1. Characters, Strings, Basic Data Structures UC Santa Cruz CMPS 10 – Introduction to Computer Science www.soe.ucsc.edu/classes/cmps010/Spring11 ejw@cs.ucsc.edu 6 April 2011

2. UC SANTA CRUZ Class website  http://www.soe.ucsc.edu/classes/cmps010/Spring11/  Please write this down, and bookmark it  Holds:  Syllabus (including homework due dates)  Homework assignment descriptions  Description of course readings  Links to class lecture notes  The final exam is scheduled for Tuesday, June 7, 8am-11am  This class will have a final exam. Please plan on this.

3. UC SANTA CRUZ Tutoring available  Learning Support Services (LSS)  Has tutoring available for students in CMPS 10  Students meet in small groups, led by a tutor  Students are eligible for up to one-hour of tutoring per week per course, and may sign-up for tutoring at https://eop.sa.ucsc.edu/OTSS/tutorsignup/ beginning April 5th at 10:00am. https://eop.sa.ucsc.edu/OTSS/tutorsignup/  Brett Care - bcare@ucsc.edu is the tutor for CMPS 10 that LSS has hiredbcare@ucsc.edu

4. UC SANTA CRUZ Abstraction and Models  Converting the real world into data:  Create a model of the real world  Represent that model in data  How do you model the real world?  Involves a process called abstraction  Abstraction  Prerequisite: know your problem or application  Focus on aspects of the real world that are important to the problem  Add those elements to your model  Omit elements of the real world that aren’t relevant  Implies: the same real world scenario can be modeled in many ways, depending on the problem at hand physical world model data (inside computer) abstraction representation

5. UC SANTA CRUZ Representing models as data  Most models can be represented using:  Basic data types  Integers  Floating point  Boolean  Characters  Strings  Basic data structures  Arrays  Lists  Stacks/Queues  Trees  Graphs

6. UC SANTA CRUZ Boolean  A boolean data type represents true or false  This is represented as a 1 (true) or a 0 (false)  How much space does a boolean require? It varies.  The minimum required space is 1 bit  However, typically a boolean is stored in an entire byte  8 bits, as in the C# language  Only use one bit:  00000001 = true  00000000 = false  … or in an integer  16 or 32 bits, as in the C language which lacks a standard boolean type  0000000000000001 = true (16 bits)  0000000000000000 = false (16 bits) www.popwuping.com/culture/true-urban-park-in- bangkok.php tv.wearefalse.com

7. UC SANTA CRUZ Character  A single letter, number, punctuation, symbol, etc.  Historically, in the US characters were represented using the US-ASCII code (uses 7 bits of an 8 bit byte)  This was superseded by ISO/IEC 8859  Provided support for special characters used in specific languages, along with accented characters  Examples: ß (German), ñ (Spanish), å (Swedish and other Nordic languages) and ő (Hungarian)  But, didn’t handle representation of ideographic languages  Led to development of many standards for this specific purpose, and for other languages not covered by ISO 8859  Historically a character of storage meant one byte (8 bits)  This still holds true in many discussions today Lead type blog.davidcaputo.net/category/design/

8. UC SANTA CRUZ UNICODE  Today, the UNICODE standard is rapidly becoming standard  Can represent every character in every human language with an alphabet  Contains more than 109,000 characters covering 93 scripts  Initial idea comes from Joe Becker and Mark Davis in 1987  Today, maintained by UNICODE consortium  Each character has a unique 32 bit identifier  But, 32 bit per character is a lot of space  So, have multiple encodings  UTF-8: most popular, maximizes backward popularity with US-ASCII, 8bits/byte for US-ASCII, more bytes for other scripts (variable width)  UTF-16: most common scripts are 16 bits, less common ones are more (variable width)  UTF-32/UCS4: each character uses 32 bits (4 bytes)  One of the great unsung achievements of computer science www.macchiato.com/

9. UC SANTA CRUZ Strings  A string is a sequence of characters  “Hello, world!” is the most famous string.  Two main ways to represent:  A sequence of characters, ended with a 0 (null character)  A length, and then that many characters 13  Each character is represented according to some character encoding (UTF-8, UTF-16, US-ASCII, etc.) Hello,World!/0 null character Hello,World!

