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CS2210 Data Structures and Algorithms Lecture 1: Course Overview

CS2210 Data Structures and Algorithms Lecture 1: Course Overview. Instructor: Olga Veksler. What is this course about?. We will study moderately complex data structures and algorithms that are essential in core areas of computer science Compilers Operating Systems Database Systems

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CS2210 Data Structures and Algorithms Lecture 1: Course Overview

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  1. CS2210Data Structures and AlgorithmsLecture 1: Course Overview Instructor: Olga Veksler

  2. What is this course about? • We will study moderately complex data structures and algorithms that are essential in core areas of computer science • Compilers • Operating Systems • Database Systems • Search Engines • etc. • This is one of the most important (and fun) courses you will take • Prerequisite for almost all other upper year courses Analysis of Algorithms

  3. Simple data structures you have seen Data structure = representation and operations associated with a data type Tree Array Set/bag Analysis of Algorithms

  4. Simple algorithms you have seen • Binary search • Bubble sort • Quick sort Analysis of Algorithms

  5. Knowledge Assumed • We assume you know basic data structures • Arrays, bags, lists, stacks, queues, linked lists • Functions, logarithms, exponents, sets, series, derivatives, limits • Abstract Data types • Basic object oriented design concepts • abstraction, encapsulation, modularity Analysis of Algorithms

  6. Skills Assumed • We assume you know how to program in Java • can design, implement, test, debug, read, understand and document relatively simple Java programs • including simple recursive code • This is not a course on Java. If you don’t know Java, start learning it now, before the programming assignments are due! • Books, tutorials on the web, etc. • Chapter 1 of our text book (Goodrich&Tamassia) gives a good introduction to Java Analysis of Algorithms

  7. What will you learn? • Analysis of moderately complex algorithms • How to predict algorithm’s performance • time and space complexity • Algorithm correctness • Moderately complex data structures that let us efficiently store, access, manage data • How to solve practical problems efficiently by choosing the appropriate data structures and algorithms Analysis of Algorithms

  8. Topics Covered • Analysis of algorithms • Time and space complexity • Correctness • Data Structures • Dictionaries, hash tables • Priority queues and heaps • Trees, binary search trees, multi-way search trees • Graphs • Algorithms • Binary Search, sorting, algorithms on trees and graphs • Java Interfaces; Java exceptions Analysis of Algorithms

  9. Contact Info • Instructor Information • Olga Veksler • Lectures: Tu 1:30-3:30, Th 2:30-3:30 • Office hours: Wed 10-12 • Lecture Notes • Available on the course web page Analysis of Algorithms

  10. Contact Info • Course Web Page • http://www.csd.uwo.ca/courses/CS2210b • You are responsible for checking the course web page frequently • I will post any important announcements on the web page (about homework, exams, etc.) Analysis of Algorithms

  11. Discussion board • I have set up a discussion board for the course (link from the course web page) • Use it to ask any questions about the course • You can post anonymously • You should also feel free to reply to other student’s questions • If you have a question about homework • Post it on the discussion board • Come talk to me or the TA • Please do not email me about homework, unless it is to set up a meeting outside the office hours  Analysis of Algorithms

  12. Course Prerequisites • Computer Science 1027a/b or 1037a/b with grade of at least 60% • One full-course equivalent from • Calculus 1050a/b, 1051a/b, 1081a/b, Linear Algebra 1040a/b, Applied Mathematics 1026, Mathematics 030, the former Mathematics 1027, 1023a/b,1024a/b, the former Mathematics 1027 • Knowledge of Java Analysis of Algorithms

  13. Textbook • Required: Data Structures and Algorithms in Java, fifth edition, Goodrich and Tamassia, John Wiley & Sons, 2010 • Supplementary: • Data Structures and Algorithms with Object Oriented Design Patterns in Java, Bruno R. Preiss, Wiley, 2000 • The Java Programming Language, Arnold and Gosling, Addison-Wesley, 1996. • Java, an Object Oriented Approach, Arnow and Weiss, Addison-Wesley, 1999. • Other books listed on the course web site Analysis of Algorithms

  14. Student Evaluation • Assignments 36% • 2 concept assignments, each worth 3% • 3 programming assignments, each worth 10% • Tentative Midterm Date 29%, 2 hours • Tuesday, February 28, in class • Final Exam 35%, 3 hours • If an assignment has to be cancelled, the remaining assignment weights will be readjusted, if the midterm has to be cancelled, final exam will be worth 64% Analysis of Algorithms

  15. Student Evaluation • To be eligible to pass this course need • 45% weighted average on the midterm and final exams and • 45% weighted average on assignments • To be eligible for an overall grade of 60% or higher, need • 55% weighted average on the midterm and final exams and • 55% weighted average on assignments Analysis of Algorithms

  16. Tentative Assignments Schedule • Assignment 1 (concept) due January 24 • Assignment 2 (programming) due February 9 • Assignment 3 (concept) due February 14 • Assignment 4 (programming) due March 15 • Assignment 5 (programming) due April 5 Analysis of Algorithms

  17. Tentative Assignments Schedule • Paper copy of assignments are due in class on the due date or electronically on webct • Programming assignments are to be submitted electronically on webct Analysis of Algorithms

  18. Exam Policies • There is no makeup for the Midterm, except for students requesting a special midterm exam for religious reasons. These students must have notified the course instructor and filed documentation with their Dean’s office at least 2 weeks prior to the Midterm Exam • If you miss Midterm for any other valid reason, present documentation to the Dean’s office; your Final exam score will be re-weighted to include the weight of the Midterm Analysis of Algorithms

  19. Class Attendance • Not required, but strongly encouraged • Lecture notes is only a summary of things happening in class, will not contain many examples • Students who attend lectures tend to do better • Attending lecture is most efficient way to learn the required material Analysis of Algorithms

  20. Assignments • Will be posted on the web site • Concept Assignments • Each concept assignment consists of a set of exercises. It must be typed or neatly written • Programming assignments • Due by 11:59 pm on the due date • Java programs • Must run on the departmental computing equipment • Hand in using electronic submission procedures, to be described later Analysis of Algorithms

  21. Late Policy • Concept Assignments • No late concept assignments accepted • Programming assignments • 1 day late: 5% • 2 days late: 10% • 3 days late: 15% • 4 days late: 20% • 5 days late: not accepted • Saturday and Sunday count as one day Analysis of Algorithms

  22. Late Policy • Assignment extensions may be granted only by the course instructor • If you have serious medical or compassionate grounds for an extension, take the supporting documentation to the Dean of your faculty Analysis of Algorithms

  23. Assignment Marks Appeals • Address appeals to the TA first. If you and the TA cannot agree, then TA will discuss the situation with the instructor • Appeals must occur within 1 week from the first day that the marked assignments were made available to students. After 1 week, no appeals will be considered Analysis of Algorithms

  24. Ethical Conduct • All assignments are to be done individually • Assignments judged to be the result of academic dishonesty will, • First offence = -assignment weight • Second offence = failing mark • You are responsible for reading and respecting the Computer science Department’s policy on Scholastic Offences • http://www.csd.uwo.ca/UnderGrad/scholastic_offences.shtml • We have sophisticated software which will examine your code against everyone else in class Analysis of Algorithms

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