course is not so much where

  • you end up relative to your classmates, but where you end

  • up relative to yourself when you began.

  • Indeed, taking into account where you currently are, perhaps

  • with no prior background, and considering

  • where you will be in just three or so months

  • is ultimately meant to be the measure of your own success.

  • And so toward that end, we'll start off this class programming

  • a little something from yesteryear.

  • An image here of Super Mario Brothers and the pyramid

  • that the character has to ascend.

  • We'll recreate a portion of this game, albeit using text--

  • otherwise known as ASCII art-- but we'll do that in just the course's second

  • or so week.

  • So this will be among the first programs you write.

  • And then fast forward just several problem sets or programming

  • assignments later, or several weeks later, too,

  • and you'll be building what we call CS50 Finance, a web

  • application of your very own that runs on the internet,

  • pulling down nearly real-time stock quotes from a third party service,

  • allowing your own users to log in and register to buy and sell stocks,

  • so to speak, using virtual currency.

  • So over the course of the class's several months,

  • will you go, truly, from building a pyramid in Mario

  • to building your very own web application and more,

  • followed by the course's capstone experience, which

  • will be your very own final project.

  • But what exactly is computer science?

  • What we thought we would do in this week zero, the very first week of the class,

  • is consider exactly what it means to solve problems.

  • And let me propose that this is computer science.

  • This is problem solving.

  • You have some input, which is the problem you care about

  • that you want to solve, and you care about the solution to that problem,

  • which is the so-called output.

  • And in between that input and output is this black box

  • of sorts, inside of which is the magic that happens,

  • the magic that you'll eventually be able to harness and compel computers

  • to solve problems for you.

  • Inside of that black box, ultimately, is going to be the code that you write.

  • But for us to begin doing that, we all kind of

  • need to agree on how we're going to represent these inputs and outputs.

  • We all kind of have to speak a common language, so to speak.

  • And so we need to agree how these inputs are going to be represented.

  • So how might we typically represent information?

  • Well, maybe the simplest thing to do at the very first class, whether we're

  • online or in person, is to take attendance

  • or to count the number of people in the room.

  • And so you might do this old school style on your hands

  • so as to represent every person in a room

  • with just a finger raised on your hands.

  • So how we might represent information boils down

  • to very simple digits on your hand.

  • Of course, you can't count very high with just this hand.

  • And there's actually a fancy word for what we're doing,

  • old school here, and that's unary notation-- uno, implying one,

  • or one finger being up or down.

  • And so you can count, it would seem, as high as five.

  • And of course, if I bring in a second hand,

  • I can go as high as 10, and then things get a little more difficult.

  • But it's a system for representing information

  • and it's fairly universal, certainly when we're all quite young.

  • But you and I tend to use a more useful system.

  • Not just digits on the hand, but other sorts of digits.

  • Namely, the decimal digits that you and I know.

  • So the numbers that are otherwise more technically called base 10--

  • and that's just a fancy way of describing the fact

  • that there's 10 digits that you and I as humans really tend to use typically.

  • Those digits, of course, are zero through nine,

  • and using these several digits, we can pose numbers like zero

  • through nine, but also 10 and 11 and 12, and as high up

  • as we want to go by using multiple digits still.

  • But computers don't really speak the same language as us.

  • They're, in some sense, much simpler than we humans,

  • even though they seem so complicated or so sophisticated and certainly so fast.

  • At the end of the day, these are all human-made devices,

  • and they're relatively simple at their core.

  • In fact, even if you don't quite know what you're saying,

  • but you've at least heard this to be the case,

  • what language do you understand computers to speak?

  • What language do computers speak, if not the system that you and I use

  • of zeros through nines or decimal?

  • Brian, could we see who might answer this?

  • What system do computers use, so far as you've heard,

  • whether or not you've taken a CS class before?

  • Keith, can we go to you first?

  • AUDIENCE: Yeah.

  • The computers use binary.

  • DAVID J MALAN: Binary.

  • And can you elaborate a little bit?

  • What do you mean by binary?

  • AUDIENCE: It's zeros and ones.

  • So, like, while we use zero through nine for base 10,

  • they use zero through one for base 2.

  • DAVID J MALAN: Yeah, exactly.

  • So computers use the so-called binary system, bi implying two.

  • And they, indeed, only use, as Keith notes, zero and one, two digits.

  • So on the one hand, this is actually pretty encouraging,

  • because, wow, this is actually a pretty simple system if we're only

  • using two of these digits.

  • But, of course, if you only have two digits,

  • how are we going to represent the number two or three or four

  • or any much larger number?

  • It would almost seem like a step backwards.

  • But it isn't actually.

  • And it turns out that this so-called system, or base 2--

  • two because there's two digits in the vocabulary, otherwise known,

  • as Keith says, as binary--

  • uses just zeros and ones, and it turns out there's other nomenclature here

  • we can toss out.

  • These zeros and ones are otherwise known as bits.

  • And bits actually derive from just two words, binary digits.

  • Binary, implying two possibilities, digits,

  • just being symbols on the screen.

  • So binary digits, or otherwise known as bits.

  • And computers speak binary using these things called bits.

  • But what does that mean and why is it the case?

  • Like, why didn't they invent computers decades ago

  • that just use zero through nine, rather than

  • come up with a whole new system for us to think about, let alone talk about?

  • Well, at the end of the day, computers are using what as their input?

  • Really just electricity.

  • Probably the only thing all of us do every day or every couple of days

  • with our laptop or desktop or phone is either make sure it's still plugged in,

  • or to plug it in so as to charge it.

  • So the only physical input to our devices

  • these days is electricity in some form.

  • And we don't have to get into the nuances of what electricity is,

  • but I think it's about electrons flowing into the device so as to charge it.

  • So it suffices for our purposes to know that there's

  • some physical input to the device, these computers and phones that we use.

  • But that's it.

  • And so if we harness this electricity, maybe we

  • can start to represent information with it.

  • For instance, here is a light bulb, this old ghost light in the theater here

  • that's currently off.

  • But it has the ability to turn on.

  • We just need to plug it in or throw on a switch.

  • And if that's the case, what's really quite

  • compelling about the metaphor of using lights

  • is that right now, this light bulb is currently off,

  • but as soon as I allow electricity to flow

  • as by plugging it in or maybe throwing a switch, now it's, of course, on.

  • And if I unplug it or throw the switch again, it's off.

  • Or if I plug it back in, it's on.

  • And the implication of this very simple idea

  • is that we can take a physical device, like a single light bulb,

  • and by plugging it in or unplugging it, we can represent information.

  • What did I just do?

  • I represented the light bulb being off or on,

  • but we can just call off and on something else.

  • We can call them zeros and ones.

  • And so this really is the germ of an idea

  • that gave us computers, and with it, their use of the binary system.

  • If, at the end of the day, all they have is physical input as electricity,

  • well, let's just use that to harness and keep track of information.

  • Let's store a little bit of electricity when we want to represent a one,

  • and let's let go of that electricity in some sense

  • when we want to represent a zero instead.

  • And so because the input to computers is so simple,

  • thus gives us the zeros and ones that we now use.

  • But we seem to have created a problem for ourselves.

  • If we only have one light bulb or one switch, if it's off,

  • it might be zero, if it's on, it might be a one,

  • but how do I count higher than one?

  • That problem still fundamentally remains.

  • Well, I could, of course, use more light bulbs.

  • So let me ask this.

  • If we were to use three light bulbs, how high could we count?

  • So with one light bulb, we can count from zero to one, two possibilities.

  • But with three light bulbs, how high could we count?

  • Let me go ahead and ask this question here on the screen.

  • In just a moment you'll see on your side this particular question via which

  • you can respond on your device.

  • How high can you count with three light bulbs?

  • So instead of one, I give you three, each of which can be on or off.

  • How high can we, perhaps, count?

  • So you'll see on the screen here the answers coming in.

  • We have a lot of folks thinking, 60-plus percent that it's

  • eight is the highest you can count.

  • A lot of you think it's seven, and some of you

  • also think it might be three or two.

  • So that's actually an interesting range of answers.

  • And let's see what might actually be the case.

  • Well, let me cut back over to three actual light bulbs here, all of which

  • are off.

  • And most naively, I think, if we were to turn these light bulbs on,

  • if they currently represent zero, obviously, I could turn one on

  • and we could call it one.

  • Then I could turn the second one on and call it two, turn on the third one,

  • and now with all three on, we could say now we're representing three.

  • But we're not really being clever enough just yet, if we're only

  • counting as high as three.

  • Because I'm just turning them on, in this story, left to right.

  • But what if we were a little more clever?

  • Maybe we turn them on right to left, or maybe we kind of permuted them

  • in different directions?

  • That is, we took into account not just how many bulbs are on

  • or how many fingers are in the air, but rather the pattern of on

  • and off light bulbs that we've created.

  • So let's just count this up.

  • So let me somewhat systematically turn some of these bulbs on here,

  • albeit virtually.

  • Here might be one, here might be two, here might be three.

  • But then we're kind of done with that story.

  • So how might we do it a little better?

  • Well, let's start again at zero.

  • Here might be one.

  • Why don't we call this two?

  • Why don't we call this three?

  • Why don't we call this four?

  • Call this five, this six, and this seven.

  • Now, it's fine if you didn't quite see what pattern I was following,

  • but take my word for it that that was a unique pattern of light bulbs,

  • eight total times.

  • I started at off, off, off, and I ended at on, on, on.

  • But along the way, there were, indeed, eight.

  • But how high can I count?

  • Well, it kind of depends on what number you start counting from,

  • and just as we thus far have been doing, computer scientists do all the time.

  • Computer scientists and, in turn, computer programs,

  • typically start counting from zero, just because it makes sense

  • because when everything is off, you might as well call that zero.

  • So if we start counting at zero, and we have eight possible patterns

  • that we just saw pictorially, well, that would

  • allow us to count as high as seven.

  • So from zero to seven, so seven is the highest

  • we can count with three light bulbs.

  • So those of you who propose that seven was the answer, 36% of you

  • were indeed correct.

  • 57% of you who said eight are correct if you assume we start counting at one,

  • and that's fine.

  • But at least in the computing world now, we'll generally, by convention,

  • start counting from zero.

  • But you are correct to say that there's eight such possibilities.

  • All right, well, this is all fine and good

  • to represent things with patterns of light bulbs.

  • But how do we actually now get to the zeros and ones

  • that a computer is actually using?

  • Because what's inside of a computer, at the end of the day,

  • are not light bulbs but tiny, tiny little switches,

  • millions of little switches that can either be on, or one, or off, or zero.

  • Those switches happen to be called transistors.

  • And these days computers do have millions

  • of these things that can be on and off in different patterns.

  • So if you have the ability to turn on and off all of these switches, well,

  • what can we all agree on representation when it comes to using those switches?

  • How will we represent information with them?

  • Well, wonderfully, we don't really need to think very hard

  • or go past our very comfortable roots as kids.

  • If we consider for a moment not just zero and one,

  • but the whole decimal system, zero through nine,

  • that you and I all started our day with today.

  • How does that system work?

  • Well, here on the screen is 123.

  • So yes, you're probably thinking that's one hundred twenty three,

  • but not quite.

  • All I've shown on the screen is a pattern

  • of symbols, 123, or three digits.

  • And all of us probably are instinctively just saying, obviously,

  • it's a hundred and twenty three.

  • But it's probably been years since you considered

  • why it is one hundred twenty three.

  • Well, let's consider what each of these digits or symbols represents.

  • If you're like me, you grew up learning that the rightmost digit is the ones

  • place, the middle is the tens place, the left one is the hundreds place.

  • And so how do we get from these three symbols or digits,

  • 123, to the mathematical idea we know as one hundred twenty three?

