CSci 3501: Algorithms and Computability -- Syllabus

[Home] [Syllabus] [Assignments] [Resources]

The syllabus will be updated throughout the semester. Dates, topics, assigned reading, and problem set due dates will be added or might change. All changes in assigned reading and due dates will be announced in class (and occasionally by e-mail). While I will do my best to update the web site accordingly, it is a student's responsibility to keep track of the problem set due dates and reading assignments. If you are not sure about due dates, please don't hesitate to ask.

Reading assignments are listed for the day when the material is first explained in class. You may read the material ahead of the lecture or after, either way is fine.

The dates for the midterm exams are set and will not change. If you have a conflict with these dates, please let me know right away. No makeup exams will be given unless there are circumstances beyond your control AND the makeup time is arranged in advance.

In addition to exams there will be 7-10 short in-class quizzes throughout the semester. Quizzes will not be announced in advance. The lowest quiz grade will be dropped (i.e. not counted towards the quiz total). A missed quiz will receive a grade of zero and thus will be counted as the lowest grade, unless it was missed due to an illness or other circumstances beyond your control. If you missed a quiz or a lab because of an illness or similar circumstances, it is your responsibility to communicate these reasons to me as soon as possible and arrange for a make-up work.

The midterms, the final, and quizzes are open book, open notes, unless stated otherwise.

Policies on Collaboration and Use of Resources

Problem sets and labs are individual work, unless otherwise stated. While it's perfectly OK (and is encouraged) to discuss problem sets in general terms with others in the class, your solution must be your own work (i.e. written or coded by you without using anybody else's materials). Copying any part of another person's solution (even if you modify the code) is considered academic dishonesty and will be dealt with according to the university's policy.

Late problem sets policy: Problem sets are due in the beginning of the class on the due date. If a problem set is submitted at (or before) the next class meeting after the due date, it is graded out of 3/4 credit. If it is submitted any time after the next meeting (until the last class meeting), then it is graded out of 1/2 credit.
Problem sets submitted more than 5 minutes after beginning of the class may be considered late.

Groups for labs and problem sets

Hand in one assignment from the entire group with names of both students on the first page. If submitting by e-mail, you must CC it to all your partner(s). In a programming assignments make sure to keep track (on CVS, in comments or in some other electronic form) of each partner's contribution to the work.

Generally all group members get the same grade for the submitted group work. If you feel that your group members are not contributing the way they should or if there are any circumstances that prevent you or you partner from contributing a fair share, please talk to your partners to work out an arrangement (if possible) and in either case let me know right away. If after the assignment is finished you feel that the group members have contributed unevenly, please talk to me and I'll try to come up with a fair grading strategy.

Discussion with students other than those in your group (or anyone not in this class) should be limited to general approaches to the problem. All such discussions as well as use of sources other than the textbook and the handouts given in class must be acknowledged in the beginning of the problem solution. Use of any materials from previous runs of this class is not allowed.

Studying in groups

Studying in groups is strongly encouraged. You may study for tests, go over textbook materials or lecture notes, and discuss problem sets in general terms (i.e. without actually writing the formulas or giving out the answers).

Use of electronic devices

Use of laptops for class-related activities is usually allowed, except for test time and other specific assignments. Laptops and other devices may not be used for activities unrelated to the class work (checking e-mail, text messaging, etc.). The instructor reserves a right to ask a student to leave the class if the student uses electronic devices inappropriate in a class. No communication devices can be used during a test, including quizzes. If you are taking notes on your laptop, you are not allowed to access anything other than your notes during a test.

Reading assignments use the following abbreviations:

