Course staff & office hours
| Instructor: | Jesse Tov | jesse@eecs |
Ford 2-215 | M 2–4, Tu 11-1, and gladly by appointment |
|---|---|---|---|---|
| TAs: | Yang Hu | yanghu2019@u |
Wilkinson Lab | W 2–4 |
| Arindam Paul | ArindamPaul2012@u |
Tech LG65 | M 10–12 | |
| Pei Yu | PeiYu2018@u |
Tech D130 | Th 3–5 |
General information
EECS 214 teaches the design, implementation, analysis, and proper application of abstract data types, data structures, and their algorithms. Topics include: data versus information, correctness, asymptotic analysis, and a wide variety of data structures.
Prerequisites
This course assumes familiarity with programming as taught in EECS 111 and 211.
Exams
We will have two in-class examinations:
- Monday, October 26
- Wednesday, December 2
There will be no final exam.
Materials
Software
Language versions TBD.
Books
There is no required textbook, but you may find these books useful:
- Udi Manber, Introduction to Algorithms: A Creative Approach shows how to design data structures and algorithms in a methodical way similar to the design recipe many of you learned in EECS 111. (This book is out of print, but used copies are available on Amazon.)
- Duane Bailey, Data Structures in Java, for the Principled Programmer may be a good reference for those of you who are working in, or can read, Java. (This book is a free PDF download.)
- Cormen, Leiserson, Rivest, and Stein, Introduction to Algorithms is a comprehensive, dense reference that isn’t always easy to understand, but covers almost anything you might want to know.
Online resources
- Piazza discussion board—ask questions here!
Lectures
This table specifies the lecture schedule; topics are tentative.
| September | ||
|---|---|---|
| M | W | F |
| 21 Intro: What’s a data structure? [notes] | 23 EECS 214 [notes] | 25 The Random Access Machine model* [slides] |
| 28Set theory* [notes] | 30More discrete math* [notes] | |
| October | ||
| M | W | F |
| 2Even more discrete math [notes] | ||
| 5- cancelled - | 7Prefix codes* [notes] | 9Huffman trees† [notes] |
| 12Trees† and tree walks§ [notes] | 14Linked lists† | 16Circular and doubly-linked lists† |
| 19Sequences‡ (lists†, arrays†) [slides] | 21Intro to complexity* [slides] | 23Exam review [practice questions, solutions] |
| 26Exam 1 | 28Asymptotic complexity* [slides] | 30Big-O notation in practice* [slides, code] |
| November | ||
| M | W | F |
| 2Abstract data types* (FIFO queues‡, ring buffers†, priority queues‡) [slides, code] | 4Binary heaps† [slides] | 6Binary search trees† [slides, code] |
| 9 AVL trees†; representation invariants* [slides, code] | 11 13Amortized analysis* (dynamic arrays†) [slides] | |
| 16Disjoint sets‡ (union-find†) [slides] | 18Probabilistic data structures* (Bloom filters†, hash tables†) [slides] | 20Graphs‡ and graph search§ [slides] |
| 23Graph representations (adjacency lists† and matrices†) [slides] | 25 Single-source shortest path algorithms§ [slides, code] | 27– No class: Thanksgiving – |
| 30Review session | ||
| December | ||
| M | W | F |
| 2Exam 2 | 4The take-away | |
Legend
| * | concepts and skills |
| † | concrete data structures |
| ‡ | abstract data types |
| § | algorithms |
Homework schedule
General homework policies are here.
| Link | Assigned | Due |
|---|---|---|
| Homework 2 | Mon., Nov. 9 | Mon., Nov. 16 at 11:59 PM |
| Homework 3 | Mon., Nov. 16 | Mon., Nov. 23 at 11:59 PM |
| Homework 1 and guide | Tue., Oct. 13 | Mon., Dec. 7 at 11:59 PM |
| Homework 4 | Mon., Nov. 23 | Mon., Dec. 7 at 11:59 PM |
Course policies
Collaboration and academic integrity
You may not collaborate with anyone on any of the exams. You may not use any electronic tools, including phones, tablets, netbooks, laptops, desktop computers, etc. If in doubt, ask a member of the course staff.
Some homework assignments will be completed with an assigned partner, and some may involve a larger team (TBD). You must collaborate with your assigned partner or team, as specified, on homework assignments. You may request help from any staff member on homework. (When you are working with a partner, we strongly recommend that you request help with your partner.) You may use the Piazza bulletin board to ask questions regarding assignments, so long as your questions (and answers) do not reveal information regarding solutions. You may not get any help from anyone else on a homework assignment; all material submitted must be your own. If in doubt, ask a member of the course staff.
Providing illicit help to another student is also cheating, and will be punished the same as receiving illicit help. It is your responsibility to safeguard your own work.
Students who cheat will be withdrawn from the course and reported to the appropriate dean.
If you are unclear on any of these policies, please ask a member of the course staff.
Homework
In general, you should submit your homework according to the instructions on the web page for the individual assignments.
More TBD
Late work
TBD
Grades
Your grade will be based on your performance on four programming assignments and two midterm exams, equally weighted. There will be no final exam.
The mapping of raw point totals to letter grades is at the discretion of the instructor.