  • Well, all of us instantaneously, these days, did 100 times 1 plus 10 times

  • 2 plus 1 times 3, which, of course, is just 100 plus 20 plus 3,

  • or the mathematical value we all know as one hundred twenty three.

  • So a bit of a circular argument, but just to remind us

  • how we got from 123 to one hundred twenty three.

  • Well, it turns out that in the world of computers, the system

  • they use is exactly, fundamentally the same.

  • The only difference is that computers only have access to zeros and ones,

  • not zeros through nines.

  • So if we consider now in the abstract, just three possible digits

  • represented here, let's consider for a moment why those columns are places

  • where one, 10, and 100, and so forth.

  • Well, why was that the case?

  • Well, there was a pattern, in fact, and it just

  • has to do with exponents or powers.

  • So the rightmost column, technically, if we really get into the weeds,

  • is 10 to the zeroth power, which if you recall,

  • just means one, 10 to the first power, which is just 10,

  • and 10 to the second power, or 10 squared, is 100.

  • But what's interesting about representing it in this way

  • is that it jumps out that 10 is involved.

  • There's 10 digits, zero through nine, so the columns are using this base of 10.

  • So you can perhaps now get even ahead of me

  • here by considering, well, if in the binary system that computers

  • use, you only have two digits, zeros and ones,

  • odds are the only thing that's going to change is the meaning of these columns.

  • Now we have the ones place still, because 2 to the zero is one,

  • but then we have 2 to the first, 2 to the second, and so forth.

  • And of course, if we just do out that math,

  • in the world of binary that computers use,

  • we have the ones place, twos place, fours place, and so forth.

  • And now we're good to go.

  • Even though we have to now think in a different base system,

  • now we can start counting more properly.

  • And now we can move away from the metaphor of light bulbs

  • and consider that if all of those light bulbs are off,

  • we're, again, just going to start thinking of those things as zeros.

  • So that would be a pattern of symbols or digits that's 000 in binary.

  • But in our human world, the mental math you

  • would probably do now instantaneously after today

  • would be, well, that's obviously 4 times 0 plus 2 times 0 plus 1 times 0,

  • or, of course, zero in decimal.

  • But how does a computer represent the number one, for instance?

  • Well, it's just going to change that rightmost bit from a zero to a one,

  • or, more metaphorically, it's going to turn that switch on and illuminate

  • that rightmost light bulb just like I did earlier.

  • How do I represent two?

  • It's going to be 010 in binary.

  • How do I represent three?

  • This is where we're about to differ.

  • Now I'm putting on two of those switches,

  • because I need something in the twos place and the ones place to give me,

  • mathematically, three.

  • Next, if we go ahead and choose--

  • count up to four, that's going to be 100.

  • if I want to count up to five, that's going to be 101,

  • six is going to be 110, and finally, the number seven is going to be 111.

  • So it would seem that using three bits, each of which can be a zero or one,

  • yes, you can permute them in eight different ways.

  • Two possibilities for the first times two for the second times two

  • for the third gives us eight.

  • But as per this math and the intuition of starting counting from zero,

  • we can only count up as high as seven in total.

  • Well, let's go ahead and actually take this out for a spin.

  • When we don't have just, say, let's say, one light bulb or three light bulbs,

  • we have, actually, the fortune of having like

  • a whole stage worth of light bulbs.

  • 64 light bulbs adorn the stage here.

  • And you know what?

  • Sumner, could we go ahead and put up a random number on the screen here?

  • All right, so if you can see these light bulbs from your perspective,

  • we have eight light bulbs plus another bunch of them,

  • and all the others are off.

  • So let's go ahead and ask a question then.

  • If these light bulbs now represent not just one light bulb or two or three,

  • but several more-- in this case, at least six light bulbs,

  • what value do we actually get?

  • Well, let me go ahead and put a question on the screen here,

  • which should pop up on yours in just a moment.

  • And you should see now on your end this same question.

  • Put in binary terms, what number--

  • in decimal, does binary number 110010 represents?

  • What decimal number does binary number 110010 represent, from left to right?

  • So here we have an overwhelming response.

  • 50 is indeed the correct answer.

  • Now why is that?

  • Well, if I go over to the physical light bulbs here, let's

  • just consider for a moment what the pattern actually is.

  • This here is the ones place, the twos place, four, eight, 16, 32,

  • and we could keep going.

  • But it's not going to matter because they're all off.

  • So we have 32 plus 16 plus 2, which indeed gives us

  • the number you and I know in decimal as 50.

  • And just imagine how high we could count with all of the other light bulbs

  • as well.

  • All right.

  • So we started with the story with electricity.

  • We then moved on to numbers and representing things,

  • either in decimal or in binary.

  • But we've kind of painted ourselves into a corner,

  • because if we only have at our disposal switches or the metaphorical light

  • bulbs, which we can think of as zeros and ones,

  • it would seem that the only things computers can do is compute.

  • That is, behave as calculators.

  • And in fact, early on, that's exactly what computers were designed to do,

  • was really facilitate mathematical calculations that were otherwise quite

  • tedious or impossible for humans.

  • But, of course, what you and I are using right now,

  • what we use every day on our phones and our laptops and desktops is much more

  • sophisticated.

  • So let's consider how could a computer represent not just numbers,

  • but letters of the alphabet.

  • Brian, could we call on someone for this one?

  • If you'd like to raise your virtual hand,

  • how could a computer go about representing letters of an alphabet

  • like English if, again, all we have at our disposal is switches?

  • AUDIENCE: We can assign the numbers that we're getting from binary

  • to specific letters of the alphabet.

  • DAVID J MALAN: Yeah.

  • We can assign the specific numbers in binary to letters of the alphabet.

  • That's pretty much our only option, it would seem.

  • If we only have the ability to permute these switches or light bulbs or bits,

  • well, we just all have to agree how to represent letters in the same way.

  • Now, maybe the simplest way for us to do this would be, you know what?

  • Let's just all agree that a capital A is going to be the number one.

  • So you turn on one light bulb, or represent the binary number one.

  • Well, how about for B, we could use the number two.

  • For C we could use the number three.

  • D could be four, and so forth.

  • We all just have to agree to number the letters in that way.

  • But it turns out humans did exactly that,

  • but a little bit differently years ago.

  • They decided for reasons that we won't get into just now,

  • that, actually, the capital letter A is actually

  • going to be represented by the decimal number you and I know as 65.

  • Now in bitwise form, that's going to look like this.

  • So this is the pattern of bits that a computer would

  • use to represent the decimal number we now know as 65,

  • and now what the computer is going to do is just be mindful of what

  • type of program you're using.

  • So yes, if you're using a calculator or maybe using something like Excel

  • to crunch numbers, well, in that context when running software,

  • like a calculator or a spreadsheet program doing numerical analysis,

  • the program is going to see inside of the computer's hardware

  • the pattern of switches that represents the decimal number 65.

  • And because it's in the context of a calculator or spreadsheet, what

  • you, the human, might see on the screen is literally the decimal number 65.

  • But if you and I are using text messaging or email or any number

  • of social media apps where we're communicating

  • not numerically but in letters, say, English letters,

  • in that context your computer is going to be smart enough

  • to know, well, that same pattern of bits that represents 65,

  • in the context of a text message or in an email or the like

  • actually represents the capital letter A. So the pattern is the same.

  • The representation is the same.

  • But the context is what differs.

  • And the system that humans came up with years ago that maps 65 to A, 66 to B,

  • 67 to C, is called ASCII, the American Standard

  • Code for Information Interchange.

  • And that just means that there is a well-defined mapping that a bunch

  • of humans decades ago decided on, in order to map letters of the alphabet--

  • English in this case--

  • to numbers starting with 65.

  • And there's a whole mapping, too for punctuation, for lowercase letters,

  • and the like.

  • So given that, suppose that you did receive a text message containing

  • a pattern of bits, or, really, just a sequence of decimal numbers that

  • happened to be this.

  • 72, 73, 33.

  • Suppose that you received a text message containing these patterns of numbers.

  • 72, 73, 33.

  • What message might you have just received?

  • Let me go ahead and pull up the abbreviated chart here

  • to consider exactly what message you've received.

  • 72, 73, 33.

  • And Sumner, could we go ahead and throw this same three-letter word

  • on the lights?

  • If you'd like to see it in bitwise form, so to speak,

  • it will appear here on these light bulbs now as well.

  • What pattern does this represent?

  • Lanham, can we go to you?

  • AUDIENCE: That would be HI with an exclamation point, correct?

  • DAVID J MALAN: Yeah so it's indeed HI with an exclamation point.

  • And it's probably pretty easy now, in retrospect,

  • to glean that, yes, the 72 and the 73 were H and I respectively.

  • But Lanham also noted the exclamation point, which isn't in this chart,

  • but per the dot dot dots, there is a well-defined mapping

  • for all of the letters of the alphabet that we might care about.

  • And so HI is perhaps more obvious than the other.

  • That 33, we need a bigger chart.

  • And so if you actually go on your computers

  • now to asciichart.com, asciichart.com, you'll

  • see a little something like this.

  • Though you can also just google ASCII in general

  • and get copies of the same chart.

  • You'll see here that H is indeed 72, I is indeed 73,

  • but if we look to the left, 33 is, apparently, an exclamation mark.

  • And you would only know that by having looked it up or just having

  • committed it to memory.

  • But the computers you and I use and the phones you and I use just

  • know this intrinsically.

  • That's, indeed, how they're programmed.

  • But it turns out, too, that we should consider

  • just how many zeroes and ones we're using now

  • to represent the 72, the 73, and the 33.

  • So let's look for one last time at the binary representation, which,

  • as per the light bulbs, are these patterns of bits here.

  • So when you receive a text message from a friend saying HI!

  • H-I exclamation point, in all caps, you're

  • technically receiving a pattern of bits, some kind of frequency,

  • if it's wireless, that represents this pattern of bits.

  • And typically, computers these days use eight bits

  • to represent each of those characters.

  • When ASCII first came out, they typically

  • used seven for efficiency reasons, because space was expensive back then.

  • But here we used eight, and, indeed, that's now

  • the norm when it comes to representing characters in multiples of eight.

  • So we have eight bits here, eight bits here, eight bits here,

  • which means to receive the message HI! you are sending or receiving 24 bits

  • total.

  • Now, frankly, bits are not a very useful unit of measure,

  • typically, because they're so small.

  • Just a zero or a one.

  • But each of these patterns of eight bits, actually

  • have a vocabulary word, if you will, which is bytes.

  • And odds are, all of us have used this term in some context,

  • but generally in the context of megabytes or even gigabytes.

  • Indeed when you talk about the sizes of your files these days,

  • you're speaking in bytes in some form, either million or billion bytes.

  • But each of those bytes, quite simply, is a pattern of eight zeros and ones.

  • So, in fact, if we have as many as 64 bulbs at our disposal,

  • that's 64 divided by 8.

  • That's eight characters.

  • So it would seem we could spell on this stage, even an eight-letter word--

  • if, Sumner, we could put up a random eight-letter word,

  • that we'll keep up now--

  • can you now spell from left to right, your left

  • to your right, an eight-letter word using the system known as ASCII.

  • But, of course, we're being a little bit biased here,

  • as ASCII is the American Standard Code for Information Interchange.

  • And on a typical US English keyboard, there's more characters, certainly,

  • than uppercase letters, like A through H and I.

  • There's also some punctuation and some numbers, but there's also quite a bit

  • missing as well.

  • And any of you who are elsewhere in the world, odds are,

  • would find using a keyboard like this especially limiting or frustrating.

  • Why is that?

  • What seems to be missing from ASCII?

  • What seems to be missing from ASCII?

  • Well, let me ask this one other question here.

  • If we do use ASCII, and we therefore give ourselves eight bits or one byte,

  • how many different characters could we potentially actually display, actually

  • represent?

  • So on your screen, you should see this question now.

  • How many symbols can you represent with eight bits?

