CS 3343/3341 Analysis of Algorithms
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.
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.
From the instructor: 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.
Time: TR 4:00pm - 5:15pm
Location: FLN 3.02.02
Time: T 8:30-9:20am and R11:30 - 12:20pm
Location: FLN 3.02.10A
Exam 1 15%
Exam 2 15%
Final Exam 30%
Lab Work and attendence 10%
Homework assignments 30 %
One lowest grades 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
make up exams. The grade that you obtain for the course will also serve as the
grade for the lab. The instructor, however, reserves the right to adjust the weights of individual components if necessary.
The instructor, however, reserves the right to adjust the weights of individual components if necessary.
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.
Tentative lecture schedule: (Scheule and lecture slides are for information only and are subject to change without notice.)
|1||8/29||Introduction, administration||Slides||Ch 1,2|
|2||9/3||Basics, asymptotic notation||Slides||Ch 3||HW1 solution||Course Policy|
|9/5||Asymptotic notation||Slides||Ch 3||
|3||9/10||Analyzing recursive algorithms - defining recurrence||Slides||
|9/12||Analyzing recursive algorithms - recursion tree method||Slides||Ch 4|
|4||9/17||Analyzing recursive algorithms - master theorem||Slides||Ch 4||HW3 solution||
|9/19||Analyzing recursive algorithms - substitution method||Slides||Ch 4|
|5||9/24||Analyzing recursive algorithms - substitution method||Slides||Ch 4|
|9/26||Review for exam 1, Quick sort||Slides||Ch 4||
|6||10/1||Quick sort||Slides||Ch 1-4, 7||
|10/3||Heap sort & Priority queue||Slides||
Linear time sorting algorithms
|10/10||Exam 1 (covers week 1-5)|
|8||10/15||Order statistics||Slides||Ch 9||HW4 solution|
|10/17||Order statistics||Slides||Ch 9|
|9||10/22||Dynamic programming||Slides||Ch 15|
|10/24||Dynamic Programming||Slides||Ch 15||HW5 solution||HW4|
|10||10/29||Dynamic Programming||Slides||Ch 15|
Intro to graphs
|Slides||Ch 22||HW6 solution||
|11/7||Minimum spanning tree||Slides||Ch 23|
|12||11/12||Review for exam 2||Slides||HW6|
|11/14||Shortest paths||Slides||Ch 24|
|13||11/19||Graph search, topological sort||Slides||Ch 24|
|11/21||String matching||Slides||Ch 32||HW7I solution|
Exam 2 (Covers topics from week 5 - week 10)
|15||12/3||String matching||Slides||HW7 part II|
Final: Dec 16, Monday, 3:15 pm - 5:45 pm