Come on down! • Take and fill out a survey • Get a copy of lecture slides • Please sit in the first 5 rows! CSE 326: Data Structures Lecture #1 Introduction Alon Halevy Spring Quarter 2001 Today’s Outline • Administrative Stuff • Overview of 326 • Survey • Introduction to Complexity Course Information • Instructor: Alon Halevy <alon@cs> Office hours: Wed. 4:30-5:30, 310 Sieg Hall • TA: Maya Rodrig <rodrig@cs> Office hours: Monday 1:30-2:30. Meet in Sieg 226B • TA (1/2) (and C++ expert): Nicholas Bone (bone@cs) • Sections are held in: BLD 392, EE1 031. • Text: Data Structures & Algorithm Analysis in C++, 2nd edition, by Mark Allen Weiss Course Policies • Several written homeworks – Due at the start of class on due date • Several programming projects – Projects turned in electronically before 11pm on due date • 10% penalty for 1 weekday late; afterward, NOT accepted • Work in teams only on explicit team projects • Grading – homework: – projects: – midterm: – final: 25% 25% 20% 30% Course Mechanics • 326 Web page: www/education/courses/326/01sp • 326 course directory: /cse/courses/cse326 • 326 mailing list: cse326@cs.washington.edu – subscribe to the mailing list using majordomo, see homepage • Course labs are 232 and 329 Sieg Hall – lab has NT machines w/X servers to access UNIX • All programming projects graded on UNIX/g++ What is this Course About? Clever ways to organize information in order to enable efficient computation – What do we mean by clever? – What do we mean by efficient? Clever? Efficient? Lists, Stacks, Queues Heaps Binary Search Trees AVL Trees Hash Tables Graphs Disjoint Sets Data Structures Insert Delete Find Merge Shortest Paths Union Algorithms Graphics Theory AI Applications Systems Used Everywhere! Mastery of this material separates you from: • Perhaps the most important course in your CS curriculum! • Guaranteed non-obsolescence! Anecdote #1 • N2 “pretty print” routine nearly dooms major expert system project at AT&T – 10 MB data = 10 days (100 MIPS) – programmer was brilliant, but he skipped 326… Asymptotic Complexity Our notion of efficiency: How the running time of an algorithm scales with the size of its input – several ways to further refine: • worst case • average case • amortized over a series of runs The Apocalyptic Laptop Seth Lloyd, SCIENCE, 31 Aug 2000 Big Bang Ultimate Laptop, 1 year 1 second 1E+60 1E+55 1E+50 2^N 1.2^N N^5 N^3 5N 1E+45 1E+40 1000 MIPS, since Big Bang 1E+35 1E+30 1E+25 1E+20 1000 MIPS, 1 day 1E+15 1E+10 100000 1 1 10 100 1000 Specific Goals of the Course • Become familiar with some of the fundamental data structures in computer science • Improve ability to solve problems abstractly – data structures are the building blocks • Improve ability to analyze your algorithms – prove correctness – gauge (and improve) time complexity • Become modestly skilled with the UNIX operating system (you’ll need this in upcoming courses) One Preliminary Hurdle 1. Recall what you learned in CSE 321 … – – – – proofs by mathematical induction proofs by contradiction formulas for calculating sums and products of series recursion Know Sec 1.1 – 1.4 of text by heart! A Second Hurdle • Unix Experience 1975 all over again! – Try to login, edit, create a Makefile, and compile your favorite “hello world” program right away – Programming Project #1 distributed Wednesday – Bring your questions and frustrations to Section on Thursday! A Third Hurdle: Templates class Set_of_ints { public: insert( int x ); boolean is_member( int x ); … } template <class Obj> class Set { public: insert( Obj x ); boolean is_member( Obj x ); … } Set <int> SomeNumbers; Set <char *> SomeWords; In Every Silver Lining, There’s a Big Dark Cloud – George Carlin • Templates were invented 12 years ago, and still no compiler correctly implements them! • Using templates with multiple source files tricky – See Course Web pages and TAs for best way • MAINTAINING SANITY RULE – Write/debug first without templates – Templatize as need – Keep it simple! Handy Libraries • From Weiss: vector < int > MySafeIntArray; vector < double > MySafeFloatArray; string MySafeString; • Like arrays and char*, but provide – bounds checking – memory management • STL (Standard Template Library) – most of CSE 326 in a box – don’t use (unless told); we’ll be rolling our own C++ Data Structures One of the all time great books in computer science: The Art of Computer Programming (1968-1973) by Donald Knuth Examples in assembly language (and English)! American Scientist says: in top 12 books of the CENTURY! Very little about C++ in class. Abstract Data Types Abstract Data Type (ADT) Mathematical description of an object and the set of operations on the object tradeoffs! Data Types integer, array, pointers, … Algorithms binary search, quicksort, … ADT Presentation Algorithm • Present an ADT • Motivate with some applications • Repeat until it’s time to move on: – develop a data structure and algorithms for the ADT – analyze its properties • efficiency • correctness • limitations • ease of programming • Contrast strengths and weaknesses First Example: Queue ADT • Queue operations – create – destroy – enqueue G enqueue – dequeue – is_empty FEDCB dequeue A • Queue property: if x is enQed before y is enQed, then x will be deQed before y is deQed FIFO: First In First Out Applications of the Q • Hold jobs for a printer • Store packets on network routers • Make waitlists fair • Breadth first search Circular Array Q Data Structure Q 0 size - 1 b c d e f front back enqueue(Object x) { Q[back] = x ; back = (back + 1) % size } How test for empty list? dequeue() { x = Q[front] ; front = (front + 1) % size; return x ; } What is complexity of these operations? How to find K-th element in the queue? Limitations of this structure? Linked List Q Data Structure b c d front enqueue(Object x) { back->next = new Node(x); back = back->next; } dequeue() { saved = front->data; temp = front; front = front->next; delete temp ; return saved;} e f back What are tradeoffs? • simplicity • speed • robustness • memory usage To Do • Return your survey before leaving! • Sign up on the cse326 mailing list • Check out the web page • Log on to the PCs in course labs and access an instructional UNIX server • Read Chapters 1 and 2 in the book