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CSCI 2100: Data Structures
Fall 2017

Tae-Hyuk (Ted) Ahn
Contact Info: ted.ahn - at -
Office: 305 Ritter Hall
Office Hours: Monday 10:30-12:30pm, Tuesday 2:30-3:30pm, or by appointment (email me)

The table below lists the programming assignments and associated dates.

Lab Topic Class Date Due Collaboration Policy Possible Solution
Lab 1 Compiling and running a C++ program Aug. 29 Aug. 30 by 11:59pm Individual
Lab 2 Copier Reduction Sep. 6 Sep. 7 by 11:59pm Pair copier.cpp
Lab 3 Speed Limit Sep. 12 Sep. 13 by 11:59pm Pair speed.cpp
Lab 4 Doubles Sep. 19 Sep. 20 by 11:59pm Pair doubles_v1.cpp, doubles_v2.cpp
Lab 5 Tanning Salon Oct. 10 Oct. 12 by 11:59pm Pair salon.cpp
Lab 6 Symmetric Order Oct. 18 Oct. 19 by 11:59pm Pair order.cpp
Lab 7 Overflowing Bookshelf Oct. 31 Nov. 1 by 11:59pm Pair bookshelf.cpp
Lab 8 Anagrams by Stack Nov. 8 Nov. 9 by 11:59pm Pair anagrams.cpp
Lab 9 Tree Grafting 1 Nov. 14 Nov. 15 by 11:59pm Pair graft1.cpp
Lab 10 List Priority Queue Nov. 28 Nov. 29 by 11:59pm Pair ListPriorityQueue.h, ListPriorityQueue.cpp, testListPriorityQueue.cpp
Lab 11 Tree Grafting 2 Dec. 5 Dec. 6 by 11:59pm Pair

Information About Lab Assignments

ACM's International Collegiate Programming Contest

This year, each of our lab assignments will be a problem taken from a past offering of the ACM International Collegiate Programming Contest (ICPC). Students work in teams of three to solve as many problems as possible in a five-hour time period.

Hundreds of regional contests are held each Fall, involving thousands of teams across the world. The top 100 teams from the regionals qualify for the World Finals held in the Spring. More information can be found on the official ICPC site. Also, if you have any interest in participating on SLU's teams, please let me know next Fall.

General Problem Format

Each problem is computational in nature, with the goal being to compute a specific output based on some input parameters. Each problem defines a clear and unambigous form for the expected input and desired output. Relevant bounds on the size of the input are clearly specified. To be successful, the program must complete within 60 seconds on the given machine (thus, efficiency can be important for certain problems).

Each problem description offers a handful of sample inputs and the expected output for those trials as a demonstration. Behind the scene, the judges often have hundreds of additional tests. Submitted programs are "graded" by literally running them on all of the judges' tests, capturing the output, and comparing whether the output is identical (character-for-character) to the expected output.

If the test is successful, the team gets credit for completing the problem. If the test fails, the team is informed of the failure and allowed to resubmit (with a slight penalty applied). However, the team receives very little feedback from the judges. In essence, they are told that it failed but given no explanation as to the cause of the problem, or even the data set that leads to the problem.

Actually, the feedback is slightly more informative. Upon submitting a program, the team formally receives one of the following responses:

Important Conventions

Because of the automated nature of the judging, it is important that programs follow these conventions:

Please note as well that the format of most problems is designed so that judges can specify multiple tests as part of a single execution. Typically this is done by having an input format where initial parameters are read, using a special value (such as 0 or #) to designate the end of the trials. Therefore, most programs will need to iterate through multiple trials using an outer loop. It is also important that relevant data structures be initialized for each trial, so that earlier trials do not affect later ones.

Testing Your Implementation

Formal Submission

Although the online tools give you a way to test your implementation, you must submit to the instructor via email in order to get credit for the lab. Please keep in mind that we will award half-credit for any sincere attempt at a lab, even if you are unable to succeed with the automated testing. However, you will get zero credit if you do not ever submit your attempt.

Also, make sure to include the names of all team members in comments at the top of the submit source code.