CSE100 Algorithm Design and Analysis (Spring semester 2012)


Miguel Á. Carreira-Perpiñán
Associate professor
Electrical Engineering and Computer Science
School of Engineering
University of California, Merced
mcarreira-perpinan-[at]-ucmerced.edu; 209-2284545
Office: 284, Science & Engineering Building

Office hours: Tuesdays/Thursdays 4:15-5:15pm Tuesdays 11am-12pm and Thursdays 4:15-5:15pm (SE284).

TA: Max Vladymyrov, mvladymyrov-[at]-ucmerced.edu. TA hours: Mondays 9-11am (AOA142).

Lectures: Tuesdays/Thursdays 3-4:15pm (KOL217)

Lab class: Fridays 1:30-4:20pm (section 03L) and 4:30-7:20pm (section 02L) (Linux Lab, SE100)

Course web page: http://faculty.ucmerced.edu/mcarreira-perpinan/CSE100

Course description

The course introduces the basics of computational complexity analysis and various algorithm design paradigms. It covers the major algorithms and data structures for searching, sorting, parsing, and memory management. Other topics include theoretical models of computation, concepts of algorithm complexity, computability, and NP-completeness.

Prerequisites: CSE31; proficient level of programming skills in C/C++/Java and elementary data structures; basic math and probability knowledge.


Required textbook (get the errata):

The companion site for the book has additional materials (partial solutions, etc.).

Other books recommended as additional reading:

Syllabus and required textbook reading


Topics: Asymptotic notation. Divide-and-conquer. Recurrent equations and the master theorem. Space and time complexity. Loop invariants. Linear and binary search. Sorting algorithms: insertion sort, selection sort, mergesort, quicksort, heapsort. Sorting lower bounds. Heaps. Binary search trees. Hash tables with chaining and open addressing. Dynamic programming and greedy algorithms. Graphs: definition and relevant problems (path search, flow, minimum spanning trees).

The course will follow parts I, II, III, IV and VI of the textbook (skipping occasional topics).

Textbook reading (table of contents):


Homework (to do on your own, graded):


Optional project (to do on your own, for extra credit): experimental run times of sorting algorithms. In groups of 2 students (or, exceptionally, individually). Due May 6 11:59pm PST by email to the TA.

Course grading

While I encourage you to discuss your work with other students, the homeworks, lab assignments, project and exams must be the result of your own work without collaboration.

Grade curves: midterm, final.



Programming resources:

Plotting resources:

Job interview questions about algorithms:

Miguel A. Carreira-Perpinan
Last modified: Mon Apr 16 17:41:17 PDT 2012

UC Merced | EECS | MACP's Home Page