  • How many symbols can you represent with eight bits?

  • And this speaks to, really, at the end of the day, how

  • many letters of the alphabet plus punctuation,

  • plus uppercase and lowercase, can ASCII, or really, can computers support?

  • Well, it looks like 72% or so of you think that the answer is 256.

  • And it is indeed the case that you can represent 256 possibilities.

  • Why?

  • You can actually do out the math.

  • If you've got eight bits, each of which can be a zero or a one,

  • that means you have two possibilities for the first,

  • times two possibilities for the second, times two times two times two.

  • That happens to be 2 to the eighth, or 256.

  • It's fine if that's not immediately obvious,

  • but if you do have eight bits, each of which can be one of two values,

  • you can come up with 256 possibilities.

  • Those of you who chimed in to say that the answer is 255 in this case,

  • are wrong, only because now we're talking about the total number

  • of patterns, which is indeed 256.

  • But the highest value we could represent with eight bits or eight light bulbs,

  • it would seem to be, indeed, 255.

  • And that's because of all of the different patterns we can permute.

  • But let me open the question to the audience now.

  • Why might a US English keyboard be especially limiting,

  • and in turn, why is ASCII really not quite appropriate

  • when it comes to representing human language,

  • even though this is what computers began with years ago?

  • What is missing from ASCII?

  • Why might 256 total possibilities not be sufficient?

  • Kevin, can we go to you?

  • AUDIENCE: Sure.

  • I mean, for one thing, missing a lot of the accents in other languages.

  • But if you just consider, like, Asian languages,

  • there are a lot more than 256 characters.

  • DAVID J MALAN: Exactly.

  • So not only are we missing accented characters

  • that you might need in some languages, we're

  • also missing the characters that you might need in Asian languages,

  • in languages like Arabic and the like.

  • There are way more symbols that we humans use to communicate in print

  • and electronically than 256.

  • English, we can get away with fitting into this keyboard,

  • but not once we introduce things like these characters,

  • let alone other symbols as well.

  • And it turns out there's other things we humans like to say these days

  • and express using characters that have come into vogue, which is, namely,

  • these things.

  • Odds are, probably sometime today you have

  • sent or received one of these things here, otherwise known as an emoji.

  • Now, even though these emojis look like pictures, they look like images--

  • and they are, technically-- the way they're implemented in computers

  • is actually as patterns of zeros and ones.

  • These are actually just characters in an alphabet, the emoji alphabet.

  • Which is to say there's some pattern of zeros and ones

  • that represents each one of these faces, and the many other emojis that

  • nowadays exist.

  • And this is because the world has transitioned over the years from ASCII,

  • which only used seven, and in some sense,

  • eight bits total to represent all possible characters,

  • to using either eight or 16 or 24 or even 32 .

  • Bits nowadays there's a system called Unicode, which humans have come up

  • with that support not only English, but also all of the human languages,

  • is the aspirational goal, both written in print or electronically is the goal.

  • And in addition to that, this is to say we can represent things like this.

  • So this is the so-called face with tears of joy.

  • And this face of tears of joy, as of last year,

  • was the most popular emoji sent via text messages, emails,

  • social media, and the like.

  • But at the end of the day, all you're receiving

  • is, like, a key on a keyboard.

  • So, in fact, you wouldn't know it to look at it.

  • But in fact, the decimal number representing this face

  • with tears of joy happens to be 128,514.

  • So to Kevin's point, to represent not only certain human languages,

  • but certainly these emojis, we need way more than 256 characters

  • so we can use not just eight bits, but 16 or 24 or 32.

  • That's a huge amount of possibilities now.

  • In fact, now, to really take the fun out of these things,

  • if you receive that face with tears of joy or send it,

  • you're technically just sending a pattern of bits that looks like this.

  • That's all that's going on underneath the hood,

  • every time you use these things.

  • All right.

  • So we started again with electricity.

  • We then represented numbers.

  • Now we have the ability to represent letters and even

  • emotions in the form of emojis.

  • What else is there out there?

  • Well, the emojis themselves, of course, at least the ones we've looked at,

  • are pictorial in nature.

  • And so that invites the question, how does a computer

  • represent things like color?

  • Like, that face with tears of joy had a lot of yellow in it.

  • So how is yellow or any color, for that matter, represented in a computer?

  • Well, let me ask the audience again.

  • If all you have at your disposal is bits, zeros and ones,

  • and we just as humans need to agree how to represent colors,

  • what might be one possibility?

  • It doesn't need to be the answer.

  • But what might your own instinct be if designing this for the first time

  • yourself?

  • How might a computer represent colors now?

  • Yasmin, what do you think?

  • AUDIENCE: You would like members to different colors and shapes

  • and just do the same system.

  • DAVID J MALAN: Yeah, exactly.

  • Perfect instincts.

  • You would just assign numbers to the different colors,

  • and we all just have to agree on what that mapping is actually going to be.

  • So it turns out there's different ways to do this.

  • And if any of you are artistic and use Photoshop or the like digitally,

  • you're probably familiar with acronyms like RGB, red, green, blue.

  • But there are other acronyms and other ways

  • to implement Yasmin's idea where we just somehow map

  • zeros and ones to actual colors.

  • Well, RGB just happens to represent red, green, and blue.

  • And this is a system humans came up with years ago that says, you know what?

  • We can actually get every color of the rainbow

  • by mixing together some amount of red and green and blue light, essentially.

  • So that just invites the question, well, how do we represent the amount of red,

  • how do we represent the amount of green, and how do we

  • represent the amount of blue?

  • And we have, as Yasmin says, bits at our disposal.

  • So we just have to decide how to do this.

  • So suppose we receive a pattern of bits, that 72, 73, 33 again,

  • but this time it's not an email.

  • It's not in a text message.

  • It's in the context of a file that I've opened in Photoshop.

  • So it's as though I've opened up a photograph that someone

  • sent me and I want to do some editing and I see this pattern of numbers,

  • or, in turn, bits.

  • Well, what is that representing in this case?

  • In the context of an email or a text message, it's still HI!

  • But in the context of Photoshop or Instagram

  • or anything that is oriented around images,

  • it's actually going to represent some amount of red, some amount of green,

  • some amount of blue.

  • And as we discovered earlier, the total number

  • of possibilities you can represent with eight bits happens to be 256.

  • The highest value you can represent is 255 if we start counting from zero.

  • So this is to say that each of these three numbers

  • is a number between zero and 255.

  • So 72 feels like a medium amount of red, 73 is like a medium amount of green, 33

  • is a little bit of blue.

  • And if you combine those three amounts of color, eight bits plus eight

  • bits plus eight bits, using 24 bits total,

  • using the first third to represent redness, the second third greenness,

  • and the third third blueness, you get, it turns out,

  • a dot that looks like this, a yellow dot.

  • And so, indeed, that emoji, when it's being displayed on the screen,

  • is the result of the computer interpreting--

  • the 128,514 value is knowing oh, that's the emoji

  • with the face of tears of joy.

  • But when it comes to displaying the information on your screen,

  • now your computer is going to be using different patterns of bits

  • to control the colors of the dots on the screen.

  • And this term you might already know.

  • The dots you and I see on our computer screens or even TVs these days

  • are called pixels.

  • They're tiny little squares that represent some color

  • such as this yellow one here.

  • And you can actually see them in some contexts.

  • If I go ahead and pull up the same face with tears of joy and zoom in a bit,

  • zoom in a bit more, and really zoom in a bit more,

  • now you can actually see what we call pixelation.

  • And odds are, you have seen this on Facebook, Instagram,

  • wherever you might be resizing or editing photos that don't quite

  • have enough resolution.

  • The resolution of an image is just how many pixels or dots there

  • are horizontally and vertically.

  • So if you really zoom in on an image, you'll eventually see those pixels.

  • And this is to say that even in this zoomed-in happy face,

  • there's a huge number of yellow dots and a whole bunch

  • of black and gray and brownish dots as well

  • that compose this very colorful image.

  • And so you can see them in that case, and every one of those dots now,

  • a pixel, is using, I claim, like 24 bits or three bytes.

  • Now, you can imagine, there's probably what, hundreds, maybe thousands of dots

  • in that image if we zoom out and look at all of them again.

  • So if every one of those dots or pixels is three bytes,

  • this is why the photographs you and I take

  • and the images you and I download from the internet

  • are typically measured not even in bytes, per se, but in kilobytes,

  • for thousands of bytes, or megabytes for millions of bytes,

  • or if it's a video file, it might get even bigger, billions, or gigabytes.

  • But that's all that is happening underneath the hood.

  • We're just representing information in this way.

  • Well, let me ask a follow up question now.

  • If we've now, thanks to Yasmin, represented colors,

  • and in turn, images, because all an image is is a grid of pixels.

  • You take the same principle Yasmin proposed,

  • where you represent each color of a dot and you have a whole bunch of dots that

  • gives us images, how would you propose computers represent video files?

  • Again, even if you don't know the answer, how might

  • a computer represent video files now using, again, only bits

  • at their disposal?

  • Who might like to field this one?

  • How might a computer represent a video?

  • Justin, what do you think?

  • AUDIENCE: I-- maybe just, like, rapidly changing the bites?

  • DAVID J MALAN: Just rapidly changing the bites.

  • I hear-- can you elaborate a little bit?

  • What do you mean by changing the bites?

  • AUDIENCE: Like rapidly changing the RGB of individual pixels--

  • DAVID J MALAN: Exactly.

  • AUDIENCE: --to match the image of that second

  • of the video or portion of the video.

  • DAVID J MALAN: Perfect.

  • So if you think about, like, the rectangular screen that is your phone,

  • or your laptop, or your desktop monitor, if you just

  • keep changing the colors of those dots once per second

  • or a whole bunch of times per second, we'll

  • get the illusion that there's actually motion on the screen, ergo video.

  • So really, a video, in some sense, it's just a whole bunch of images,

  • to Yasmin's definition, flying across the screen really quickly.

  • And so you can see this even old school style.

  • For instance, let me go ahead and open up on my screen

  • a short video that represents a flipbook.

  • So you might have made one of these as a kid or maybe your teacher

  • did or you saw them, at least, in person somewhere.

  • Where if you take a whole bunch of pieces of paper and staple

  • or clip them together in some way, draw a whole lot of pictures, all of which

  • are similar but slightly different on each page,

  • you can create an animation, or, really, a video.

  • And this is all a video is in a purely electronic world.

  • Even though this happens to be implemented

  • in paper, what happens in the computer world

  • is indeed just a whole sequence of images

  • flying across the screen at some rate.

  • And that's what actually gives us the video files that you and I know today.

  • And there's even more rabbit holes we can go down.

  • For instance, how might you represent music?

  • Well, music, could be represented, gosh, in different ways.

  • Like, if you play the piano, for instance, you

  • might know that there are notes, like A through G.

  • But there's also sharps and flats and so forth.

  • But you know what?

  • Maybe we just need a number to represent each of those possible notes.

  • And maybe also we could use another number,

  • just like images use multiple numbers to represent dots,

  • we could use a number to represent the notes in a song,

  • but also another number to represent the duration of that note.

  • How many seconds or milliseconds or beats should you hear that note for.

  • So you could come up with other formulations, too,

  • but music, really, can be quantized in the world of computers

  • into just small pieces of information.

  • And so long as you and I agree on how to represent it,

  • that's how these things all work.

  • And if you've ever wondered why there are JPEGs and PNGs and GIFs and Word

  • documents and Excel files and all of these different file formats or file

  • extensions on computers, those file extensions or formats just

  • represent a whole bunch of humans agreeing

  • how to store patterns of zeros and ones in a file

  • so that when those zeros and ones are loaded into a computer for display

  • or for interpretation, it knows what those patterns represent.

  • Images are represented slightly differently,

  • sound and video are represented slightly differently,

  • but it's all zeros and ones at the end of the day.