10. UC SANTA CRUZ Basic Data Structures

11. UC SANTA CRUZ Modeling and sets  When modeling the real world, there is a need to model sets of things  Can also think of this as a group of things, collection of things, etc.  Examples:  The temperature at my house measured every hour over a day  All of the songs in my music collection  All of the houses on a street  All of the people in my family  People standing in line at a restaurant  Frequently, these sets have a natural order  Temperature over a day:  First temperature reading at hour 0, then the second at hour 1, etc.  Houses on a street:  Order by house number

12. UC SANTA CRUZ Representing sets  Many different data structures have been developed to represent sets  Array  A set with fixed length  Elements can be added anywhere  Can go directly to any element  Lists  A set with variable length  Elements can be added anywhere  Need to search list for specific element  Stack/queue  A set with variable length  Elements can be added only at beginning (stack) or end (queue)  Can only retrieve element from beginning (stack/queue) www.setgame.com

13. UC SANTA CRUZ Arrays  Used to represent sets of fixed length  Also represents mathematical vectors and matrices of fixed size  Once set, cannot change the size of an array (biggest limitation)  But, this limitation permits fast lookup of values (biggest strength)  How do they work (1-dimensional)  Given an integer index can:  Retrieve an element of the array  array[index]  value  Set an element of the array  value  array[index]  Can have an array comprised of any basic data type  Array of integers, array of floats, array of strings, etc.

14. UC SANTA CRUZ Array example  Consider a set of temperature values at a location, with temperature readings taken once every hour  Have a total of 24 readings each day, and this won’t change  Model for one day of readings  A set of 24 ordered temperature readings  Representation  Use an array to represent the ordered set of 24 readings  Use a floating point number to represent each temperature reading temperature is array[24] of float

15. UC SANTA CRUZ Array Example: 24 hours of temperature  Typical use:  temperature[0] = 52.5 Sets the temperature value for hour 0 to 52.5  noon_temp = temperature[12] The variable noon_temp takes the value of the temperature array at hour 12 (noon), 68.2 52.5 52.0 51.7 51.2 50.8 50.1 0: 1: 2: 3: 4: 5: 49.8 51.6 55.7 57.2 61.4 65.8 6: 7: 8: 9: 10: 11: 68.2 70.4 72.5 72.9 72.1 70.3 12: 13: 14: 15: 16: 17: 68.3 61.8 58.0 56.4 54.3 52.6 18: 19: 20: 21: 22: 23:

16. UC SANTA CRUZ 2-dimensional arrays  It is also possible to have 2 and more dimensional arrays  Represents tabular data, or matrices  In this case, have indices for the row and column of the data  Example:  Temperature readings for a year temperature is array[365][24] of float  Noon_Jan_First_temp = Temperature[0][12]  The temperature on January 1, at noon

17. UC SANTA CRUZ Array: pros and cons  Pros  Permits fast access to elements of the array  Array notation maps well to certain kinds of problems (mathematical matrices)  Cons  Array size is fixed, and cannot grow  In many situations, the amount of data is unknowable in advance  Example:  Your music collection. Can you predict how many songs you’ll acquire over your lifetime?  For this situation, would be better to have a representation that can grow or shrink over time

18. UC SANTA CRUZ List  Used to represent sets of variable length  It is possible to change the length of a list by adding and removing members  Are slower than arrays for looking up members  How do they work  List.add(element)  Adds element to end of the list  List.remove(element)  Searches list, and removes first one that matches element  List.Insert(position, element)  Adds element at specified position in list  Can have a list of any basic data type  List of integers, list of floats, list of strings, etc.

