Lecture: Monday, Wednesday, Friday 2:30-3:20 EEB 105
Optional TA-led meetings: Tuesdays 4:30-5:30 and Thursdays 4:30-5:20 in Bagley 154
Optional TA-led meetings will be held most but not all weeks and will be announced in advance
Aaron Bauer, Allen Center 220, Thursdays 10:30-11:30AM + by appointment + try stopping by at my shared office (Allen Center 324)
Nicholas Shahan, Allen Center 220, Mondays 11:30AM-12:30PM
Shuo Wang, Allen Center 220, Mondays 1:30PM-2:30PM
Yuanwei Liu, Allen Center 220, Tuesdays 9:30AM-10:30AM
Rama Gokhale, Allen Center 220, Tuesdays 12:30PM-1:30PM
Luyi Lu, Allen Center 218, Thursdays 11:30AM-12:30PM
Yunyi Song, Allen Center 220, Thursdays 3:30PM-4:30PM
Iris Jianghong Shi, Allen Center 220, Fridays 4:30PM-5:30PM
Course Email List (mandatory): You should receive email sent to the course mailing list regularly, roughly at least once a day. Any important announcements will be sent to this list.
Email sent to firstname.lastname@example.org (not @u...) will reach the instructor and all the TAs. For questions multiple staff members can answer, please use this email so that you get a quicker reply and the whole staff is aware of points of confusion.
All staff: email@example.com (not @u...)
Instructor: Aaron Bauer, firstname.lastname@example.org, not @u...
TA: Luyi Lu, email@example.com, not @u...
TA: Iris Jianghong Shi, firstname.lastname@example.org, not @u...
TA: Nicholas Shahan, email@example.com, not @u...
TA: Yuanwei Liu, firstname.lastname@example.org, not @u...
TA: Rama Gokhale, email@example.com, not @u...
TA: Shuo Wang, firstname.lastname@example.org, not @u...
TA: Yunyi Song, email@example.com, not @u...
Course Discussion Board (optional but encouraged)
Anonymous Feedback (goes only to the instructor)
Material in the future naturally subject to change in terms of coverage or schedule
Optional sections that cover certain topics more in depth from the lectures and may or may not have postable items.
Homework 0: on-line survey worth 0 points, "due" Friday January 10
The programming assignments will use Java. We will use Java 7, the most recent version of the language. So if installing Java on your own machine, you can get Java 7 from http://jdk7.java.net/.
We strongly encourage using the Eclipse IDE, though we will not require this. You can download Eclipse for your own machine from http://eclipse.org/downloads; it is also installed on all the lab machines. Some guidance on getting started with Eclipse is included in Homework 1.
The textbook is Data Structures and Algorithm Analysis in Java, Mark Allen Weiss, 3rd Edition, 2011, ISBN: 0132576279. Errata is here. Code from the book is here. We will also do our best to support the 2nd Edition, ISBN: 0321370139. Errata for the 2nd edition is here. Code for the 2nd edition is here. The textbook is also available for 4 hour loan at the Engineering library. The textbook often provides a second explanation for material covered in class.
A Java reference is also strongly recommended. While there are a variety of (more than) sufficient references, we recommend Core Java(TM), Volume I--Fundamentals 9th Edition, Cay S. Horstmann and Gary Cornell, 2002, ISBN: 0137081898.
Here are some interesting, usful, and accessible articles related to the course material. These are optional reading that you may find helpful and enriching.
Acknowledgments: Many of the materials posted here and used in the course have been shared and refined by many other instructors and TAs in previous offerings of CSE373, CSE332, and CSE326. This version of the course was particularly based on previous offerings by Ruth Anderson and Dan Grossman.