  • So this is all to say, so long as we all agree, ideally around the world,

  • how to represent information, now we can represent inputs to problems

  • and hopefully solve problems and get outputs.

  • So all that remains in problem solving, or really, computer science broadly,

  • is to look inside of this black box and to consider how you take inputs,

  • whether it's numbers, letters, images, video, sound,

  • and convert them into actual solutions.

  • And so inside of this black box is what we would typically

  • describe as algorithms.

  • Algorithms are step by step instructions for solving problems.

  • They don't even have to involve computers.

  • We humans can execute algorithms just by following someone else's instructions.

  • If you've ever prepared something from a cookbook, following a recipe,

  • you are executing an algorithm step by step.

  • But unlike a lot of recipes or unlike a lot

  • of instructions that we humans give to each other,

  • there's no room for ambiguity in computers.

  • Computers' algorithms, when implemented by machines,

  • they really have to be not only correct so

  • that you get the right outputs that you care about,

  • but they also need to be precise.

  • You need to be ever so precise, because unlike we humans who can kind of like

  • read between the lines and, yeah, I get what you mean,

  • computers are going to take you literally.

  • And so when programming a computer, that is, translating an algorithm,

  • step by step instructions, into some language the computer understands,

  • the onus is on you to make sure that the computer cannot misinterpret what you

  • want.

  • So let's consider one such algorithm.

  • So on all of our phones, whether iOS or Android or the like,

  • you have some contacts application.

  • And that contacts application's probably storing all of your friends

  • and family members and colleagues, probably alphabetically.

  • Maybe by first name, maybe by last name, or however

  • you've organized that device.

  • Well, the old school version of this happens

  • to be in paper form, which looks a little something like this, a phone

  • book.

  • And inside of an old school phone book really is that exact same idea.

  • It's much larger.

  • It's much more much more printed.

  • But it's the same thing.

  • There's a whole bunch of names and numbers in a typical phone book,

  • sorted alphabetically just like your own Android phone or iOS

  • phone might be as well.

  • So suppose we want to solve a problem.

  • And the input to that problem is not only this phone book, but also

  • the name of someone to look up the number for.

  • So my own name, for instance.

  • If I want to look up my phone number, or you do, you might open up this book

  • and start looking for David, for instance,

  • if we assume that it's sorted by first name.

  • I don't see David on the first page, so I move on to the second.

  • I don't see myself there, so I move on to the third.

  • I don't see myself there so I move on to the fourth.

  • And so forth, one page at a time, looking for my name and, in turn,

  • my number.

  • Well, if correctness is important-- let me ask that question first.

  • Is this algorithm, turning the pages, step by step,

  • looking for David correct?

  • What do you think?

  • Within Zoom, you should see some icons under the participants

  • window labeled yes and no.

  • If you'd like to go ahead and vote virtually, yes or no,

  • is this algorithm correct?

  • One page at a time, looking for myself.

  • Never mind the fact that this is yellow pages,

  • and so I'm not going to be anywhere in the phone book,

  • but indeed, we'll assume it contains humans as well.

  • All right.

  • So it looks like the algorithm is indeed correct,

  • but it's terribly, terribly slow.

  • And that's OK, because one of the ideas we're

  • going to consider in CS50 and in turn, computer science,

  • is not only the correctness of an algorithm, but also the efficiency.

  • How well designed is the algorithm?

  • This is correct.

  • It's just incredibly, incredibly tedious and slow.

  • But I will find myself.

  • But, of course, we can do better.

  • Instead of looking for myself one page at a time, why don't I do one page,

  • let me do two, four, six, eight, 10.

  • It sounds faster and it is faster.

  • I'm going twice as fast through the phone book looking for myself.

  • Is this algorithm correct?

  • Let me go to someone in the audience this time.

  • Is this algorithm of searching for someone's name two pages at a time

  • correct?

  • Because I claim it's more efficient.

  • I claim it's better designed because I'll solve the problem twice as fast.

  • Aneka, what do you think?

  • AUDIENCE: No, because you might skip your name on a page.

  • DAVID J MALAN: Yeah, I might skip my name on a page.

  • And let me ask a follow up question.

  • Can I fix this?

  • Do I have to throw out the whole algorithm

  • or can we at least fix this problem, do you think?

  • AUDIENCE: I think whatever page you flip to, it would help to see,

  • like, what name is there and maybe see if your name would

  • come before or after.

  • DAVID J MALAN: Nice.

  • So that's exactly the right intuition.

  • I don't think we have to completely sacrifice the idea of speeding up

  • this algorithm by moving twice as fast.

  • But as you propose, if I go too far-- maybe I get to the E section,

  • which is one letter too late--

  • I should at least double back one page.

  • Because I could get unlucky, and maybe David

  • is kind of sandwiched in between two pages, at which point

  • I might fly by, get to the end of the phone book, say, no, there's no David,

  • and I just got unlucky with 50% probability.

  • But as you propose, I can at least recover and sort of conditionally

  • ask myself, wait a minute, maybe I just missed it, and double back.

  • So I can get the overall speed improvement,

  • but then at least fix that kind of mistake or bug.

  • And bug, a term of our-- in programming, a bug

  • is just a mistake in a program, or a mistake, more

  • generally, in an algorithm.

  • But honestly, none of us are going to do that.

  • When we actually go to search for someone in a phone book,

  • just like our phones do, they typically don't start at the top

  • and go to the bottom.

  • And computers do exactly what you might do more intuitively.

  • They'll probably go roughly to the middle.

  • Maybe they'll skew a little to the left, if you know

  • D is toward the start of an alphabet.

  • But, no I open to the middle sort of sloppily, and I'm in the M section.

  • So what do I know when I'm in the M section about this problem?

  • Let me call on one more person.

  • I'm in the M section.

  • What would you do as a human now, taking this as input to solve this problem?

  • What do I know about the location, of course, of my name in the phone book?

  • What decision can I make here?

  • What decision can I make?

  • Kyle, what do you think?

  • AUDIENCE: Yeah.

  • So from the M onwards, you know that your name won't be there for sure.

  • DAVID J MALAN: Yeah, so my name is not going to be in the M section.

  • But thanks to the alphabetization of the phone book, I at least know,

  • you know what?

  • I can take a huge bite out of this problem

  • and tear the problem in half, both metaphorically and also literally,

  • in the case of a phone book.

  • And I can literally throw half of the problem away.

  • And so if I started with something like 1,000 pages in this phone book

  • or 1,000 contacts in my phone, just by going to the middle,

  • roughly, and taking a look to the left and the right, I can decide,

  • as you note, well, it's not on the page I'm looking for.

  • But I can decide it's to the left or to the right.

  • I know D comes before M. And so now I can go to the left.

  • And you know what's interesting here, is that I

  • can use that exact same algorithm.

  • I don't have to think any differently.

  • I can apply the same logic, open to the middle of this half of the phone, book

  • and now I see I'm in the G section.

  • So I'm still a little too far.

  • But again, I can tear half the problem away, throw it down

  • and now I've gone from, like 1,000 pages to 500 pages to 250 pages.

  • If I do this again, I might find myself, oh, I made it to the C section now.

  • I can tear the problem in half again, throw the left half away,

  • and now I'm down to just 125 pages.

  • Now, that's still a lot, but my god.

  • I've gone from 1,000 to 500 to 250 to 125.

  • That is way faster than going from 1,000 to 999 to 998,

  • and it's even faster than going from 1,000 to 998 to 996 to 994.

  • Both of those algorithms are going to take me much longer as well.

  • We have this visualization made by Brian, wonderfully,

  • that depicts 1,024 page phone book with one page being flipped at a time.

  • And now we're down to 996, 995.

  • I mean, honestly, this isn't all that enlightening.

  • It's going to take forever to find David or any name in a phone book

  • when starting at that kind of pace with that algorithm.

  • But what if, instead, I'm a little smarter

  • and I'm a little more intuitive?

  • And I harness the intuition that probably you had and I

  • start with 1,024 pages again, and this time

  • divide and conquer, half at a time, splitting the problem in half?

  • Tearing the phone book in half, I get down to just one page.

  • And if we actually do out the math, if you start at like 1,000-plus pages,

  • it will only take me 10 total tears of that phone book in order to get down

  • to my number, 949-468-2750.

  • So that just is to say that the third algorithm is not only correct, just

  • as the first one definitely was and the second one could be with that bug fix,

  • but it's also much better designed.

  • It's much more efficient.

  • And so we can see this a little graphically as well.

  • Let me go ahead and propose not a numerical analysis or anything

  • like that.

  • But just something that's a little visual like this.

  • So if I have an x-axis here that represents

  • horizontally the size of the problem, the number of pages in a phone book,

  • and vertically on the y-axis, the amount of time required to solve a problem.

  • What co these algorithms look like, if we just kind of chart them?

  • Well, the first algorithm, depicted here in red, it's just a straight line.

  • It's a slope of one because there is this one to one

  • relationship between number of pages and the amount of time

  • it takes me to solve it.

  • For every new page of that phone book, maybe year after year,

  • if the phone book grows, it's going to take me

  • one more step to look for myself or anyone else,

  • potentially, in that phone book.

  • Unless I get lucky and they're early in the phone book, but one more

  • page means one more page turn.

  • The second algorithm is actually better.

  • It's still a straight line.

  • So it's still a linear relationship.

  • But for every two pages in the phone book it takes me one more step.

  • Two pages, one turn.

  • Two pages, one turn.

  • So it's strictly better than the first algorithm.

  • Why?

  • Well, if we consider this-- if the size of the problem is,

  • maybe, here, for instance.

  • So if we assume, for the sake of discussion, maybe

  • the phone book has this many pages depicted with this dotted line.

  • Well, how much time is it going to take the second algorithm

  • to find someone in that phone book?

  • It's going to take this amount of time, right?

  • Where those two lines intersect.

  • If you're using the first algorithm, though, going one page at a time,

  • it's actually going to take this much time, which is literally twice as much.

  • So they're both correct, assuming we double back as needed

  • if I go too far past a name.

  • But both of those are sort of fundamentally the same.

  • They're the same shape, and, honestly, they both

  • felt slow to say and to act out.

  • The third algorithm, if we were to graph it,

  • has a fundamentally different relationship

  • between the size of the problem and the time required to solve the problem.

  • The line goes up, up, up, up, as it should,

  • because the more pages there are, the more time it's going to take to solve,

  • but notice how much more slowly it goes up.

  • This thing barely starts to rise as the size of the problem

  • gets bigger and bigger and bigger.

  • And why is that, intuitively?

  • Well, here, what's powerful is, suppose that phone book, next year,

  • for whatever reason, doubled in size.

  • Maybe Cambridge and Allston, Massachusetts merged together into one

  • big phone book, so there's 2,000-some-odd pages now instead.

  • How many more steps would it take next year

  • to search for someone in that phone book?

  • One.

  • One more step.

  • And so if you look way out here along this green line,

  • doubling the size of the phone book, the line

  • itself is only going to rise ever so slightly because no big deal.

  • With that third algorithm you're taking much bigger bites out of the problem.

  • And so this, too, speaks to what computer science and what programming

  • are ultimately like.

  • Harnessing ideas that you come into the class with

  • and that you might use in your everyday life,

  • but you don't necessarily think about how you might represent problems

  • using those algorithms and how you might translate them to computer speak.

  • And indeed, one way we'll start to think about algorithms

  • is not only their correctness, but how well designed they are.

  • And so for instance here, I've deliberately

  • labeled these three lines n, n over 2, and log base 2 over n.

  • That just means that if we use n as number-- so computer scientists tend

  • to use n as a variable, much like a mathematician might say x or y or z,

  • n for number.

  • And so the first red line is the running time,

  • the number of steps it might take to solve a problem

  • might be, in the worst case, n.

