2. Algorithms and Data Structures

3. Algorithms and Data Structures
An algorithm does something, solves some problem, in a mechanical way.
It is a bit like a “machine” or a specialised tool

4. Algorithms and Data Structures
A data structure is some way to represent and store data
so that we can process that data efficiently

5. Algorithms and Data Structures
Data structures use algorithms
Algorithms use data structures

6. Algorithms and Data Structures
Data Structures and Algorithms a
Computer Scientist’s building blocks

7. Algorithms and Data Structures
Computer Scientist invent and study
algorithms and data structures and problems

8. Algorithms and Data Structures
Computer Scientists do other things too 

10. Our website, link from moodle

11. Lecture

12. Why don’t I just go away and read the book myself?
Lectures … Aye, right.
Why don’t I just go away and read the book myself?
Why come to lectures?
meet new exciting people
keep in touch with fashion, trends, …
be part of the “in” crowd
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13. Great!
Algorithms
&
Data Structures
Algorithms
&
Data Structures

15. Lassie, what’s in this ADS2 course ? Will it be interesting?
woof!

16. Content
linked lists
single/doubly-linked,
insert, delete, find, min, max, …
stacks
push/pop/size
bracket matching, RP calculator
queues
enqueue/dequeue/size
circular queue (in array)
recursion
see above
big O 

17. Continued
Content
trees
n-ary trees: representations & properties
binary trees
representations & properties & traversals
binary search trees
insert/find/delete/traverse/height …
AVL trees
heap
insert/delete/sort
splay trees (maybe)
red-black trees (maybe)

18. Continued
Content
skip lists (maybe)
Sorting
bubble/insert/sift sort
merge sort
quick sort
bucket sort (pigeon hole sort)
bead sort (maybe)
Dictionaries
maps and hash tables
open and closed hashing

19. Continued
Content
5 pieces of practical work
2 of above are assessed (20%)
exam in May (80%)
lab every week
woof

20. Great!
Algorithms
&
Data Structures
Algorithms
&
Data Structures

22. our ADS2 website
under construction
(permanently)

23. Home

24. News

25. The lectures

26. The lectures

27. code & api

28. Lots of code in there

29. demos

30. Links to interesting & useful stuff

31. Links to interesting & useful stuff

32. exercises

33. Questions & Answers

34. … and now for something completely different!!!

35. Lassie, why are algorithms and data structures important?

36. Lassie, will there be anything in the course that is challenging and exciting?

37. I just hope I get feedback, continuously

38. Lassie, will you teach us to “THINK LIKE A COMPUTER SCIENTIST”?

39. Lassie, honestly, I’m not that experienced as a programmer
Lassie, honestly, I’m not that experienced as a programmer. Will you help us with our programming?

41. Will we use BIG data sets?

42. woof!

43. 1st lecture … “Who cares?”

44. algorithms are ancient
Many algorithms predate computers

45. But first … what is an algorithm?

46. A finite sequence of instructions, each with a
What is an algorithm?
A finite sequence of instructions, each with a
clear meaning, and can be performed with a
finite amount of effort in a finite length of time
[Aho, Hopcroft, Ullman 1983]

48. Before some of you were born

49. Prim’s Algorithm
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50. Abu Jafar Mohammed ibm Musa Al Khwarizmi
Before I was born
800AD

51. 325BC to 265BC
GCD
Euclid of Alexandria

53. Euclid’s algorithm
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54. Euclid’s algorithm
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55. Code is not an algorithm … maybe a realisation of an algorithm
Euclid’s algorithm
Code is not an algorithm … maybe a realisation of an algorithm
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56. Algorithms you might know/use
Addition/subtraction
Long division/multiplication
Tying your shoe laces
Changing a tyre on your bike
Baking a cake
Opening a bottle of beer …
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57. Algorithms you might know/use
Addition/subtraction
Long division/multiplication
Tying your shoe laces
Changing a tyre on your bike
Baking a cake
Opening a bottle of beer
A finite sequence of instructions, each with a
clear meaning, and can be performed with a
finite amount of effort in a finite length of time
[Aho, Hopcroft, Ullman 1983]
ADS2 Lecture 1

58. Addition/subtraction Long division/multiplication
Tying your shoe laces
Changing a tyre on your bike
Baking a cake
Opening a bottle of beer
Algorithms you might know/use
A finite sequence of instructions, each with a
clear meaning, and can be performed with a
finite amount of effort in a finite length of time
[Aho, Hopcroft, Ullman 1983]
It terminates
It produces correct result
It has a “complexity” (measure of performance)
All steps can be performed without “magic”
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59. Things I do not consider to be algorithms
Algorithmic trading
Rules to decide if you get a loan or a job or …
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60. Things I do not consider to be algorithms
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61. Data Structures … what’s that then?
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62. Data Structures … what’s that then?

63. ways to organise data/information efficiently
Not a Data structure – ADT (see next slide)
Data structure
Data structure
Data structure
ways to organise data/information efficiently
where will I (not) see data structures?

64. abstract data types?

65. Definitions contd. Basically an ADT is an “abstract” entity
Set, Queue, Priority Queue, Stack, …
But a data structure has a fixed implementation (as well as “structural” properties).
ADS2 Lecture 2 65

66. Who cares?
Machines are getting bigger, faster, cheaper … do efficient data structures and algorithms really matter?

68. Bigger, faster, cheaper machines
Bigger data sets, greater expectations

69. You have a file of names of people We don’t know how many people
What data structures might we use and what algorithms?
An example …
You have a file of names of people
We don’t know how many people
Read them in to memory and allow
Find
Add
delete
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70. What data structures might we use and what algorithms?
A quick look at fBook
We have a file of people members.txt and a file of friends with entries
that are pairs of names of people who are friends. We want to be able
to find people, find out who is friends with whom … basically, a toy facebook
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71. Refreshed our knowledge of ArrayList Consequences of add and remove
What have we learned?
What data structures might we use and what algorithms?
Refreshed our knowledge of ArrayList
Consequences of add and remove
How to compile and run on the command line
What args means
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72. ADS2 Lecture 1

73. ADS2 Lecture 1

74. Person
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75. Person
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76. Person
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77. I dream of ArrayLists

85. So, ArrayList created with space for 10 objects!
That’s enormous 

86. And when I add an object into a given position it shuffle things up
And when I add an object into a given position it shuffle things up. Is that for free? Does that take any time?

87. And what happens when I want to put in an 11th object into my ArrayList?

88. Back to Person
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89. Person
constructor
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90. Person
utilities
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91. Person
For printing
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92. FBook
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93. FBook
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94. FBook
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95. FBook Given a name as a String create a person with that name and make
them a member of FBook
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96. FBook Opening a file, reading it, creating persons and adding
them as members
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97. Find a person with a given name … 1st algorithm FBook
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98. Find a person with a given name … 1st algorithm FBook
But how did we need to structure the data so that we can use that algorithm
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99. Find a person with a given name … 1st algorithm FBook
But how did we need to structure the data so that we can use that algorithm
How efficient is that algorithm, and what could we have used instead?
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100. FBook
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101. Test
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102. ADS2 Lecture 1

103. Test
What are args[]?
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104. Test
HCI Fail?
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105. I want to keep it simple
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107. So, let’s compile and run it …
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108. So, what have we learned …
The need for dynamic data structures
Refreshed our knowledge of ArrayList
Consequences of add and remove in ArrayList
Algorithms & data structures go hand in hand
How to compile and run on the command line
What args means
Keeping it simple …
ADS2 Lecture 1