CS 3343.001/3341.001/3341.002 Analysis of Algorithms
Spring 2017


Disclaimer

This Syllabus is provided for informational purposes regarding the anticipated course content and schedule of this course. It is based upon the most recent information available on the date of its issuance and is as accurate and complete as possible. I reserve the right to make any changes I deem necessary and/or appropriate. I will make my best efforts to communicate any changes in the syllabus in a timely manner. Students are responsible for being aware of these changes.

Class Description

From the catalog: This course is to provide an introduction to the design and analysis of computer algorithms. The students will learn how to analyze the performance of computer algorithms, and programming techniques and data structures used in the writing of effective algorithms.

We will discuss classic algorithm design strategies (e.g., divide-and-conquer, dynamic programming, greedy approaches), data structures (e.g., hash tables, binary search trees), classic problems (e.g., sorting, knapsack problem, scheduling, graph-related problems) and the classic algorithms to solve them. We will also analyze algorithm complexity throughout, and touch on issues of tractibility such as NP-Completeness.

Objectives: to learn and apply techniques for the design and analysis of algorithms.

Prerequisites: CS 2123, CS 2233, CS 3333

Lecture (3343.001)

Time: TR 11:30am - 12:45pm
Location
: MH 3.04.22

Recitation (3341.001/002)

Time: T 1:00-1:50pm (Session 1) or R 1:00-1:50pm (Session 2)
Location: NPB 1.226

Textbooks:

Instructor:

Teaching Assistant:

 

Tentative lecture schedule: (Schedule and lecture slides are for information only and are subject to change without notice.)

Week

Date

Topic

Notes

Reading

Assignment

Due

Misc

1

1/10

Introduction, administration

Slides

Ch 1,2

 

 

Course Policy

1/12

Basics, asymptotic notation

Slides

Ch 3 

HW1 | solution

 

 

2

1/17

Asymptotic notation

Slides

Ch 3

 

 

1/19

Analyzing recursive algorithms - defining recurrence

Slides

Ch 4

 

3

1/24

Analyzing recursive algorithms - recursion tree method

Slides

Ch 4

HW1

 

1/26

Analyzing recursive algorithms - master theorem

Slides

Ch 4

HW2 | solution

 

4

1/31

Analyzing recursive algorithms - substitution method

Ch 4

 

2/2

Analyzing recursive algorithms - substitution method

Ch 4

 

 

5

2/7

Review for exam 1

Slides

Ch 1-4, 7

 

2/9

Quick sort

Ch 7

HW3 | solution

HW2

 

6

2/14

Heap sort & Priority queue

Slides

Ch 6

 

 

2/16

Linear time sorting algorithms

Slides

Ch 8

 

7

2/21

Linear time sorting algorithms

 

2/23

Exam 1 (covers week 1-4) solution

 

 

8

2/28

Order statistics

Slides

Ch 9

HW3 

 

3/2

Dynamic programming

Slides

Ch 15

HW4 | solution  

 

9

3/7

Dynamic programming

 

Ch 15

 

3/9

Dynamic Programming

Slides

Ch 15

 

10

 

Spring Break

11

3/21

Greedy Algorithm

Slides

Ch 16

HW5 | solution 

HW4 

 

3/23

Intro to graphs

Slides

Ch 22

 

 

12

3/28

Review for exam 2

Slides

 

HW6 | solution 

HW5

 

3/30

Minimum spanning tree

Slides

Ch 22

 

13

4/4

Minimum spanning tree

Ch 23

 

 

4/6

Shortest paths

Slides

Ch 24

HW7 | solution

HW6 

 

14

4/11

Graph search, topological sort

Slides

Ch 24

 

 

4/13

String matching

Slides

Ch 32

 

 

 

15

4/18

Exam 2 (Covers topics from 2/7 to 3/21) solution

 

4/20

String matching

Ch 32

HW8 | solution

 

16

4/25

P/NP

Slides

Ch 34

HW7

 4/27

Final review

Slides

Short

 

 

HW8

 

 

 

Final: May 9, Tuesday, 9:45 am - 12:15 pm

 

 

 

 

 


Grading

     In-class quizzes and attendance 5% 
     Homework assignments 25 %

     Exam 1 and Exam 2 grades will be averaged and compared with Final Exam grade; whichever is greater will weight 50% and the other will weight 20%.

 

I reserve the right to slightly adjust the weights of individual components if necessary.

One lowest grade in homework will be dropped.  Exams cannot be made up, cannot be taken early, and must be taken in class at the scheduled time.  There will be no makeup exams. The grade that you obtain for the course will also serve as the grade for the lab.

Since your grade is partially based on computer and homework assignments, they must be your own work. You can ask me questions about any aspect of an assignment and pursue general discussions with others on the system or on an approach to solving a problem. You may discuss high-level ideas and thoughts about a homework assignment with your other classmates, but you have to work out all details of any solutions discussed and write up the solution completely on your own. In particular, when working with a student on an assigned homework problem you should do so verbally -- Nothing should be written. This is aimed at keeping your discussion at a high level so everyone can work out the details on their own. Please follow the spirit of this rather than working to finds ways to share details verbally. Also you must clearly acknowledge anyone (except the instructor and TA) with whom you discussed any problem and say briefly what you discussed.

You are not allowed to read, copy, or rewrite the solutions written by others (in this or previous terms). Copying materials from websites, books or other sources is considered equivalent to copying from another student.

Every cheating (for example, copy homework solutions from the web, friends or other textbooks) will be reported to the office of academic integrity. If two people are caught sharing solutions then both the copier and copiee will be held equally responsible. Cheating on an exam will result in failing the course.

It is your responsibility to contact me in a timely manner if there are extenuating circumstances that impact your ability to perform in this class. Your grade is 'not given' by the instructor, but rather is earned by you through demonstrating your mastery of the subject.


Last modified by Jianhua Ruan,   jruan at cs.utsa.edu ,