ALGORITHMS AND COMPLEXITY
CS 3AC3 (Winter 2018)
* * * This outline is constantly
updated. Students should consult this page regularly for all
information relevant to this course * * *
Dr. George Karakostas
ITB/218, ext 26132, Mac address: karakos
Office hours: by email appointment
Enamul Haque (email@example.com),
Office hour: Mon. 4-5 pm, Rm. ITB/223
(firstname.lastname@example.org), Office hours: Thu. 2-3 pm, Rm.
Term II, 2017/18
Tu We Fr 12:30 - 1:20 PM, Rm T13 127
Session 1: Mo 1:30 - 2:20
PM, Rm BSB 119
CS 2C03, CS 2FA3
In this course, we will study the solution of computational problems from two complementary perspectives: (i) The Algorithm Design & Analysis perspective, i.e., the design methods one can employ in order to build efficient algorithms for fundamental problems (e.g., network flows), and the analysis of their running times. We will study the design of Divide-and-Conquer, Greedy and Dynamic Programming algorithms, approximations algorithms that are efficient but can only provide approximation-of-the-optimal guarantees, and the use of randomization in our algorithms. (ii) The Computational Complexity perspective, i.e., the study of the inherent difficulty of solving a problem computationally. As opposed to the 'easyness' of solving a problem, demonstrated by efficient algorithms designed in (i), in this part we will study how one can show that a problem is at least as 'hard' to solve as another problem, using reductions, and will classify our problems into complexity classes such as P, NP, PSPACE, according to their 'hardness'.
More specifically, students should know and understand:
Students should be able to
Learning objectives, indicators, and rubrics
Outline of Topics (roughly per week)
Student Assessment (Grading)
Policy on collaboration for homework assignments: Collaboration on the homework assignments is highly encouraged, within reasonable limits. Students are expected to discuss assignment problems with each other, and to cooperate on solutions in groups of no more than 5 people. However, the final write-up should be done by individual students (i.e. individual students should be able to explain their solutions by themselves, if such an explanation is asked for by the instructor) and the names of the collaborators should appear on the paper. Cooperation and teamwork are necessary for the success of any complex task (the design of algorithms being one such task), and it is the instructor's hope that students will come to appreciate them in a constructive way. Please see the instructor if you need someone to collaborate with.
Policy on delayed assignments: Assignments delivered between the lecture they were due and the following lecture get 50% of total credit. After the following lecture, no credit given.
Policy on collaboration during
exams: ABSOLUTELY NO
COLLABORATION DURING EXAMS!!!
Required textbook: "Algorithm
Design", by J. Kleinberg and E. Tardos, Addison-Wesley
Recommended textbook: "Introduction to Algorithms", 3rd Ed., by T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein, MIT Press
Recommended textbook: "Introduction to the Theory od Computation", 3rd Ed., by M. Sipser, Cengage Learning
"Academic dishonesty consists of
misrepresentation by deception or by other
fraudulent means and can result in serious consequences, e.g. the grade of
zero on an assignment, loss of credit with a notation on the transcript
(notation reads: "Grade of F assigned for academic dishonesty"), and/or
suspension or expulsion from the university.
It is your responsibility to understand what constitutes academic
dishonesty. For information on the various kinds of academic dishonesty
please refer to the Academic Integrity Policy, specifically Appendix 3,
located at http://www.mcmaster.ca/senate/academic/ac_integrity.htm
The following illustrates only three forms of academic dishonesty:
1. Plagiarism, e.g. the submission of work that is not one's own or for which other credit has been obtained. (e.g. submitting a copy of someone else's writeup for an assignment)
2. Improper collaboration in group work. (e.g. collaboration between groups in an assignment)
3. Copying or using unauthorized aids in tests and examinations."
"The Faculty of Engineering is
concerned with ensuring an environment that is free of all
discrimination. If there is a problem, individuals are
reminded that they should contact the Department Chair, the
Sexual Harrassment Officer or the Human Rights Consultant, as
the problem occurs."
"The instructor and university
reserve the right to modify elements of the course during the
term. The university may change the dates and deadlines for
any or all courses in extreme circumstances. If either type of
modification becomes necessary, reasonable notice and
communication with the students will be given with explanation
and the opportunity to comment on changes. It is the
responsibility of the student to check their McMaster email
and course websites weekly during the term and to note any
All assignments are to be submitted
to the instructor at the beginning of the lecture.
Assignment 1 (Due Part I: Tue 16/1,
Part II: 23/1): The questions are
here. The solutions
Assignment 2 (Due Part I: Tue 30/1, Part II: Fri 9/2): The questions are here. The solutions are here.
Assignment 3 (Due Part I: Wed 14/1, Part II: Tue 6/3): The questions are here. The solutions are here.
Assignment 4 (Due Part I: Tue 13/3, Part II: Fri 23/3): The questions are here.
Assignment 5 (Due ?): The questions are here.
To read the assignment files, you'll
need the Adobe Reader, which is here.
The lecture slides used in the
lectures are designed by the textbook authors, and are
distributed by Pearson Addison-Wesley.