The text is Lewis and Chase, Java Software Structures, 3rd ed., Addison Wesley, 2010.
The prerequisite for this course is C or better in CS 211. I will assume that you have developed a significant degree of skill in programming (program organization, coding, documenting, testing and debugging) -- you will develop yet more this semester. I will also assume that you are able to build abstract data types using Java classes.
The purpose of the course is two-fold. We will continue the study of data structures from CS 211 and we will learn how to approach larger and more challenging programming projects than those you did in CS 211. Programming is a significant part of this course and you should expect to spend a good deal of time on the course projects.
Topics to be covered include:
The students will:
There will be several programming assignments. Programming assignments will be posted on the course website.
You may discuss the programming projects with other students (this is encouraged) but you must do and submit your own work. No joint work will be accepted. Read the CS Department honor code: http://cs.gmu.edu/wiki/pmwiki.php/HonorCode/CSHonorCodePolicies and the University honor code: http://honorcode.gmu.edu. You are bound by these honor codes. Any submitted work which shows too much commonality with others' work to be completely original, or any plagiarized work, will receive a grade of 0. Any code which is presented in class or provided to you as part of the project may be included in your programs.
You can only turn in a program once. No revisions or additions can be made to your program after it has been submitted. Late programs will be accepted with a 10 points per day late penalty. You are responsible for keeping backups of your work ("my disk crashed" and "my roommate ate my program" are not reasons for late submissions).
There will be a midterm exam and a final. There will be no makeups on exams except under exceptional circumstances (as judged by me), and any such makeup must be arranged in advanced. Grades will computed from a weighted average computed with the following weights: