CS 315: Algorithms & Data Structures

Instructor: Gordon S. Novak Jr., CSA 1.110; Office Hours: M T Th 1:00 - 1:50.

TAs:

• Hrishikesh B. Acharya, acharya@cs.utexas.edu       Office Hours: M T W 4-5 at TA Station 1, PAI 5.33 .
• Xie, Chao chao@cs.utexas.edu       Office Hours: W 2-4 and F 2-3, PAI 5.33 .
• Ali Muqeet muqeet@cs.utexas.edu       Grading.

Lab Proctor will be in the lab to help with programming projects:

• Tomas McCandless: tomniscientia@gmail.com
  Hours: PAI 5.38, Mon: 9:00-10:00, 12:00-3:30, 5:30-8:30;   Tues: 9:00-11:00, 12:30-2:00;   Wed: 9:00-10:00, 1:00-4:00, 5:30-8:30;   Thurs: 9:00-11:00.

Syllabus

Text: Mark Allen Weiss, Data Structures and Algorithm Analysis in Java, 2nd Ed.; Amazon; Barnes & Noble.

Lecture Notes: Available in printed form in WEL 2.228. Buying the printed notes is strongly recommended so that you can take notes on them during class.
Lecture Notes by Contents or Index or PDF      DO NOT print out the slides on CS department printers.

Vocabulary

Follow CS 315 Discussions on Piazza

DrJava provides an interactive development environment for Java. Documentation at the preceding link. There is also a DrJava plugin for Eclipse at the preceding link. Downloads: Use their downloads or these copies: Windows (right-click and select Save Target As), Mac OSX, JAR file .

Programming assignments will mainly be done in Java, with an option to do some in Lisp or Scheme. All programming assignments must be your own individual work. Program files are provided, in the directory /projects/cs315/ or in the FTP directory for Program Files, ftp://ftp.cs.utexas.edu/pub/novak/cs315/ for use with the assignments. It is legal to use any of these files as part of your programs.

How to Turn in Assignments

Testing and Debugging

1. Timing and Big O   log-log paper (PDF)   semi-log paper (PDF)
2. Recursion and Lists
3. More Recursion and Lists
4. Merging and Stacks
5. Java List Library
6. Basic Trees
7. Trees and Symbolic Algebra   Handout (PDF)
8. Patterns
9. Memos and Drums
10. Do You Know the Way to San Jose Muleshoe?     Selected Answers
    
11. MapReduce
    MapReduce Paper
    NYT Article on Hadoop
    Google Code University
    Hadoop
    Lecture slides on PageRank
    

Goals of the Course:

• Understand the tools of the trade:
  • Data Structures that allow certain operations on the data to be done efficiently.
  • Algorithms that perform operations and maintain the data structure.
• Gain experience in using library packages
  • the buy-versus-build decision
• Understand performance:
  • Big O
  • How to analyze a problem, design a solution, and estimate the performance.
  • How to analyze an existing design or program, spot the performance problems, and fix them.
• Gain experience in other programming paradigms:
  • Lisp
  • Patterns or Rewrite Rules
  • MapReduce, Hadoop and data-intensive parallel programming

Topics:

• Introduction: why we need clever algorithms and data structures.
• Performance: Big O: how much time and storage are needed as data sizes become large
• Some Lisp: (+ x 3)
• Lists and Recursion; Stacks and Queues
• Trees and Tree Recursion
• Pattern Matching and Rewrite Rules
• Using Library Packages
• Balanced Trees and Maps
• Hashing and randomization; XOR
• Priority Queues
• Sorting, Merge
• Graphs
• Map, Reduce, and MapReduce

You can download Gnu Common Lisp for Linux or GCL for Windows or LispWorks for Mac.

Lisp is easier to use through the Emacs editor. Gnu Emacs can be dowloaded free, for Linux or Windows or Mac.

Song: "God Wrote in Lisp", Lyrics by Bob Kanefsky, sung by Julia Ecklar.

Final Exam Study Guide and Example Final Exam Questions