  • If there's n pages in the phone book, maybe I'm looking for someone way

  • at the end of the phone book and it's going

  • to take me all n steps to find them.

  • The second algorithm is going to take half as many steps.

  • So we express that as n divided by 2, because if we're

  • doing two pages at a time we'll get to the end of the phone book--

  • if we're looking for someone whose name starts with Z, for instance--

  • twice as fast.

  • But the third algorithm, if you're a little rusty on the mathematics,

  • is represented as a logarithm with a base of 2.

  • And this just means that this graph, the green line

  • describes how much time it takes to solve a problem when on each pass,

  • on each step, you are dividing the problem, in this case, by half.

  • The other two algorithms are taking one or two bites out of the problem.

  • The third algorithm was taking half of the whole problem at a time.

  • And that's what made it all the more powerful.

  • So when it comes to programming now, we need

  • to translate these things called algorithms to code.

  • Or, in this case, let's call it pseudocode.

  • And in just a bit, we'll focus on an actual programming language,

  • albeit a graphical one.

  • But for now let's just consider some of the constructs or sort

  • of fundamental ideas that are going to be useful to leverage

  • here on out in this class.

  • So let me propose that what I really just did verbally

  • can be translated into pseudocode, which is like an algorithm implemented

  • in English, or whatever your spoken or written language is.

  • But the key is that it's got to be correct,

  • and ideally it had better be precise so that there's no ambiguity.

  • Step one was, indeed, what I did.

  • Pick up phone book.

  • Step two, open to middle of phone book.

  • Step three, look at page.

  • And indeed I did that.

  • And now things got interesting.

  • Step four, if person--

  • David, in my case-- is on the page, what do I want to do?

  • Well, I should probably call that person.

  • The problem is solved.

  • I've gotten my output, the person's number.

  • But there's another possibility, not if the person's on the page

  • but, rather if the person is earlier in the book--

  • and that is what happened a moment ago.

  • If I ended up on M, but I'm looking for David, that's to the left,

  • I should then do what?

  • Open to the middle of the left half of the book.

  • And that's indeed what I did.

  • And I sort of gratuitously tore the problem in half.

  • But algorithmically, I just looked at the left half of the book next.

  • What do I do next?

  • Well, really, that's the point at which I

  • proposed that the algorithm is now just repeatable, again and again,

  • and so we'll say go back to line three.

  • Why?

  • Well, starting at line three, I have an algorithm

  • for looking up someone in a phone book.

  • It just so happens the phone book now is half as large.

  • But there's another case.

  • What if the person is later in the book?

  • I wasn't searching for David, which starts with D,

  • but someone else's name that's toward the end of the alphabet.

  • Well, then if that person is later in the book, same idea.

  • Open to the middle of the right half of the book,

  • and then again, go back to step three.

  • But lastly, there's a fourth possibility.

  • There's a fourth possibility.

  • Either the person's in the phone book, or they're to the left

  • or they're to the right, or, frankly, they are just not there at all.

  • And this last point, though somewhat subtle, is so important.

  • Odds are all of us on our Macs, PCs.

  • Maybe even phones, have had that very frustrating experience where

  • your computer hangs, you get the stupid spinning beachball or hourglass,

  • the thing freezes or just reboots, you know, something goes wrong

  • and it's sort of inexplicable.

  • And you might think it's your fault, but really it's

  • usually the programmer's fault who wrote the software that you're

  • using on your computer or your device.

  • Why?

  • Very often, that programmer, for whatever reason,

  • did not anticipate a possible scenario.

  • In this case, there's four scenarios, but you

  • could imagine kind of forgetting the fact that, oh, well maybe David's

  • not even in this phone book.

  • But you'd better handle that scenario.

  • And when you have a computer that freezes or hangs

  • or reboots or just something goes awry, that

  • is quite often quite simply because a human did not

  • code for some possible scenario.

  • So what are the fundamental constructs we've

  • seen here that we're going to continue seeing in class?

  • Well, highlighted in yellow now are really some verbs or actions

  • that we exercised with that phone book.

  • These are, in general, in programming called functions.

  • A function is an action or a verb.

  • It's a statement that gets the computer to do something.

  • Next highlighted here are what we'll call conditions or branches.

  • These are sort of the proverbial forks in the road.

  • You could either do this or this or maybe this other thing.

  • And you can have one decision to make or two or three or four,

  • however many conditions make sense logically.

  • We'll call those conditions.

  • But how do you decide which fork in the road to take?

  • Whether to do this or that or this other thing?

  • For that we need something called Boolean expressions.

  • A Boolean expression it's just a question

  • whose answer is yes or no, or true or false, or, frankly, one or zero.

  • All of those would be equivalent for our purposes.

  • So person on page.

  • That's a yes or no question.

  • Person earlier in book?

  • That too is a question.

  • Person later in book is a third question as well.

  • So if you can imagine a yes-no answer, a true-false answer, a one-zero answer,

  • that is what gives us these things called Boolean expressions.

  • And then lastly, in yellow here are these things.

  • Go back to line three.

  • This will induce what we'll call a loop or a cycle,

  • which is just a programming construct or principle of an algorithm that

  • gets you to do something again and again so you

  • don't have to write 100-line algorithm.

  • You can write a 13-line algorithm and reuse parts of it again and again.

  • And so we'll begin now, and we'll begin CS50 with a look

  • at an actual programming language, one that you might have used recently

  • or as younger kids, known as Scratch, which is a graphical programming

  • language which, while it might be very familiar to some of you,

  • it actually represents a lot of these programming fundamentals

  • that we'll use as this ground for transitioning in just one week

  • to a more traditional more old school language,

  • known as C, which is entirely text and keyboard-based.

  • But we'll see in all of the languages we look at in CS50,

  • these things called functions and conditions, Boolean expressions

  • and loops, and today, in just a moment, we'll

  • also see some other features that we describe as variables, not unlike x, y,

  • and z in math, threads, which allow a computer to do, it would seem,

  • multiple things at once, events, and yet other features as well.

  • And so from here, we transition from pseudocode to actual code.

  • And what you see on the screen here is an example

  • of a language called C, where we'll spend a good amount of time

  • this semester.

  • This is the older school text-based, keyboard-based language

  • to which I referred earlier.

  • But this language is a bit cryptic.

  • And certainly at first glance, you might wonder why is the hash symbol there,

  • the angled brackets, the parentheses, the curly braces, the semicolon,

  • the quotes, I mean, my god, there is so much syntax to what is on the screen

  • now.

  • And you can probably guess what this program does.

  • Let me just go quickly to the audience.

  • What, anyone, does this program probably do, even if you've never

  • programmed a computer before?

  • AUDIENCE: It just prints out hello, comma, world.

  • DAVID J MALAN: Exactly.

  • It just prints hello, world.

  • And my god, like, look at all of the syntax and all of the keystrokes

  • we had to type just to command the computer to do that.

  • And so by contrast today is Scratch.

  • We'll allow ourselves for just today to look at something much more

  • friendly, much more graphical, that will allow us to explore these very ideas

  • and set the stage for more sophisticated, more traditional

  • languages next week and beyond, but in the context

  • where we don't have to worry about parentheses, semicolons, curly braces,

  • and where even these keys are on the keyboard.

  • So allow me to introduce you, then, to Scratch,

  • developed by some of our friends down the road

  • here in Cambridge at MIT's Media Lab.

  • You can play along at home here on out if you would like at scratch.mit.edu.

  • It's web-based, but there's also an offline version

  • if you tend not to have the best of internet.

  • But the user interface would typically look like this.

  • And a quick tour.

  • So here on scratch.mit.edu, when you go to create

  • a project via the button on the interface, you'll see first Scratch,

  • the namesake of the program, this cat who

  • lives in this little rectangular world in which you can move up,

  • down, left, or right.

  • But the cat can be transformed into any number of other characters,

  • or what we'll call sprites, visual representations thereof.

  • On the left here, now, are all of the building blocks that come with Scratch.

  • All of the programming constructs available to you

  • in the form of puzzle pieces.

  • And you'll notice that they're categorized according

  • to color and description and there's a whole bunch of puzzle pieces

  • that rather say what they do.

  • And today the goal is not to go into the weeds of all of these various puzzle

  • pieces, but to highlight some of the fundamental ideas that are possible.

  • And we'll explore those ideas via the middle of the screen here.

  • We'll be able, in just a moment, to start dragging and dropping

  • these puzzle pieces onto this larger screen

  • and interlock them together, if it makes logical sense to do so.

  • Finally, for the most sophisticated programs,

  • we can actually create yet more characters or sprites

  • and actually have a lot of interactions on the screen as well.

  • But let's go ahead and dive in with just an example quite quickly.

  • I'm going to go ahead on my screen and go, indeed, to scratch.mit.edu.

  • And you're welcome to play along at home as well.

  • And I'm going to click Create in order to get into exactly that interface.

  • You do not need to make an account from the get go unless you would like.

  • And let me go ahead and start creating a program.

  • The very first program that was once written, by lore,

  • was quite simply what Iris proposed as "Hello World," a program that

  • prints on the screen hello, world.

  • Well, how can we do that?

  • Well, I can probably do this quite quickly

  • because I've used the interface before, but the goal

  • for you at hand if you've never used this before,

  • with the course's first problem set or programming assignment, really

  • is just to get your hands dirty and explore and poke around.

  • And odds are, the ideas you are looking for, you'll find eventually pop out.

  • And the first one I'm going to try out is this one here.

  • This puzzle piece that's a little yellow or orange in color.

  • It's in the Events category, and it's called when green flag clicked.

  • This is of interest, because if I go to Scratch's stage over here,

  • you'll see at top left there's a green flag that's going to signify go,

  • and a red stop sign that's going to signify stop.

  • So if I want something to happen when I click that green flag,

  • I'm going to start with this puzzle piece here.

  • Now I'm going to go over into the Looks category.

  • And in the Looks category, there's a whole bunch of blocks.

  • But we're going to keep it simple here.

  • I'm going to go ahead and just say the canonical, as Iris noted, hello, comma,

  • world.

  • I'll zoom back out.

  • I'll move over to Scratch here, and I'm going to click now the green flag.

  • And voila, hello, world.

  • So that is my-- and perhaps, soon, your-- very first program,

  • using in this language Scratch.

  • But, of course, this isn't terribly interesting.

  • Might be gratifying for the very first time.

  • But it's not something you'd want to play again and again.

  • But we can make this thing much more interactive

  • and we can start to layer these building blocks

  • and have an algorithm more like searching that phone book,

  • that has multiple steps.

  • So let me go ahead and stop that program.

  • And let me explore a little bit instead.

  • Let me go under Sensing this time, this blue category.

  • And you'll see this block here.

  • Ask what's your name, and wait.

  • But notice that what's your name is in this white oval,

  • and that implies that I can change what the question is if I want,

  • but I'm fine with that question for now.

  • And let me go ahead and first get rid of these blocks,

  • and give myself when green flag clicked, and this time start under Sensing

  • with ask what's your name and wait.

  • But notice that this is kind of a special block.

  • It comes with a second block, a so-called variable.

  • It turns out that this ask puzzle piece is literally

  • going to ask the human who's playing this game a question,

  • and it's going to store the answer to that question in a variable, depicted

  • here as this blue oval, called answer.

  • Just like in math, an x, a y, or a z.

  • So what could I do with that.

  • Well, let me again go to Looks.

  • Let me go to say hello, but this time, you know what?

  • Let me go ahead and say hello, comma, and then-- all right,

  • let me give myself a second say block.

  • But I don't want to say hello again.

  • So I'm going to delete that.

  • But I'm going to go back to Sensing and I'm going to drag and drop answer.

  • Now it looks a little too big, but notice if I get close to it,

  • it sort of magnetically wants to connect.

  • And indeed, Scratch will grow to fill the puzzle piece for me.

