1. INTRODUCTION TO DATA STRUCTURES AND ALGORITHMS Thomas Kuehne School of Engineering and Computer Science, Victoria University of Wellington COMP 103 2016-T2 Welcome  Thomas Kuehne, Marcus Frean,

2. 2 PEOPLE  Co-ordinator: Alex Potanin [CO262, 463-5302] Office hours: Tuesdays 10:00a.m. – 12:00 p.m  Lecturers: Thomas Kuehne, Lindsay Groves  Senior Tutor: Zarinah Amin [Co343, 463-5936]  Email: firstname.lastname@ecs.vuw.ac.nzfirstname.lastname@ecs.vuw.ac.nz  Course URL: http://ecs.victoria.ac.nz/Courses/COMP103_2016T2  Class Rep:YOUR NAME HERE?! 2

3. 3 ADMINISTRATION  Prerequisite:  You need to have passed COMP112, or COMP102 with a B- or better.  If you did not meet this, you can take 102/112 again. 3

4. 4 HELPING YOU SUCCEED 4

5. 5 LECTURES Mon-Wed-Fr in HM LT205  Slides  on course webpage  print yourself  video recordings  Goals  Provide a framework for your learning  Provide explanations/demonstrations  SLIDES NOTES TEXTBOOK 5

6. 6 TUTORIALS  Run by a successful former student of 103  Starting next week  locations → “Timetable” at COMP 103 pages  What happens  quick quiz  work with peers to understand tricky bits  The tutor will set topical problems – you will work out answers, get feedback, discuss with the tutor and each other...  Our aim: help you to understand both lectures and assignments better 6

7. 7 ASSIGNMENTS  Critical for your learning!  10 Assignments  total of 20%  out: Fridays  due: Fridays (before lecture) (submitted electronically)  Solutions will be available after hand-in time.  Late assignments cannot be marked. 7

8. 8 ASSIGNMENTS Some THEMES for the assignments  Graphical editors: painting, diagrams, family trees..  Processing files of TEXT DATA: analysing data files, stories, web pages etc.  Simulations: programs that implement real world behaviour  Do it yourself – no pairing up  You can work in the ECS labs at all sorts of hours of day and night  Register on a lab computer to obtain a user login (if you haven’t already got one from 102/112) 8

9. 9 HELP DESK  Intended for small groups...  One-on-one help with assignment work  No direct solutions will be provided  Close to the labs but not in them print your code & highlight aspects to discuss  Where and When → “Timetable” at COMP 103 pages 9

10. 10 TEXT BOOK  JAVA FOUNDATIONS: Introduction to Program Design & Data Structures by Lewis, DePasquale and Chase - 2 nd or 3 rd edition is best  SAME textbook as comp 102/112  COMPLEMENTS lectures and assignments (but we do not always follow the text closely) 10

11. 11 WEB RESOURCES  FORUM  Post questions  Collaborate and help each other  Course staff monitor and answer when appropriate  NO posting chunks of ANSWERS to assignments!  all lecture slides and assignments  videos  links to Java reference material  tips on getting Java and BlueJ working at home 11

12. 12 ASSESSMENT  10 Assignments[20%]  Mid-term test[20%] 45 mins, close to break  Tutorials – participate![ 2%]  Final Exam [58%] 2 hours, in exam period Mandatory Requirements:  submit reasonable attempts for at least 7 out of 10 Assignments (may also be used for borderline cases and aegrotats)  at least a D in the exam  and (as always) at least ‘C-’ grade overall 12

13. 13 PLAGIARISM UNACCEPTABLE  We want you to LEARN, TALK to each other, learn TOGETHER, and HELP each other, but PLAGIARISM is UNACCEPTABLE!  Got help from anybody other than lecturer or tutor ? STATE IT ON THE ASSIGNMENT!  Copied bits of code from anywhere other than lecture slides or textbook ? STATE IT ON THE ASSIGNMENT! 13

14. 14 SAFETY in the LABS  Please be safe in the computer labs  Read the POSTERS in the lab  Listen to Roger Cliffe  See student health quickly if you get problems 14

15. 15 QUICK RECAP  What was in comp 102/112?  Classes, Objects, Fields, Methods  Conditionals, Loops (if, if...else, for, while, do..while)  Using variables, reading input, writing, drawing  Algorithm design  Using GUI’s (Graphical User Interface)  Arrays, and using ArrayList Revise these concepts if necessary! 15

16. 16 Some Basic Terms  Algorithm: step-by-step process to solve a problem (pseudocode: part code, part English)  Program: actual implementation of an algorithm in a programming language  Data Structure: the way data is structured or organized (example: Array)  Collection: an object that serves as a container for other objects (it aggregates them) 16

17. COLLECTIONS  Many real life examples involve what we could call Collections, and this is reflected in programs written to help real life:  Collections of books, music, photos, clothes,...  Organized in a way to ease access and management  Some STANDARD types of Collections we will use in our programs:  List, Set, Bag, Stack, Queue, Trees, Map 17

18. 18 Varieties of collection  Different structures  No structure – just a collection of values  Linear structure of values – order matters  Hierarchical structures  Different constraints for accessing elements  get, put, remove anywhere  get, put, remove only at the ends, or only at top (and so on). 18

19. WHAT CAN YOU EXPECT...  Using and understanding the current Java Collections Library  Creating your own Collections  How to add, remove, search, sort,... efficiently So this is what 103 is about:  The fundamental data structures of computer science  The crucial algorithms on those structures  Especially the efficiency of those algorithms 19

20. 20 Course Overview – Part 1 Programming with Linear collections  Different Kinds of collections:  Lists, Sets, Bags, Maps, Stacks, Queues, Priority Queues  Using, implementing, sorting, and searching these linear collections... 20

21. 21 Course Overview – Part 2 Programming with Hierarchical collections  Building, traversing Tree-structured collections  Re-implementing linear collections  with binary search trees  with partially ordered trees  with hash tables 21

22. 22 RECURRING THEMES  Good Design Choosing appropriate implementations How do you get it right first time ?  Efficiency How fast is it ? How much memory does it take ? Analysis and benchmarking 22