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from one node to another such that each of those elements in the array is
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5.08
a pointer to another array.
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1.75
And if you keep following these pointers, following the bread crumbs
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3.05
and you eventually find yourself at this special sentinel value--
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3.61
and actually, it wouldn't be null, it would be like a Boolean saying true.
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3.74
This is a word you can just by storing a single yes or no at this location way
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5.76
down here, implicitly reveal that M-A-X-W-E-L was in fact a word.
6,087.39
7.995
Let's follow another.
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0.875
So, let's say Turing, T-U-R-I-N-G, check, Boolean true.
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10.88
Turing is in this dictionary as well.
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2.42
So, if there are bread crumbs that lead to null, that word is not in here.
6,109.56
3.9
So, apparently there is no names starting with A through L,
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4.3
and there is no one after U through Z or some of the letters in between,
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3.99
because those pointers are implicitly and pictorially null.
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3.23
But let's consider, then, what is the running time of inserting or looking up
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4.92
a name and [? in a trie? ?] Thus far, pretty much all of the data
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4.22
structures we've talked about have pretty slow running times,
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3.86
linear in the worst case.
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1.84
So, if we used an array to store people's names
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2.55
or we used to linked list to store people's names, in the worst case
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3.152
we had linear running time, unless maybe we sort things, but even
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2.708
then that costs us some time.
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1.208
So, linear may be logarithmic was the best we could do.
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3.192
And even with a hash table, whereby, maybe we
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2.75
store Maxwell at the M location in our table,
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2.65
he might still have a link list of a whole bunch of other M people.
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3.49
That, again, can devolve into something linear, a linear linked list.
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3.99
But what about a hash table?
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2.13
To answer the question is Maxwell in a trie-- sorry, what about to trie?
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5.14
To answer the question is Maxwell in a trie, what do we do?
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3.6
We start at the root and we follow the pointer that represents m,
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3.96
and then we follow the pointer there that represents A, then X, W, E, L, L,
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4.31
and we look for at the end of that series of steps a true false value.
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3.73
And if it's true, yes, Maxwell is here.
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3.15
What about Turing?
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0.89
Well, we start at the pointer that represents
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1.875
T, then U, R, I, N G, then check.
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1.865
Oh, true.
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1.43
Turing is in there.
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1.27
Let's look for David.
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1.22
No, false.
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1.27
There's not even a pointer there.
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1.52
David is not in this dictionary.
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2.08
So, how many steps did that each take?
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1.95
To tell whether Maxwell was in the dictionary,
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2.2
was M-A-X-W-E-L-L and then look at the Boolean, so that was eight steps.
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5.51
And to look up Turing was T-U-R-I-N-G. And then that Boolean,
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4.84
that was seven steps.
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2.91
Those numbers have nothing to do with how many words are already in the trie.
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5.66
There might be-- and there's only a couple dozen here--
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2.94
there are a dozen or so here-- there might be thousands of actual words
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3.48
in this dictionary, but we're still going to find Alan Turing by way
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4.15
of T-U-R-I-N-G Boolean seven steps, and M-A-X-W-E-L-L Boolean, eight steps.
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7.74
It doesn't matter how many other data elements are in this trie.
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4.21
And that's what's powerful, because if there
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2.48
is an upper bound on the number of letters in an English
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2.56
word-- which is kind of true.
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2.14
I've rarely typed words that are longer than I don't
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2.62
know 10 characters, 15 characters.
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1.81
At some point there might exist these words,
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2.5
but no one actually says or types these words.
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2.63
Those are effectively constants.
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1.63
The maximum length of a word in English is surely some constant,
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3.096
because there is one word that's the longest.
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1.874
That's a constant value, which means inserting a name,
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3.18
or searching for a name, or removing a name from a trie
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4.26
does depend on the length of the name, but it does not
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2.7
depend on how many pieces of data are already in the data structure.
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3.95
And as such, it is constant time.
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4.05
So, now in C, we have a whole bunch of new syntax
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2.3
with which to represent data structures, namely actual structs in C,
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3.315
and we have pointers, and we have malloc with which
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2.125
we can build more interesting shapes, if you will, in memory.
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2.99
And we now have a number of abstract data types and actual data structures
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4.1
we can build using these ingredients with which we can now solve problems
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4.142
that are going to demand all the more resources, all the more time, all
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2.958
the more space, in which case efficiency and good design
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3.24
is going to be ever more important.
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2.3
All this and more next time.
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2.34
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4.394
AUDIENCE: She thought she was doing the right thing.
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2.166
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4.975
[AUDIO PLAYBACK]
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2.85
-Tell me more.
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2.375
-David was sure it had to be the muppet, something called muppet mode,
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6.7
but the pressure was too much.
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2.86
-This is Mario in muppet mode.
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1.37
Take 23.
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0.71
6,350.23
4.99
[HONKING]
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2.45
6,357.67
14.71
-What's happening?
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1.048
I thought this is what you always wanted,
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2.302
to star in the walkthrough videos, to have all of YouTube's eyes
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3.52
watching you.
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2.5
[HONKING]
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0.5
6,382.25
5.74
-Yes, you are.
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1.96
You have to be.
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1.53
Now stand up straight, tuck in your shirt, look into the camera!
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3.662