Spring Quarter, 2007

Intermediate Data Structures and Algorithms

News

Jun 4: warm-up problems for Final posted.

May 31: hw3 solution posted.

May 31: syllabus final posted.

May 23: prj3 posted.

May 18: warm-up problems for Quiz 2 posted.

May 16: hw3 posted.

May 8: "graph" slides posted.

May 2: project 2 posted.

Apr 27: mock exam posted (for Quiz 1).

Apr 27: warm-up problems for Quiz 1 posted.

Apr 25: syllabus for Quiz 1 posted.

Apr 25: Homework 2 posted.

Apr 19: Homework 1 solution posted.

Apr 18: "dynamic programming" slides posted.

Apr 18: "greedy" slides posted.

Apr 16: "divide and conquer" slides posted.

Apr 12: office hours cancelled.

Apr 11: Project 1 posted.

Apr 6: Lab 2 posted.

Apr 4: Homework 1 posted.

Apr 2: Both lab sessions will be offered.

Mar 30: "Intro" and "Algorithm Analysis" slides posted.

Lecture Schedule Lab Session Topics Email list Turnin Grade mapping Previous offerings Resources Tutorials Animations

Overview

CS 141 introduces what many say is the core of Computer Science: data structures like graphs, and problem solving techniques. This material is essential in almost all of our upper-division courses.

Catalog description: CS 141 Intermediate Data Structures and Algorithms 4 Lecture, 3 hours; laboratory, 3 hours. Prerequisite(s): CS 014 with a grade of "C-" or better; CS 111/MATH 111; MATH 009C or MATH 09HC; proficiency in C++. Explores basic algorithm analysis using asymptotic notations, summation and recurrence relations, and algorithms and data structures for discrete structures including trees, strings, and graphs. Also covers general algorithm design techniques including "divide-and-conquer," the greedy method, and dynamic programming. Homework and programming assignments integrate knowledge of data structures, algorithms, and programming.

UCR course schedule, UCR course catalog. Note: Students receiving less than a C- in the CS 14 prerequisite will be dropped automatically a few weeks into the quarter, as the course relies heavily on basic knowledge of and skills in data structures, discrete mathematics, and programming.

Basic information

Syllabus: Download the PDF file.

Instructor: Stefano Lonardi (stelo@cs.ucr.edu)
Office hours: Mon and Thu 4-5pm. Office: Engineering 2, 317.
Teaching Assistants and office hours:

Elena Harris (elenah@cs.ucr.edu), Office hours: Monday 12-1pm and Thursday 1pm-2pm

Office hours are held in Engineering 2, 110.
Lectures:

MWF 1:10-2:00, SPR 2339

Labs:

(021) T 8:10 a.m.-11:00 a.m., EBU2 135, Elena

(022) T 2:10 p.m.-5:00 p.m., EBU2 135, Elena

Academic Excellence Workshops:

T and R, 1-2 pm, EBU2 103, Ben

Text Book:

Introduction to the Design and Analysis of Algorithms, 2nd edition, by A. Levitin.

References:

Introduction to Algorithms (2nd Edition) by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Cliff Stein, MIT Press.

Algorithm Design (Foundations, Analysis, and Internet Examples) by Michael T. Goodrich and Roberto Tamassia, Wiley.

Approximate Time Requirements: This is a four-unit CS course. As such, you should expect to spend the following approximate amount of time: 3 hours/week in lecture
3 hours/week in lab
6 to 10 hours/week doing individual study (readings, homeworks, programming assignments, preparation for lectures, etc).
Please don't underestimate the time you will need to spend on this course. These are real time amounts spent by average successful past students. Computer Science and Engineering are challenging disciplines requiring extensive time to master.

Lectures

See the syllabus. Read the book before lecture! Reading ahead is one of the most effective ways of doing better in class -- you'll be amazed how much more comprehensible and useful the lectures will be. The schedule is subject to change as the quarter progresses.

