Faculty Syllabus

Grade Policy:

Grade will be assigned based both on concepts and practical application. Exams, quizzes, and lab projects will be a part of the grade. An overall grade will be assigned on the following grading scale:
90% - 100% A

80% - 89% B 70% - 79% C 60% - 69% D 0%-59% F

Each student’s grade for this course consists of chapter quizzes, exams, and program assignments. The grade breakdown is as follows:

All assignments have a due date shown in Blackboard. Assignments must be submitted via Blackboard.

3 Exams

20 Chapter Quizzes (15 chapters, 5 interludes)    

5 Programming Assignments / Labs

Lab assignments are to be completed outside of class time either in a CIS open lab or using a personal computer with the appropriate tools installed. Labs are due according to the date specified with the assignment in Blackboard. Late lab assignments are not accepted.

Missed EXAMS must be made up no later than the next scheduled class period. Exams can be missed only for extreme circumstances (Example: hospitalization). Please contact the instructor IN ADVANCE if you will miss one of the exams. There are NO makeup exams for un-excused absences. Only one exam may be taken as a makeup exam.

Data Abstraction & Problem Solving with C++ By CARRANO
REQUIRED
• EDITION: 7TH, 2017

• PUBLISHER: PEARSON • ISBN: 9780134463971

This course is designed to teach students the fundamental data structures and the algorithms used to manipulate them. The data structures and algorithms will be implemented in a modern object- oriented programming language (C++). Since this course is designed to transfer into a bachelor degree program, check with the college to which you plan to transfer to be sure that they will accept this course.

Course Objectives / Learning Outcomes:

1. Demonstrateathoroughunderstandingofthebehaviorofbasicdatastructures:lists,stacks, queues and trees by developing programs that implement or apply these data structures.

2. Demonstrate a thorough understanding of how data structures impact the performance of algorithms.

3. Demonstrate a thorough understanding of the object-oriented concepts of data abstraction and encapsulation by designing and implementing data structures using classes.

4. Demonstrate a thorough understanding of template classes by developing programs that use them.

5. Demonstrate an understanding of recursion by applying recursive techniques to solve problems including list and tree processing.

6. Demonstrate a thorough understanding of searching and sorting algorithms including recursive techniques.

7. Demonstrate proficiency in implementing data validation code and performing unit and integration testing by developing robust solutions to the assignments in this course.
8. Demonstrate good documentation style in all of the programs written in this course.

SCANS (Secretary’s Commission on Achieving Necessary Skills):

Refer to http://www.austincc.edu/cit/courses/scans.pdf for a complete definition and explanation of SCANS. The following list summarizes the SCANS competencies addressed in this course: