CS 142/IT 501 Introduction to Computer Science II
Spring 2003

Official Course Description. This course will further develop and expand upon the topics introduced in CS 141. Advanced programming techniques will be covered, with extensive use of recursion and dynamic data structures. Abstract data types, including lists, queues, trees and graphs, will be studied. Specific emphasis will be given to tree traversals and binary search trees. Algorithms for searching and sorting will be explored along with methods of comparative analysis. The topics in this course provide an essential foundation for the further study of computer science.

Prerequisites. CS141 or equivalent.

Location and Times. Science Center 162, TuTh 2:30-4:00.

Instructor. Alexis Maciel
Office: Science Center 379
Phone: 268-2385
E-mail: alexis@clarkson.edu.

Office Hours. M 2:30-4:00, Tu 10:00-11:00, W 10:00-11:30, Th 4:00-5:00.

Teaching Assistant. Vineet Raghavan. Science Center 450, 268-2339, raghavvs@clarkson.edu. Office Hours: M 10-12 (in the SC334 lab), W 1:30-3:30 (lab), F 3-4 (office).

Required Text.

Course Objectives.

  1. To learn fundamental programming concepts including data abstraction, basic data structures, dynamic data structures, basic notions of object-oriented programming, analysis of algorithms and recursion.

  2. To further develop coding and debugging skills.

  3. IT 501 students will have more indepth programs to do.
Demonstrable outcomes. By the end of the semester,
  1. You will have a good understanding of the concepts mentioned in Objective 1 above.

  2. You will be able to design and implement C++ programs of a moderate size using data abstraction, basic data structures, dynamic data structures, basic notions of object-oriented programming and recursion.

  3. You will be able to implement basic data structures including lists, stacks and queues.

  4. You will understand the importance of using standard software components and will be familiar with the basic data structures and algorithms provided in the C++ Standard Template Library.

  5. You will be able to analyze the running time of simple algorithms.

  6. You will be able to implement and analyze basic algorithms for searching, sorting and, if time permits, tree traversal.

Topics to be covered. Data abstraction, classes, object-oriented design, lists, vectors, stacks, queues, linked structures, iterators, templates, the STL, inheritance, polymorphism, analysis of algorithms, recursion, sound programming principles and, if time permits, trees and binary search trees.

Grading. You will be evaluated based on several homework assignments (which will be mostly programming assignments), two quizzes, two tests and a final exam. Your course grade will be computed using the following formula:

15% A + 10% Q + 20% T1 + 20% T2 + 35% F

If you do better on the final exam than on one of your tests, your lowest test grade will be replaced by your final exam grade. Essentially, this allows you to make up for one bad test. In addition, your average grade on the tests and final exam will replace any lower grade on a quiz. This allows you to make up for bad or missed quizzes.

Tentative dates for the quizzes and tests are: January 28 (Q1), February 18 (T1), March 11 (Q2), April 8 (T2). All students are required to write the final exam (no exemptions).

Policy for missed work. There will be no make-up assignments or quizzes. Late assignments may be accepted if a good excuse is provided and if arrangements are made at a reasonable time, in advance, if possible. Make-up tests can be arranged under the same conditions. Other special arrangements can be made for students forced to miss more than a few days of class.