Lecture Notes:

Course Overview [PDF]

Algorithm Analysis [PDF]

DivideConquer [PDF]

Greedy [PDF]

Dynamic Programming [PDF]

Graphs [PDF]

Weighted Graphs [PDF]

String Matching

Tentative list of topics

week 1: Course overview, analysis of algorithms

week 2: Discrete math for algorithm analysis

week 3: Greedy approach for algorithm design

week 4: Divide and conquer, dynamic programming

week 5: Graphs, and their representation

week 6: Graph traversal, connectivity

week 7: Minimum cost spanning tree, single-source shortest path

week 8: All-pais shortest path

week 9: String matching, KMP

week 10: NP completeness, review

Actual list of topics

Apr 2nd: Overview of the course.
Apr 4th: Algorithm Analysis [slides 1-27][HW1 posted]
Apr 6th: Algorithm Analysis [slides 28-40]
Apr 9th: Algorithm Analysis [slides 41-60]
Apr 11th: Algorithm Analysis [slides 61-77] [PRJ1 posted]
Apr 13th: Algorithm Analysis [slides 77-88]
Apr 16th: Algorithm Analysis [slides 89-end]
Apr 18th: DivideConquer [1-20] [HW1 due]
Apr 20th: DivideConquer [21-end]
Apr 23th: Greedy [1-29]
Apr 25th: Greedy [30-45][HW2 posted] [PRJ1 due]
Apr 27th: Greedy [46-end]
Apr 30th: Prep for Quiz 1
May 2nd: QUIZ 1 (in class, closed book, closed notes) [PRJ2 posted]
May 4th: Dynamic programming [1-29]
May 7th: Dynamic programming [30-38]
May 9th: Dynamic programming [39-end] [HW2 due]
May 11th: Graphs [1-21]
May 14th: Graphs [22-45]
May 16th: Graphs [46-81] [HW3 posted] [PRJ2 due]
May 18th: Graphs [81-end]
May 21th: Prep for Quiz 2
May 23th: QUIZ 2 (in class, closed book, closed notes) [PRJ3 posted]
May 25th: Weighted graphs [1-20]
May 28th: HOLIDAY - MEMORIAL DAY
May 30th: Project 3 overview, Weighted graphs [21-34] [HW3 due]
Jun 1st: Weighted graphs [35-55]
Jun 4th: Weighted graphs [56-78]
Jun 6th: Weighted graphs [78-end][PRJ3 due]
Jun 8th: Prep for Final
Jun 12th: Final 3-6 pm, Sproul 2339

Do not put off reading the assignments or you will risk falling behind. Reading ahead is one of the most effective ways of doing better in class -- you'll be amazed how much more comprehensible and useful the lectures will be.

Homework

Homework 1 [PDF] (posted Apr 4th, due Apr 18th)
Homework 1 solution [PDF] (posted Apr 19th)
Homework 2 [PDF] (posted Apr 25th, due May 9th)
Homework 2 solution [PDF] (posted May 9th)
Homework 3 [PDF] (posted May 16th, due May 30th)
Homework 3 solution [PDF] (posted May 31th)

Projects

Project 1: BigInt (posted Apr 11, due Apr 25)
Project 2 (posted May 2nd, due May 16th)
Test input for Project 2
Project 3 (posted May 23th, due June 6th)

Quizzes

Labs

Week 1:
Introduction of TA; class accounts, Moodle and mailing list
Debugging and testing in C++; working on Linux
Counting execution time of a program
Review of linear, tree and graphical data structures
Top-down design of algorithms; pseudo-code
Asymptotic (big-O, Theta) analysis of running time
More details

Week 2:
Preview the first homework.
More asymptotic analysis of algorithms
Treatment of for-loops using summation
Pointers and recursive algorithms/programs
More details

Week 3:
Preview the first programming assignment
Recurrence relations and analysis of recursive algorithms
Recursive programming - computing the Fibonacci function
More details

Week 4:
Review the first homework solution
Review the first programming assignment
Example of the greedy method
Implementation of the task scheduling algorithm
More details

Week 5:
Preview the second homework
Go over some of the questions in the warm-up and in the mock exam
More details

Week 6:
Address questions regarding the second homework
Address questions regarding Quiz 1
Preview the second programming assignment
Implementation of the knapsack (dynamic programming) algorithm
More details

Week 7:
Go over the solution of the second homework
Address questions regarding the second programming assignment
Discuss data structures for graphs and digraphs
Implement DFS for undirected graphs
More details

Week 8: Preview the third homework
Implement topological sorting
More details

Week 9: Answer questions about the third homework
Answer questions about project 3.
Discuss Dijkstra and Bellman-Ford algorithms
Implement transitive closure
More details

Week 10:
Review the third homework solutions
Review for the final exam
More details

