CS 142 Introduction to Computer Science II
Spring 2005

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 354, TuTh 11:00-12:15.

Instructor. Chris Lynch. Science Center 377, 268-2384, clynch@clarkson.edu.

Office Hours. TTh 2:30-5:00 but they will probably change

Teaching Assistant. Todd Deshane. Office Hours: TBA, in the ITL lab (SC334).

Required Text. Online book. Table of Contents, Chapter 1, Chapter 2, Chapter 3, Chapter 4, Appendix, Bibliography.

Course Objectives.

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

  2. To further develop coding and debugging skills.
Demonstrable outcomes. By the end of the semester,
  1. You will have a good understanding of the principles and techniques mentioned in Objective 1 above.

  2. You will be able to use them in the design and implementation of C++ programs of a moderate size.

  3. You will be able to implement elementary 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 lists, iterators, templates, the STL, analysis of algorithms, recursion, sound programming principles. If time permits, inheritance, polymorphism, trees and binary search trees.

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

25% A + 20% T1 + 25% T2 + 30% F

I will soon give dates for the two exams.

Policy for missed work. There will be no make-up assignments. 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.