  • So now I have a program, it would seem, a program written in Scratch,

  • a piece of software written in Scratch that's going to, when the green flag is

  • clicked, ask what's your name, and wait-- that's our function--

  • say hello--

  • that's another function-- and then it's going

  • to say answer, whatever the human typed in.

  • Well, let me go over to Scratch's world here and click the green flag.

  • Notice the cat is asking me what's your name.

  • I type in David and enter.

  • Huh.

  • I only see David.

  • Well, maybe I did something wrong.

  • Let me do it again.

  • Green flag, D-A-V-I-D, enter.

  • Hmm.

  • What's going on?

  • This seems to be a bug, because I'm pretty sure I have three functions,

  • ask, say, and say.

  • But I feel like I'm missing the second instruction.

  • Any thoughts on what bug I have made?

  • What might explain this?

  • Natalie, is it?

  • AUDIENCE: So you replaced the output with the same function.

  • DAVID J MALAN: Yeah.

  • I replaced the output with the same function.

  • And honestly, even though we're using a fairly simple program, Scratch,

  • my Mac is actually pretty fast.

  • And your PC or your Mac or your phone is pretty fast.

  • And even though Scratch is saying hello and saying answer, as Natalie notes,

  • the answer is sort of overwhelming to say, because I didn't so much as pause.

  • So I could go in and find a block-- there's

  • a wait block that could allow me to insert an arbitrary pause.

  • But I really want this to be one breath.

  • I want it to be hello, comma, David, all at once.

  • So how can I do that?

  • Well, let me go under Operations.

  • And it turns out there's a whole bunch of math-related things here,

  • but also some English or language-related things down here.

  • Join apple banana.

  • Now this has nothing to do with apples and bananas.

  • Those are just placeholders, but there's this puzzle piece here

  • that I can drag and drop.

  • And you know what?

  • Let me go ahead and do this.

  • Let me replace the first input to say, and let me join hello comma, and then

  • not banana, but let me drag the answer--

  • and notice that will drop in place.

  • Let me throw this other block away.

  • To delete things, you can just drag them over to the left and let go.

  • And now notice that I have a program that's asking what's your name

  • and then I'm going to say the result of joining hello and answer.

  • And let me go ahead and play this now, after stopping the old one.

  • What's your name?

  • I type in David, enter, and voila.

  • As Natalie notes, now it's not tripping over itself,

  • clobbering what was previously there.

  • Now I'm getting it all in one breath.

  • Now the program is getting a little more interesting,

  • but the paradigm is no different from before.

  • In fact, let me propose that everything we've just done

  • is fitting perfectly into this whole mental model of what

  • it means to solve problems and what computer science itself is.

  • So for instance, if this is the problem to be solved

  • and I've got inputs and outputs are my goal and an algorithm in between,

  • let's consider how Scratch even fits into this mental model.

  • My input to the very first program that we wrote a moment ago

  • was literally hello, world in its own oval.

  • The algorithm was implemented as a function in Scratch called say.

  • So an algorithm, step by step instructions,

  • a function is the computer's implementation of an algorithm.

  • In this case, a function called say.

  • The output, of course, was the cat saying hello, world.

  • But things got more interesting just now after Natalie's remark, whereby when I

  • introduce something like ask what's your name and then wait,

  • notice what happens this time in the model.

  • Now the input to the problem is what's your name--

  • that's the string that comes by default, and I could change it but I didn't.

  • That's being fed now into the ask block.

  • And the ask block's purpose in life is to get the cat

  • to give me an answer like this.

  • Now, that answer is interesting because I can now join it

  • in with the word hello as a prefix.

  • So this block is interesting because notice, the input,

  • the white oval to the say block actually has another puzzle piece and then

  • two more puzzle pieces on top of it.

  • And what's cool here is that when programming functions,

  • you can have the outputs of one function become the input to another function.

  • And so the flow here is quite simply this.

  • Now I have two inputs to the function, both hello, which I wrote,

  • and answer, which came from the ask block.

  • The algorithm in question now is the join function, which I just used.

  • And its output is hopefully going to be hello, comma, David.

  • But I don't want to see a white oval on the screen saying hello, comma, David.

  • I want the cat to say hello, comma, David.

  • So let me go ahead and focus only on the output.

  • Make it become the input to a final function, which is that say block,

  • and voila, now the cat says what I want it to.

  • So again, even as you start to nest, that is, place these puzzle pieces

  • one on top of the other, all we're doing is passing in inputs

  • and getting outputs.

  • Doing something with those outputs and making them inputs, and so forth.

  • That really is the paradigm, ultimately, of what it means to program.

  • But we can make the cat do more interesting things.

  • And just to have a little bit of fun with this,

  • let me go ahead and dig in to this bottom icon

  • at the bottom left of the screen.

  • Scratch has these so-called extensions, where you can really

  • make it do fancier things as well.

  • And let me go to Text to Speech at the top right.

  • So this is using a cloud-based service--

  • that is some internet-based service--

  • that's going to send the words that I type out on the internet.

  • The internet, some server there, is going to respond with a verbalization

  • now of what it is I just typed.

  • So let me go ahead and try this.

  • Let me get rid of the purple say function

  • and replace it with this speak block.

  • And let me go ahead and drag in the join puzzle piece

  • here-- notice it's going to grow to fill,

  • and I'm not going to use this one anymore.

  • This time I'm going to hit Stop and I'm going to go ahead

  • and hit Play once more and type in my name.

  • And--

  • COMPUTER: (FEMININE ROBOTIC) Hello, David.

  • DAVID J MALAN: OK, not a very natural cat sound,

  • but notice we can set the voice differently.

  • So notice I can drag this puzzle piece.

  • And you can even squeeze blocks inside of others.

  • Notice that it can go wherever you want.

  • I'll put it at the very top here.

  • So I could put it in a couple of different places.

  • Right now the default voice is alto.

  • Squeak sounds appropriate.

  • Let's try that.

  • Typing in my name, David.

  • COMPUTER: (HIGH PITCHED) Hello, David.

  • DAVID J MALAN: All right.

  • Still not very catlike.

  • Ironically, there is a kitten voice, which if I change it to kitten,

  • we'll now hear this.

  • Type in my name and enter.

  • COMPUTER: (HIGH PITCHED) Meow meow.

  • DAVID J MALAN: OK, so it doesn't really matter at that point what I type in.

  • But now this is amazing.

  • Like, we've gone from just saying hello, world to hello,

  • David, which is dynamically changing.

  • If you were to type your name, obviously,

  • it would say your name instead.

  • And now, thanks to the cloud, that is, servers on the internet,

  • we're converting automatically text that the human has just

  • provided into a sound file--

  • notes and durations and all of that--

  • into something my computer can now play.

  • Well, let's actually make this cat sound a little more like a cat.

  • Let me go ahead and get rid of those blocks

  • here, and let me go and give myself now from the sound category,

  • how about this?

  • Play sound meow until done.

  • Now, this is a simple program.

  • When the green flag is clicked, play sound meow until done.

  • Here we go.

  • I'm going to go ahead and hit Play.

  • [MEOW]

  • All right, that's it.

  • If I want to hear the cat meow again, I got to do it again.

  • [MEOW]

  • OK, that's great.

  • I could kind of amuse myself for a while by just clicking--

  • [MEOW]

  • --play, but--

  • [MEOW]

  • --surely we can do better than this.

  • You can imagine this--

  • [MEOW]

  • --getting tedious quickly.

  • So how might I get the cat to do this again and again?

  • Well, you know what?

  • Let me go ahead and let me just kind of grab a few of these.

  • Meow, meow, meow, three times.

  • So now that's two fewer times I have to hit the button.

  • [MEOWING THREE TIMES RAPIDLY]

  • All right.

  • It doesn't seem like the happiest cat.

  • So let me actually go to Control and let me give him a second break in between.

  • Wait one second in between here.

  • Now let me do it again.

  • [MEOWING THREE TIMES]

  • OK, slightly happier cat.

  • But this seems a little messy now.

  • This is correct.

  • It is meowing three times.

  • But let me go to the audience.

  • Let's now consider design.

  • Recall that we considered design in the context of the phone book.

  • The third algorithm was better designed in that it was faster,

  • it was more efficient, but there's another element

  • to design, which is that you shouldn't repeat yourself if possible.

  • So those of you who have programmed before

  • might know what the solution here might be.

  • Well, it turns out that go back to line three, we call a loop.

  • Turns out Scratch supports these things called loops.

  • And, in fact, there's one staring at me right here.

  • If I zoom in on the left, notice that under the control blocks,

  • these orange blocks there's a repeat block.

  • And even though it says 10 by default, I bet we can change that.

  • So let me drag that over here.

  • Let me throw away a lot of this redundancy, this copy paste.

  • Let me move these puzzle pieces inside of the repeat block,

  • and it, too, will grow to fit them.

  • Not a problem.

  • Let me change the repeat to three.

  • And now let me reconnect everything.

  • And now the program is just tighter.

  • It's using fewer puzzle pieces, or fewer lines of code,

  • fewer steps, if you will, to achieve the same result.

  • So now if I click the green flag--

  • [MEOWING THREE TIMES]

  • --it's still working.

  • So you could imagine changing this to any number you want.

  • There's even a forever block, where we could do it forever,

  • if the cat's going to do this in perpetuity.

  • But it's a better program now.

  • Now it is better designed, because if I want to change the amount of time

  • the cat is waiting or if I want to change

  • the total number of times the cat meows, I

  • can change those details in one place, not in one or two or three,

  • as by copying and pasting those same puzzle pieces.

  • Well, what about that forever loop?

  • What if you do want to do something forever?

  • What might I want to do?

  • Well, let's get the cat up and moving.

  • Let me go under the motion category now.

  • Let me go to point towards mouse pointer.

  • So let me zoom in on this.

  • And every time the cat points toward the mouse pointer,

  • let's have him take one step.

  • So I'm going to grab the move some number of steps,

  • and I'm going to change the 10 to a one.

  • And now I'm going to hit Play.

  • And now we have our first program where the cat is

  • kind of responding to my Mac's cursor.

  • And I can move it around, and I can kind of get a little goofy,

  • but it's taking me literally.

  • It's pointing at the mouse cursor and it's then moving one step.

  • Now, I can make it move faster.

  • Let me stop this for a second.

  • What if I move not one step at a time, but two steps at a time?

  • And we'll see that now the cat is moving a little faster.

  • Not quite super fast.

  • Let's do 20 steps at a time and see what happens.

  • And this is really the essence of animation.

  • The more you adjust the number of steps or the number of changes happening

  • to those pixels per second or per unit of time,

  • the more that's going to happen visually on the screen.

  • Well, what more can we do from just following?

  • Well, you know what?

  • If I have the ability now to have the cat follow me,

  • let me try something else altogether.

  • Let me go ahead and open up another extension.

  • Let me go into the Pen tool, which is going

  • to allow me now to draw with, like, a pencil or pen on the screen.

  • And let me go ahead and still have the cat follow me, I think--

  • actually, you know what?

  • Let's change this.

  • Let's just have him go to where I am.

  • So there's another block that says go to random position.

  • I don't want that.

  • So I'm going to change it by the little triangle menu

  • here, to go to the mouse pointer.

  • So now, forever, the cat's just going to go to where the mouse pointer is.

  • It's not going to glide or do it slowly or quickly.

  • It's just going to go to wherever the cursor is.

  • And let me go now to this new Pen category down below.

  • And how might I do this?

  • You know what I want?

  • I want this cat to be able to draw for me.

  • When I move the cursor up, down, left, right, I

  • want to actually draw something with ink on the screen.

  • But I only want to draw something when the pen is down.

  • Notice on the left that two of the two puzzle pieces I just introduced over

  • here at left are pen down and pen up.

  • But there's a piece of missing logic here.