General course features and policies

Material covered: Lectures don't cover all required material, which also appears in the text and reference books and may be covered only in the lab sessions.
Academic dishonesty: Cheating will be strongly punished (typically with an F in the course). You can report cheating anonymously at: https://www.cs.ucr.edu/cheating/. Assignment submissions must represent your original work. Copying from any sources (web, other books, past or current students, etc.) is strictly prohibited -- learning to program requires you to learn to solve programming problems by yourself; using existing code and other resources becomes important later on in your studies. While discussing assignments together is encouraged, team coding (even of pseudo-code) or letting others see your code are specifically not allowed. Be aware that programs are automatically compared to the current and prior quarter's programs for plagiarism, using a sophisticated code-comparison tool that ignores insignificant differences (like whitespace and variable names). Be aware that a subset of exams may be photocopied, for comparison with exams submitted for regrades. Also, be aware that lying to an instructor in order to be able to makeup a missed exam or in other ways to obtain a better grade can be treated as academic dishonesty.
Regrade policy: Regrade requests must be submitted in writing and within two weeks of the distribution of the graded material. The entire homework/test/assignment may be regraded, not just the problem in question, so the grade may go up or down. Thus, think your regrade requests through carefully. To have a homework/test regraded, communicate with the TA(s) who graded the involved questions. For assignments, send email requests to the CS141 grader account (cs141-g) with detailed explanations. Recording errors should also be pointed out to TAs or the instructor before the last class.
Final grades: Per university policy, changes to your final grade will be made only in the event of a clerical error. Asking your instructor how far you were from a cutoff and what extra work you can do to improve the grade is not appropriate.
Communicating with the instructors and TAs: When sending electronic mail to the instructors or TAs or graders, please include your full name, student ID number, and UCR email address, so that we may properly identify you (remember, many students have similar names). Also, please try to be polite and use reasonable grammar and formatting.
Cell phones: During lectures and lab sessions, please turn off your cell phone. During exams, cell phones must not be visible (e.g., store them inside a backpack).
Written Assignments: All assignments and solutions will be posted on the class homepage. Write your full name with upper-case LAST name, assignment number, student ID, login, class section, lab section. Write legibly: what cannot be read will not be graded. Consider typing the assignment if you handwriting is hard to read. Written assignments have to be submitted before the beginning of the class on the due date on the instructor's desk. Include the following on first page ``I certify that this submission represent my own original work'' (date, signature). No late assignment will be accepted. Any problem with grading of a written assignment should be addressed at the latest two weeks after the assignment is returned to you.
Programming assignments: All programming assignments will be turned in electronically. Each file should begin with our report template header. Source code should comply with professionally accepted coding standards. In particular, all code must be compiled with the -Wall -W -Werror command line options, or else it will not be graded. Also, you must include a section explaining the design, structure, etc of your program and how it works. Comments in source code are important, but they are not a replacement for an explanatory section. Please remember that successfully writing a computer program that compiles and runs correctly is not something anyone can do in just a few minutes, even when it looks easy. Debugging typically takes three times longer than figuring out how to write your program. So don't leave your programming assignments to the last minute!
Reading: Read the current book sections before coming to lecture, and attend all lectures in their entirety. Feel free to ask questions.

Lab guidelines

Students are expected to attend the lab sessions in their entirety. The lab sessions typically consist of tutorials, discussions, reviews, practical exercises/tests, and time for students to work on homes and programming assignments.
During lab tutorial/discussion/review time, students should not use the computers. Ideally, students would move their chairs to the whiteboard area.
To reduce disruptions and provide for the best educational environment, all persons in lab during scheduled lab time should be formally registered in that section. In general, no swapping sections and no unregistered people in the lab are allowed, even if there are extra computers.

90+ -> A+
85+ -> A
80+ -> A-
77+ -> B+
73+ -> B
70+ -> B-
67+ -> C+
63+ -> C
60+ -> C-
57+ -> D+
53+ -> D
50+ -> D-
49- -> F

Intermediate Data Structures and Algorithms

News

Overview

Basic information

Lectures

Homework

Projects

Quizzes

Labs

General course features and policies

Lab guidelines

Electronic assignment turn-in

Anonymously report suspected cheating

Grade mapping

Course email list

Previous course offerings' web pages

Tutorials

Algorithm Animations