19. UC SANTA CRUZ List example  Consider a list of the titles of songs you own  This list will grow over time… and may shrink  Maybe you delete the Miley Cyrus in your collection?  Model  A set of song titles  Representation  Use a list to represent the set and a string to represent the title  Songtitles is List of string Songtitles is a list of strings

20. UC SANTA CRUZ List example  Start with this list, called Songlist  0, “Poker face”  1, “Video killed the radio star”  2, “Rock star”  Add a song to the list  Songlist.Add(“Beat it”)  0, “Poker face”  1, “Video killed the radio star”  2, “Rock star”  3, “Beat it”  Songlist.Remove(“Rock star”)  0, “Poker face”  1, “Video killed the radio star”  2, “Beat it”  Songlist.Retrieve(1)  Gives the value, “Video killed the radio star”  Songlist.Insert(1, “Let’s Go”)  0, “Poker face”  1, “Let’s Go”  2, “Video killed the radio star”  3, “Beat it”

21. UC SANTA CRUZ Linked List  The typical implementation of a list is as a linked list  Each element holds a pointer to the next element in the list  Can also have each element point to the next and previous element in the list (permits fast “previous item” capability) A singly linked list (en.wikipedia.org/wiki/Linked_list) 0: 12, 1: 99, 2: 37 A doubly linked list (en.wikipedia.org/wiki/Linked_list) 0: 12, 1: 99, 2: 37

22. UC SANTA CRUZ History of Linked List  Linked lists emerged early in computing  1955-1956 by Allen Newell, Cliff Shaw, Herbert Simon while developing language IPL  In 1958, the language LISP (List Processor) was developed at MIT by John McCarthy  Made lists (implemented as linked lists) a fundamental part of the language  Today, most major programming languages provide a built-in list data type, often with multiple variations

23. UC SANTA CRUZ List: Pros and Cons  Pros  Can handle a list of any length  Cons  Slower access than with arrays  Slower to add elements into a list  Notation for accessing elements not as convenient as arrays  Some languages allow use of array notation (e.g., list[index]) with lists

24. UC SANTA CRUZ Stack and Queue  Stacks and queues are used to represent ordered sets where you typically want to access the most recently added element (the “top”)  Accessing the top element is called “pop” for Stacks, “dequeue” for Queues  With a stack, the elements can only be added (push) to the top  With a queue, the elements can only be added (enqueue) to the bottom Stack en.wikipedia.org/wiki/Stack_(data_structure) Queue en.wikipedia.org/wiki/Queue_(data_structure)

25. UC SANTA CRUZ Stack example  Consider a list of web page addresses (URLs) you have visited in your browser  If you hit the “back” button, you would like to go to the last page you visited  Model  A set of ordered web page URLs  Representation  Use a stack to represent the set, and a string to represent each URL  Visited_pages is stack of string  Visited_pages is a stack data structure where each element is a string  The Visited_pages structure ensures that the last element added is the first element removed (last-in, first-out, LIFO)

26. UC SANTA CRUZ Stack example  Assume the starting history is as follows and you’re at the page www.engadget.com  0: www.ucsc.edu  1: games.soe.ucsc.edu  2: www.acm.org  (www.engadget.com) isn’t added until you go to a new page, and it becomes history  Now, you browse over to Slashdot (www.slashdot.com)  Visited_pages.push(“www.engadget.com”)  0: www.engadget.com  1: www.ucsc.edu  2: games.soe.ucsc.edu  3: www.acm.org  Then, you decide to hit back button  Visited_pages.pop()  Returns: www.engadget.com  0: www.ucsc.edu  1: games.soe.ucsc.edu  2: www.acm.org  Browser reloads this page

27. UC SANTA CRUZ Queue example  Consider people waiting in line at the coffee cart  It might be nice if you could just give your name, and they would call you when it’s your turn  Model  An ordered set of customer names.  Representation  Use a queue to represent the set, and a string to represent the customer name  Coffee_line is queue of string  Coffee line is a data structure where each element is a string  The queue data structure ensures no one will cut in line (first-in line, first-served, or first-in, first-out, FIFO)

28. UC SANTA CRUZ Queue example  Assume the line is currently:  0: “Ada Lovelace”  1: “Charles Babbage”  2: “Grace Hopper”  A new person, Alan Turing comes to the end of the line  Coffee_line.enqueue(“Alan Turing”)  Line is now (Turing is added to the end of the queue)  0: “Ada Lovelace”  1: “Charles Babbage”  2: “Grace Hopper”  3: “Alan Turing”  Now the next person in line is served  Coffee_line.dequeue()  Returns “Ada Lovelace”  List is now (Ada came from the from the front of the queue)  0: “Charles Babbage”  1: “Grace Hopper”  2: “Alan Turing”