Course topics and timeline

Monday Wednesday Thursday - Lab Friday
Week 1: August 25 - 27
Summer break, no class Introduction; algorithms; review of Big-O notation.
Reading: CLRS Ch. 1, 3.
Experimenting with function growth rates. More on asymptotic function growth notations.
Problem set 1: Big-O notation. Due Fri., Sept 3.
Week 2: August 30 - September 3
Pseudocode notations, complexity of algorithms.
Correctness of an algorithm, loop invariants.
Reading: CLRS Ch. 2.
Approaches to complexity analysis of algorithms.
Reading: CLRS Ch. 4.
Algorithm development and analysis.
Reading: CLRS Ch. 4.
Problem set 1 due.
Problem set 2: algorithm analysis. Due Fri., Sept. 10.
Week 3: September 6 - 10
Labor day, no class. Recurrences (cont.), the master theorem.
Algorithm development and analysis.
Sorting algorithms.
Reading: CLRS Ch. 6, 7 (up to 7.2).
Problem set 2 due.
Problem set 3: recurrences. Due Fri., Sept. 17.
Week 4: September 13 - 17
Sorting algorithms (cont.). Randomized algorithms.
Reading: CLRS Ch. 5, 7.3, 7.4.
Non-comparison sorting algorithms.
Reading: CLRS Ch. 8.
Algorithm development and analysis. Non-comparison sorting algorithms (cont.).
Problem set 3 due.
Problem set 4: analysis of sorting algorithms. Due Fri., Sept. 24.
Week 5: September 20 - 24
Strings, graphs, sets, proofs.
Reading: Sipser Ch. 0 (especially sections on graphs, strings, sets, and proofs).
Finite automata.
Reading: Sipser Ch. 1.1
Algorithm development and analysis.
Practice with DFA using JFLAP.
Finite automata (cont.)
Problem set 4 due.
Problem set 5: background for computability theory; finite automata. Due Fri., Oct. 1.
Week 6: September 27 - October 1
Nondeterministic finite automata.
Reading: Sipser Ch. 1.2
Nondeterministic finite automata (cont).
Practice with NFA. Regular expressions.
Reading: Sipser Ch. 1.3.
Problem set 5 due.
Problem set 6: NFA, DFA/NFA conversion. Due Fri., Oct 8. .
Week 7: October 4 - 8
The pumping lemma.
Reading: Sipser 1.4.
The pumping lemma (cont.).
Regular expressions using JFLAP and in Java.
Q&A session for the midterm.
Problem set 6 due.
Problem set 7: regular expressions, the pumping lemma. Due Fri., Oct. 16.
Week 8: October 11 - 16
Midterm I (covers material up to Friday, Oct. 2). Context-free grammars.
Reading: Sipser 2.1
The pumping lemma and context-free grammars with JFLAP.
Context-free grammars (cont.).
Problem set 7 due.
Problem set 8: context-free grammars. Due Fri., Oct. 22.
Week 9: October 18 - 22
Fall break, no class Pushdown automata.
Reading: Sipser 2.2.
Pushdown automata with JFLAP. Pushdown automata (cont.).
Problem set 8 due.
Problem set 9: pushdown automata. Due Fri., Oct. 29.
Week 10: October 25 - 29
Turing machines.
Reading: Sipser 3.1.
More on Turing machines, Church-Turing thesis.
Reading: Sipser 3.2, 3.3.
Turing machines with JFLAP. Decidability.
Reading: Sipser 4.1.
Problem set 9 due.
Problem set 10: Turing machines. Due Fri., Nov 5.
Week 11: November 1 - 5
The halting problem.
Reading: Sipser 4.2.
Time complexity: class P problems vs class NP problems.
Reading: Sipser 7.1, 7.2, 7.3.
Extended algorithm development lab, day 1. Time complexity: examples of class NP problems; P vs. NP question.
Reading: Sipser 7.3.
Problem set 10 due.
Problem set 11: time complexity, decidability. Due Fri., Nov. 12.
Week 12: November 8 - 12
Reading: Sipser 7.4, parts of 7.5.
Overview of space complexity.
Reading: Sipser parts of 8 (details TBA).
Extended algorithm development lab, day 2. Applications to cryptography.
Reading: Sipser 10.6.
Problem set 11 due.
Problem set 12: NP-completeness, space complexity, applications. Due Wedn., Nov. 23.
Week 13: November 15 - 19
Dynamic programming.
Reading: CLRS Ch. 15.
Dynamic programming (cont.).
Q&A session for the midterm.
Midterm II. Covers material up to Fri. November 12th. Greedy algorithms.
Reading: CLRS Ch. 16.
Week 14: November 22 - 26
Greedy algorithms (cont.).
Graphs, graph algorithms.
Reading: Ch. 22, 23, 24.
Problem set 12 due.
Problem set 13: dynamic programming. Due Fri., Dec. 4
Thanksgiving holiday - no class Thanksgiving holiday - no class
Week 15: November 29 - December 3
Extended algorithm development lab, day 3. Graph algorithms (cont.).
Dynamic programming. Graph algorithms (cont.).
Problem set 13 due.
Problem set 14: greedy algorithms, graph algorithms. Due Fri., Dec. 10
Week 16: December 6 - 10
Graph algorithms (cont.).
A topic from CLRS.
A topic from CLRS. Last day of classes
Review and wrap up.
Problem set 14 due. Last day to submit any late work.
Final exam: Wedn., Dec. 15 2010 1:30-3:30pm in Sci 2185.

The views and opinions expressed in this page are strictly those of the page author. The contents of this page have not been reviewed or approved by the University of Minnesota.