CSI 4v96: Competitive Learning, Spring 2015
This course is a topics course in problem solving and algorithms. It is modeled on the collaborative and competitive environments at the ACM International Collegiate Programming Contest. Each week we will discuss a topic, and the assignments will be programming-based problems related to that topic.
Lectures are from 2:30 to 3:20 PM in Rogers 113 on Tuesdays.
My office is in the Rogers Engineering and Computer Science building, and office hours are listed on my home page. I am glad to talk to students during and outside of office hours. If you can't come to my office hour, please make an appointment for another time, or just stop by.
Here is a schedule of the material we will cover. As the semester progresses, the relevant problems will be listed under each topic.
- Introduction to Problem Solving.
- Elementary Data Structures — The C++ Standard Template Library or Java Collections, including sequence containers, iterators and basic template algorithms.
- Sorted associative set and map data structures and their implementations in C++ STL or Java Collections.
- Strings and string algorithms, searching, sorting.
- First Local Contest.
- Sorting and applications to uniqueness testing, deleting duplicates, selection, efficient searching, and set intersection/union.
- Arithmetic and algebra, big number implementation, prime factorization.
- Arithmetic and algebra, number theory, counting problems, modular arithmetic.
- Elementary Search Topics, recursive depth-first search, combination and permutation generation, state space traversal.
- Second Local Contest. Also, problem writeups are due.
- Intermediate Search Topics, search pruning and ordering.
- Simulation problems.
- Disjoint set data structure, path compression algorithm, and applications. No meeting due to Diadeloso.
- Representing, counting, and computing on grid-oriented data; rectangular, hexagonal, and triangular grids.
- Final Local Contest.
Textbooks & resources
There is no required text for this course. However, the following books may be useful:
- Competitive Programming by Steven Halim and Felix Halim
- Programming Challenges by Steven Skiena
- The Algorithm Design Manual by Steven Skiena
- Introduction to Algorithms by Cormen et al.
- Programming Pearls by Jon Bentley
- Any other data structures, algorithms, and language reference books.
Other online programming contest software:
- Open Kattis -- this is the software used to judge the ACM ICPC contest world finals
Other online resources:
- Bruce Eckel, Thinking in C++ (2nd edition)
- the Standard Template Library (STL) reference
- Project submission guidelines and coding style guidelines for this course.
Grades will be assigned based on the following breakdown:
- First semester students:
- # of problems completed: 100%
- Second and third semester students:
- # of problems completed: 80%
- problem(s) developed: 20%
Final letter grades will be assigned at the discretion of the instructor, but
here is a minimum guideline for letter grades:
A: 90-100, B+: 88-89, B: 80-87, C+: 78-79, C: 70-77, D: 60-69, F: 0-59
Each problem completed within 1 week of it being assigned earns 2 points. Each problem not completed within a week but completed by the end of the semester earns 1 point. Completing a program means passing the (hidden) tests on the judge.
For weeks designated as "contests", the problems will not be publicly posted to the web. You should choose a 3 hour window during which you plan to work on the problems. Send your professor an email about 24 hours in advance of this time, and he will send you the problems via email. Then work on the problems during your chosen time frame.
Students taking the course for the second (third) semester must develop one (two) problems of their own. Use the Kattis problem package and fill in the relevant parts. In particular, your writeup should have:
- A Latex writeup.
- At least one correct, efficient, well-structured, well-commented, one-file solution in C++ or Java.
- Possibly other submissions that highlight incorrect solutions (wrong answer, too much time, etc.)
- Files containing sample and secret inputs (each having suffix ".in"). The size of all inputs combined should be less than 500 Kb.
- Files containing sample and secret outputs (each having suffix ".ans"). The size of all inputs combined should be less than 500 Kb.
- An input format validator. It should use exit code 42 when the input file is correctly formatted, another exit code when there is a problem.
- A test case generator which generates input file (may be written in C++, Java, Perl, or Python). This should probably have some hand-made test cases hard coded in, as well as some randomly created test cases.
- An appropriately filled-in problem.yaml file.
The reason we use Kattis problem package format is due to the set of tools that are available for verifying problem integrity. You should get and install them from github on the Kattis problemtools project page. (They are easiest to install on Ubuntu.) As the problemtools package uses a Git submodule, to get the full source you need to use the following command to get all the sources you'll need:
git clone --recursive email@example.com:Kattis/problemtools.gitAfter installing it, use this software to verify your problem package before submitting it to me. This means running "verifyproblem.py" to verify the entire problem package. You can also use "problem2pdf.py" to see how your problem writeup looks when rendered in PDF.
These problems are due at the last class meeting of the semester. You must also submit via email to the professor your ideas for your problem(s) the 3rd class meeting, and a draft of the completed writeup of the entire problem on the 10th meeting. A completed writeup is a complete package (solution(s), test data, input validator, problem writeup, problem.yaml metadata file, etc.). The package should validate using "verifyproblem" (see Kattis problemtools above).
- This website contains the official course information. Please check it regularly for updates.
- All work in this course is strictly individual, unless the instructor explicitly states otherwise. While discussion of course material is encouraged, collaboration on assignments is not allowed. Collaboration includes (but is not limited to) discussing with anyone (other than the professor) anything that is specific to completing an assignment. You are encouraged to discuss the course material with the professor, preferably in office hours, and also by email.
- Bring any grading correction requests to your professor's attention within 2 weeks of receiving the grade or before the end of the semester, whichever comes first.
I take academic honesty very seriously. Many studies, including one by Sheilah Maramark and Mindi Barth Maline have suggested that "some students cheat because of ignorance, uncertainty, or confusion regarding what behaviors constitute dishonesty" (Maramark and Maline, Issues in Education: Academic Dishonesty Among College Students, U.S. Department of Education, Office of Research, August 1993, page 5). In an effort to reduce misunderstandings, here is a minimal list of activities that will be considered cheating in this class:
- Using a source other than the optional course textbooks, the course website, or your professor to obtain credit for any assignment.
- Copying another student's work. Simply looking over someone else's source code is copying.
- Providing your work for another student to copy.
- Collaboration on any assignment, unless the work is explicitly given as collaborative work. Any discussion of an assignment or project is considered collaboration.
- Studying tests or using assignments from previous semesters.
- Providing someone with tests or assignments from previous semesters.
- Turning in someone else's work as your own work.
- Giving test questions to students in another class.
- Reviewing previous copies of the instructor's tests without permission from the instructor.