  • Let me ask the audience how might we go about enhancing this program

  • so not only does the cat follow my cursor, but I also draw on the screen?

  • Nicholas, what kinds of solutions would you propose?

  • AUDIENCE: So what you could do is take an if statement--

  • so you can control when the pen is up or when the pen is down,

  • depending on some condition that you have.

  • Like, I know a lot of things, you draw with the mouse click,

  • if the mouse is on, then you can say the pen is down.

  • And when the mouse click is not on, your pen is up.

  • And then while it follows it forever it also

  • senses to see if your mouse click is on or off.

  • I don't really know.

  • DAVID J MALAN: No, you really do know.

  • That was, like, perfect.

  • Because you took this principle of having the forever

  • block not only go to the mouse pointer, but you proposed

  • asking a question by a condition.

  • So let me actually go under Control, where

  • I happen to know this puzzle piece is, and notice similar to our phone book

  • pseudocode, where I said if else, if else, if else, well,

  • here there's only two questions, I think, as you're proposing.

  • Is the mouse button down or up?

  • So I think we can get away with just an if else.

  • So let me go ahead and drag this below the go to mouse pointer.

  • And then notice this little trapezoid-like shape in the middle

  • here.

  • Let me go to Sensing here.

  • And notice if I scroll down-- yep, there it is.

  • On the left, notice this one?

  • Mouse down, question mark?

  • These are our Boolean expressions.

  • Let me drag that Boolean expression into that similar shape.

  • It's going to grow to fit it.

  • And then what do I want to do?

  • If the mouse is down, I think I want to put the pen down.

  • Else, if the mouse is implicitly up, let me go ahead and put the pen up

  • like this.

  • Well, let me go ahead and full screen this, just

  • so we can see a little better.

  • Let me hit Play.

  • And now the cat is following me, as promised.

  • But this is now a drawing cat.

  • If I click the mouse button, I can say something like, very poorly in cursive,

  • Hello.

  • Sort of.

  • Been a long time since I've done cursive.

  • So we now have the cat actually drawing something.

  • And honestly, it's a little ridiculous that it's a cat drawing.

  • But you know what?

  • Scratch has these costumes.

  • We could go at top left here, and even though Scratch comes with two cat

  • costumes, we could change it to be a pen or a marker or, really, anything

  • we want.

  • Because at the end of the day, this sprite

  • is really just a character on the screen that

  • can take any form that we might want.

  • Well, how can we take this further?

  • I like this introduction of conditions and loops,

  • but there's some other principles we can introduce here.

  • Let me go ahead and start a new program here altogether.

  • And let's see if we can't start counting up

  • and start keeping track of information.

  • So for this time, let's do this.

  • When the green flag is clicked, this time let's go under variables

  • and let's give ourselves a new variable.

  • Scratch lets you create puzzle pieces, this one being a variable,

  • and I'm going to call this a counter.

  • Just something that's going to keep count from one on up.

  • Now this has given me some custom puzzle pieces over here

  • called counter, and then the default my variable, which was there already.

  • And I'm going to go ahead and do this.

  • I'm going to set the counter initially equal to one.

  • And then I'm going to do something forever.

  • Let me grab one of those forever blocks.

  • And I want the cat now to do this forever.

  • I want it to just say whatever the current count is.

  • So I don't want it to say hello for two seconds.

  • I want it to say something for one second, let's say.

  • So I'm going to go back to variables.

  • And I'm going to grab this new circular shape, counter, that I created

  • and drag it right there.

  • So you can read this literally top to bottom.

  • So counter to one, then forever say the counter for one second.

  • But if we don't want the cat to say the same number again and again and again,

  • let's go ahead and change the counter by one.

  • And that's implicitly going to add one to the counter.

  • Now if I go ahead and hit Play, we see a cat

  • that's counting from one to two to three,

  • and it's going to count up, ideally, all the way to infinity.

  • The difference being now, we have this feature

  • of actually using a variable, a variable that's keeping

  • track of some amount of information.

  • In this case, the number that's constantly being updated,

  • and the screen is being redrawn again and again.

  • Well, now let me go ahead and just start opening

  • a few programs that I wrote in advance, just

  • so that we can get a tour of some of those.

  • I've got this program called Bounce that works a little something like this.

  • And this, too, is part of programming.

  • Not only writing your own code, but reading your own code.

  • And let me go ahead and zoom in on this, which I've already created,

  • and consider what it says.

  • First set, rotation style, left, right.

  • This is just a fix what would otherwise be a bug where the cat accidentally

  • ends up upside down.

  • But let me wave my hand at that.

  • This is the interesting part.

  • Forever have the cat moved 10 steps.

  • And then if it's touching the edge, then turn around 180 degrees.

  • So now we can reintroduce the idea of animation.

  • But not that's driven by me, the human, with my cursor.

  • I can now make a game, and interactive piece of art, or anything

  • now where the cat is self-driven.

  • Because when I hit Play now, notice that it's

  • moving back and forth, back and forth.

  • And if it is touching the edge and the answer

  • to that Boolean question is, actually, yes or true or one,

  • then it's going to turn 180 degrees.

  • But this looks kind of stupid, admittedly.

  • You know, one, the cat, yes, is bouncing off the screen,

  • which is maybe a little unrealistic.

  • But he's not really walking.

  • He's gliding.

  • But this is the thing about animation.

  • Just as we noted before that videos, at the end of the day,

  • are really just images flying across the screen--

  • you know what?

  • I bet we can create our own illusion of movement, just like in a real video,

  • by taking not just one costume, the cat with his feet like this.

  • What if we gave ourselves a second costume, where it's almost the same

  • but his feet are slightly differently positioned?

  • Just like the paper based flipbook that we looked at earlier.

  • And you know what?

  • I bet if I toggle between these two costumes,

  • changing the condition of the cat again and again,

  • I bet we can create the illusion of actual movement.

  • And that's what we have here in this other bounce example.

  • In this other bounce example, we have the cat now moving

  • not only back and forth, but notice this purple puzzle piece.

  • After it bounces off the edge, or considers bouncing off the edge,

  • it constantly changes its costume to the next one, to the next one,

  • to the next one, essentially alternating between the two.

  • So now it's not quite perfect.

  • Like, it has what we call very low frame rate.

  • This is like watching a really bad animated GIF online

  • that only has two different frames in it.

  • But it looks more like he's walking and much less

  • like he's gliding back and forth on the screen.

  • So we can actually have some fun with this, too.

  • Scratch support sounds.

  • So, for instance, here's the meow we've heard before.

  • [MEOW]

  • I can record my own, though, if I click this little plus icon down here.

  • Click Record, and allow Scratch to access my microphone.

  • Click OK a couple of times.

  • Here we go.

  • Let me record my own voice.

  • Ouch.

  • All right.

  • That's what the word Ouch looks like, at least when I pronounce it.

  • I can trim off the beginning here.

  • Let me save that.

  • I'm going to give this recording a name, Ouch,

  • and now let me go back to my code.

  • And under the sound block, you know what?

  • Let me go ahead and say this.

  • If I'm touching the edge, not only do I want to turn 180 degrees.

  • Now I can kind of make this a little more playful.

  • COMPUTER: Ouch.

  • Ouch.

  • Ouch.

  • DAVID J MALAN: All right.

  • Still not very catlike, but again, we're just layering and layering.

  • And the takeaway here really is, as these programs

  • get more and more complicated, the goal should never be, when writing code,

  • whether it's in Scratch or C or eventually

  • Python in this class or others, to just start and try

  • to implement your entire vision.

  • Notice with every one of these programs that I wrote from scratch,

  • no pun intended, did I start small and add one or two or three puzzle

  • pieces, building up from something simple to something more complex.

  • And you know what?

  • I bet if we synthesize some of these ideas, we can do yet other things too.

  • Here's another example that involves, perhaps, petting a cat.

  • Let me go ahead and see inside this program.

  • This one's relatively simple, but it's not doing anything just yet.

  • I already hit the green flag.

  • Let me Zoom in on the code, and you can, perhaps, now read my own code

  • that I wrote in advance.

  • The cat is forever asking the question, if touching mouse pointer then

  • play that sound meow until done.

  • Well, it would seem that even though the program is running,

  • it's not doing anything.

  • But it is.

  • It's waiting for something to happen.

  • So let me move my cursor over the cat like--

  • [MEOW]

  • --this.

  • [MEOW]

  • So it would seem, and if I leave it on there, he'll keep meowing.

  • And it's kind of like a program that's petting a cat.

  • And so you can imagine now having conditions

  • inside of loops that are using Boolean expressions to decide

  • exactly what you want something to do.

  • And even more powerfully, even in a language like Scratch can we do this.

  • Let me open up the sea lion here, who has a very distinct bark.

  • But he's demonstrative now of a program that has multiple scripts.

  • So inside of this Scratch project now, we're not just one program but two.

  • Notice both of which start when a green flag is clicked.

  • And let me put them both onto the screen.

  • And it looks longer.

  • But that's just because the puzzle pieces are growing to fit each other.

  • Let's go ahead and hit Play on this.

  • Play

  • [SEA LION BARKING]

  • Notice that every second or so, the sea lion is barking.

  • And frankly, this gets annoying quickly.

  • But how can I stop it?

  • Well, let me go ahead and look over here on the left while it's still barking.

  • Notice the sea lion is forever asking a question.

  • If muted equals false, start sounds sea lion, think hi hi hi for two seconds.

  • So what is muted?

  • Well, the shape of it, recall, represents

  • a variable, like x or y or z, which is just some way of retaining information.

  • So this is like saying, is the value of the muted variable false?

  • If so, you should bark, because if it's false muted, if it's not muted,

  • go ahead and play the sea lion sound.

  • But my god, lets-- on the right here, notice there's another program.

  • When the green flag is clicked, forever ask the question.

  • If the spacebar is pressed, then if muted is true,

  • set muted to false, else set muted to true.

  • So the program on the right is going to change the value of muted

  • from false to true or true to false.

  • Because, my god.

  • I've hit the space bar--

  • [SEA LION BARKING]

  • And now it's over.

  • The program is still running, but it's no longer

  • playing because muted is now true and not false.

  • Well, what else can we do?

  • Things can get pretty fancy pretty quickly.

  • Let me go ahead and create one other program here.

  • And I'll go ahead and do one with just two blocks.

  • This one-- let me go into the extensions again, video sensing this time,

  • and notice there's different types of ways to start programs.

  • Not every program has to start when you click the green flag.

  • There's a similar shape here, but this one in green, that

  • says when video motion is greater than 10.

  • Like 10% of the screen is moving.

  • Let me increase that to 50%.

  • And let me go ahead and do this.

  • Let me go ahead and find the sound puzzle piece.

  • Play sound meow until done.

  • So now I have a two block program.

  • When video motion is more than 50, play sound meow until done.

  • Let me zoom out.

  • And you'll notice that I'm actually in the screen here.

  • Let me move off stage.

  • And now nothing is happening.

  • Let me go and pet the cat, though.

  • [MEOW]

  • Let me do it again.

  • [MEOW]

  • And again.

  • So it's using my computer's camera--

  • [MEOW]

  • --detecting motion, and then executing that particular program.

  • So again, with just these simple building blocks,

  • can we get more and more interesting things to happen.

  • And you know what?

  • We can even have multiple sprites.

  • Let me go ahead and open up an old school game

  • that you might have played in, like, a swimming pool, perhaps,

  • growing up, where one person yells out Marco and the other people

  • are supposed to yell out Polo.

  • Notice here we have a program with two sprites.

  • So two puppets, an orange puppet and a blue puppet.

  • And down here at the bottom, for the very first time,

  • We have two different sprites' abilities to write programs.

  • So right now the orange puppet is selected,

  • which means the program at top left here,

  • up here, belongs to the orange puppet.

  • And the orange puppet has been programmed

  • to say forever, if the keyboard's space key is pressed,

  • then say Marco for two seconds.

  • And then here's the new feature.

  • There's a way in programming to have, like, one program talk

  • to another, or in this case, one sprite talk to another.

  • Sort of passing a secret message that you don't see on the screen.

  • But one program can hear from another.

  • And that's called broadcasting an event.

  • And that's what the orange puppet is doing.

  • If I click on the blue puppet's icon here,

  • he's not going to do very much at all.

  • But instead of doing anything when the green flag is clicked,

  • instead of doing something when the camera sees motion,

  • he instead is going to, when he receives the event, say Polo for two seconds.

  • And so in this case, if I hit Play now, nothing happens yet.

  • But when I do hit the spacebar, orange says Marco, blue says Polo.

  • But they are written independently.

  • I've written one program for orange, one program for blue,

  • and they're somehow communicating.

  • And speaking of communicating, there's even

  • more things you can do these days thanks to the internet and the cloud.

  • Let me go ahead and open up one other new canvas here.

  • Very quickly give myself a when green flag clicked.

  • Let me go ahead and ask that same question before, ask what's your name

  • and wait.

  • But now let me go into these extensions and let

  • me find the translate extension, which is, again,

  • going to use the cloud to send whatever I type in out on the internet

  • and get back a response, and then say it on the screen here.

  • So let me go ahead and say something on the screen, like say hello.

  • But I don't want to say hello.

  • I want to go back to the Translate category,

  • and I want to go ahead and translate--

  • you know what?

  • I like this block.

  • Translate something to another language.

  • But let me get one of those join blocks again, and let me go ahead

  • and join the word hello and then the name that the person has typed in.

  • So to get that, I need the answer block again.

  • So I'm just recreating some of our blocks from earlier.

  • And notice, before I just did this.

  • I said the result of joining hello and answer, albeit with a comma last time.

  • But now let's do this.

  • Let me take the output of join, make it the input to translate.

  • Let me translate, say, to Arabic here.

  • Let me drag and drop into the say block.

  • So now we have two inputs going into join, join's output going

  • into the input of translate, and the output of translate going into say.

  • But the net result is going to be I'll type in my name David and hit Enter.

  • Hello, David, now in Arabic.

  • All thanks to these principles of functions, conditions, and loops,

  • and now even adding in the internet.

  • Now let's consider finally, before we play a final couple of games.

  • In conclusion, there's a way to even improve

  • the design of a lot of what we've done.

  • In fact, let me go back just a moment to where we left off with that meowing.

  • And in one of our meowing examples, we had

  • code that looked like this, where I repeated three times,

  • recall, and I played the sound meow again and again and again.

  • And I argued at the time that this was better designed.

  • Why?

  • Because I didn't just drag and drop the same puzzle piece again

  • and again and again.

  • I used a repeat block, I threw away all of the redundancy,

  • and I've arguably kept it simple.

  • I'm using some fancier ideas, but the code is simpler

  • and it's fewer puzzle pieces now.

  • But it turns out that there's a missed opportunity

  • here to apply another principle of computer science,

  • and this is what we would generally describe as abstraction.

  • Abstraction is this amazing problem solving

  • technique that's really just a fancy way of saying

  • let's take a very complicated idea, or a slightly complicated idea

  • and simplify it in such a way that we all agree that you can implement it

  • the complicated way, but let's now just stipulate

  • that we're going to think about it as on a more simple level.

  • So let me go over to this same program.

  • And you know what?

  • Scratch, curiously, did not anticipate having a meow block.

  • Like, there is a say block and there's a think block, but there's no meow block.

  • And that seems appropriate for a program where it comes with a cat built in.

  • So we can do this.

  • Just as you can create your own variables, notice at bottom left here,

  • you can create your own blocks with this pink category.

  • And if I go here, I'm going to make a block

  • and I'm going to call this block meow.

  • And quite simply, I'm going to click OK.

  • Now notice I get this new puzzle piece that says define meow.

  • And it's ready to have other pieces connected to it.

  • How am I going to define meow?

  • I'm just going to go ahead and drag this over here, because I already

  • implemented meow before.

  • And now, notice what I have on the left hand side.

  • Because I've just made this custom block or puzzle piece,

  • I now have a pink piece called meow, just as though it came with Scratch.

  • And now what's compelling about this is that I can sort of think

  • of this as out of sight, out of mind.

  • Who cares how meow is implemented?

  • We know we implemented it earlier.

  • Let's now just stipulate that we can take for granted it exists.

  • And if I zoom in now on the new program, now it's more readable in some sense.

  • It's a little shorter.

  • It has a fewer puzzle piece.

  • But it also is more self-descriptive.

  • I can read my code.

  • I can look at this code and say, OK, it's

  • obviously going to repeat three times a meow block.

  • But let's play that.

  • [MEOW]

  • It's no different.

  • [MEOW]

  • Two.

  • [MEOW]

  • But I bet we can simplify this one step further and make

  • it a little more flexible.

  • Let me go ahead and right click or control click on the meow custom block.

  • And let me actually add an input here that we'll call n.

  • And let me just add a label that says times.

  • And let me go ahead and click OK.

  • And notice that my puzzle piece now looks different.

  • It looks more like some of MIT's blocks that take input

  • with these little white ovals.

  • And, in fact, now notice what I can do.

  • I can change the definition of meow, as Scratch already has for me,

  • such that I can now do more inside.

  • Let me actually disconnect all of this stuff.

  • Let me move the repeat block to the definition of meow itself.

  • Let me go ahead and play the sound and wait inside of that repeat block,

  • but notice this little circle around the end.

  • Let me just repeat an arbitrary number of times now.

  • I don't have to worry about hard coding three or 10 or anything else.

  • And now, out of sight, out of mind, don't have to worry about that anymore.

  • Let's now just whittle down that increasingly complicated program

  • that we wrote earlier into, really, just two puzzle pieces.

  • When the green flag is clicked, meow, sure, three times.

  • I don't have to know or care any more how meow is implemented.

  • I just need to know that someone did it for me, whether MIT or maybe

  • myself, minutes ago.

  • I'll click play again.

  • [MEOWING THREE TIMES]

  • Two, and three.

  • And so now we have an implementation of abstraction.

  • Taking a somewhat complicated idea, like getting a cat to meow,

  • not worrying about the so-called implementation details,

  • and just defining a puzzle piece or function called meow.

  • Well, now let's take all of this together

  • and see some of the creations of some of your predecessors in past terms.

  • Here, for instance, is a sort of story that one of your classmates years ago

  • made involving a gingerbread tale.

  • Let me go ahead and full screen this and click Play.

  • [MUSIC PLAYING]

  • And you'll see now that we have multiple sprites already, each of which

  • have different costumes, and I'm being asked a question.

  • Would you like an apple?

  • Yes or no.

  • So I'm no longer being asked my name.

  • I'm being asked arbitrary questions.

  • Sure.

  • Let me go ahead and have an apple.

  • I type in yes and hit Enter.

  • Notice the movement.

  • We've seen movement before.

  • [CHOMPING SOUNDS]

  • [MUSIC PLAYING]

  • OK, unfortunately, that was the wrong decision to make in this story.

  • So that's OK.

  • Let's start it again.

  • Red stop sign.

  • [MUSIC PLAYING]

  • Green flag.

  • Hello dearie, would you like an apple?

  • No, let's learn from that lesson.

  • Cupcake sounds much better.

  • I'll type yes this time.

  • Notice, again, the motion.

  • So there's some animation there.

  • It's touching the other sprite.

  • That, too, was unfortunate.

  • Let's try one last time with this art.

  • And now we have an apple, no.

  • Learned a lesson.

  • Cupcake, no.

  • Learned a lesson.

  • OK, now let's see what happens with that loop.

  • [CACKLING]

  • [SCREAMING]

  • [CHOMPING SOUNDS]

  • OK, surprise ending.

  • But this is all to say that by taking these building blocks of loops,

  • conditions, and functions, can you start to make things

  • that are a little more interactive.

  • In fact, I myself did something years ago-- the very first thing

  • I myself wrote in Scratch was actually when I was in graduate school

  • and cross-registered for a class at MIT, the professor for which

  • was the author of and the originator of Scratch itself.

  • And let me go ahead and full screen this and propose

  • how I thought about solving, now, a fairly large problem back in the day.

  • Drag as much falling trash into the can as you can.

  • So what's happening now?

  • A piece of trash is falling on the screen.

  • You'll see that it's moving from the top to the bottom,

  • and we've seen animations like that.

  • But watch this.

  • I bet using a condition and a forever loop,

  • we can make it possible to pick this up.

  • Notice now the trash is following my cursor, just like the cat was.

  • And notice if touching this other trash can sprite,

  • maybe we can even get Oscar to pop out of the can.

  • And he, then, starts counting up my score, thereby using a variable,

  • and indeed, as more sprites or more trash falls,

  • I can continue to play a game in this way.

  • But here, too, even though things are starting to happen more quickly,

  • there's more on the screen, the song is playing in the background,

  • it all reduces to basic building blocks.

  • And I can't emphasize enough.

  • When I wrote that first program years ago,

  • I did not implement what you just saw.

  • I think the very first thing I did was I googled around

  • and found Sesame Street's street lamp and I put that on the screen.

  • And that was sort of version one.

  • It didn't do anything, but it looked like what I want.

  • Then I added the trash can.

  • Then I think I programmed one piece of trash or one sprite to fall.

  • So I changed the cat to a piece of trash and then

  • I had it animate from top to bottom.

  • Then version four or five, I then added a forever loop

  • and a condition that checks if the mouse button is down,

  • and if so, I have it follow the mouse pointer.

  • So I took a big problem and broke it down bit by bit

  • into much smaller steps.

  • And this was the same approach that CS50's own Andrew Berry took years ago,

  • one of our teaching fellows.

  • The very first year I taught CS50, created his very own first Scratch

  • project that I thought I'd leave us with here today.

  • This is a program that he called Raining Men.

  • It might have a familiar tune, and I would

  • propose that you consider, when watching this,

  • our final Scratch program today, how it is that Andrew went about programming

  • everything that you see.

  • Now Andrew went off into the real world and didn't pursue computer science,

  • per se.

  • He's actually now the general manager for the Cleveland Browns,

  • which is an American football team.

  • But this, too, speaks to just what kind of foundation you

  • can form, irrespective of your intended major, your possible major,

  • considering, after all, that a lot of the ideas we're going to focus on

  • in this class are ultimately about problem solving,

  • programming being just one tool for the trade.

  • And, indeed, even within the world of sports,

  • are there so many opportunities nowadays for algorithms, for analysis,

  • for video simulations thereof, and so many of Andrew's worlds

  • and your worlds will invariably start to collide

  • as you begin to build up your own toolkit

  • and your own understanding thereof.

  • So in conclusion, we'll take a look at this, Andrews program.

  • In the meantime, this was CS50, and now it's raining men.

  • [MUSIC - "IT'S RAINING MEN]

  • COMPUTER: Hi.

  • Hi.

  • We're your weather girls.

  • Uh huh.

  • And have we got news for you.

  • You better listen.

  • Get ready, all you lonely girls, and leave those umbrellas at home.

  • All right.

  • (SINGING) Humidity's rising, barometer's getting low.

  • Oh.

  • Uh oh.

  • According to all sources--

  • What sources now?

  • The street's the place to go.

  • 'Cause tonight for the first time, at just about half past 10,

  • for the first time in history it's gonna start raining men!

  • It's raining men, hallelujah, it's raining men--

  • [MUSIC PLAYING]

[MUSIC PLAYING]

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B1 中級 美國腔

CS50 2020 - 第 0 課 - Scratch(CS50 2020 - Lecture 0 - Scratch)

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    羅仕瑋 發佈於 2021 年 08 月 27 日
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