3/21/2025 11:38:03 PM	CS 11 Course Outline as of Fall 2013	Changed Course
CATALOG INFORMATION
Discipline and Nbr:  CS 11	Title:  DATA STRUCT & ALGORITHMS
Full Title:  Data Structures and Algorithms
Last Reviewed:3/27/2023

Units		Course Hours per Week			Nbr of Weeks	Course Hours Total
Maximum	4.00	Lecture Scheduled	4.00		17.5 max.	Lecture Scheduled	70.00
Minimum	4.00	Lab Scheduled	0		6 min.	Lab Scheduled	0
		Contact DHR	0			Contact DHR	0
		Contact Total	4.00			Contact Total	70.00
		Non-contact DHR	0			Non-contact DHR Total	0

Total Out of Class Hours:  140.00

Total Student Learning Hours: 210.00

Title 5 Category:  AA Degree Applicable
Grading:  Grade or P/NP
Repeatability:  00 - Two Repeats if Grade was D, F, NC, or NP
Also Listed As: 
Formerly:  CIS 11

Catalog Description:

Continued study of computer programming including specification and implementation of data structures, and analysis of associated algorithms. Topics include: abstract data types, dynamic memory, templated functions and classes, iterators, exception handling, linked lists, stacks, queues, recursion, trees, searching, sorting, and inheritance. Several significant programming projects are written in C ++.

Prerequisites/Corequisites:
Course Completion of CS 10

Recommended Preparation:
Eligibility for ENGL 1A or equivalent

Limits on Enrollment:

Schedule of Classes Information
Description:

Continued study of computer programming including specification and implementation of data structures, and analysis of associated algorithms. Topics include: abstract data types, dynamic memory, templated functions and classes, iterators, exception handling, linked lists, stacks, queues, recursion, trees, searching, sorting, and inheritance. Several significant programming projects are written in C ++.

(Grade or P/NP)
Prerequisites:Course Completion of CS 10
Recommended:Eligibility for ENGL 1A or equivalent
Limits on Enrollment:
Transfer Credit:CSU;UC.
Repeatability:00 - Two Repeats if Grade was D, F, NC, or NP

ARTICULATION, MAJOR, and CERTIFICATION INFORMATION

Associate Degree:		Effective:		Inactive:
Area:
CSU GE:	Transfer Area			Effective:	Inactive:
IGETC:	Transfer Area			Effective:	Inactive:
CSU Transfer:	Transferable	Effective:	Spring 1991	Inactive:
UC Transfer:	Transferable	Effective:	Spring 1991	Inactive:
C-ID:
CID Descriptor: COMP 132	Programming Concepts and Methodology II	SRJC Equivalent Course(s): CS10C

Certificate/Major Applicable: Major Applicable Course

COURSE CONTENT

Outcomes and Objectives:
At the conclusion of this course, the student should be able to:

Upon completion of the course, students will be able to:

1.  Analyze algorithms for efficiency.

2.  Use data abstraction as a tool for modeling.

3.  Construct linked lists, pointers, queues, stacks, and trees as abstract data types.

4.  Design and construct iterative approaches to algorithm development.

5.  Evaluate a variety of sorting and searching methods for efficiency.

Topics and Scope

A. Abstract data types: operator overloading

   1.  Overloading arithmetic, shorthand arithmetic, and relational

       operators

   2.  Overloading the insertion and extraction operators

   3.  Overloading the pre and post decrement and increment operators

   4.  Overloading the square brackets (subscript) operator

   5.  Overloading operators as member functions, free (global)

       functions, and friend functions.

   6.  Default parameters

B. Pointers and Dynamic Memory

   1.  Address operator

   2.  Dereference (indirection) operator

   3.  Pointer assignment

   4.  Arrow (dereference and select) operator

   5.  Arrays of pointers

   6.  "NULL"

   7.  Relationship of arrays and pointers

   8.  "new" operator

   9.  "delete" operator

   10. Memory leaks

   11. Reference types

C. Dynamic memory in classes

   1.  Assignment operator, including checking for self-assignment

   2.  Copy constructor

   3.  Destructor

   4. Object lifetime management

D. Container Classes

   1.  Documenting member functions with pre/post conditions

   2.  Using std::size_t

   3.  Returning a reference

   4.  User defined namespaces

E. Linked lists

F. Templated functions and classes

G. Iterators, including user-defined

H. Standard Template Library

I. Exception handling

J. Stacks, including expression evaluation

K. Queues

L. Recursion

   1.Development techniques

   2.Analysis techniques

M. Trees:  specification, implementation, and big-O analyses of

   1.Binary search trees

   2.Heaps

N. Searching Algorithms:  specification, implementation, and big-O analysis of

   1.Sequential search

   2.Binary search

   3.Hashing

O. Sorting Algorithms:  specification, implementation, and big-O analysis of

   1.  Selection sort

   2.  Insertion sort

   3.  Bubble sort

   4.  Merge sort

   5.  Quicksort

   6.  Heapsort

P. Inheritance

   1.  Contrasted with composition

   2.  "is-a" relationship and "has-a" relationship

   3.  Protected

   4.  Constructors in inheritance

   5.  Initializor lists

   6.  Polymorphism and virtual functions

   7.  The slicing problem

   8.  Pure virtual functions and abstract classes

Q. String Processing

Assignments:

1.  Read approximately 40 pages per week from text book.

2.  Write computer programs.

3.  Correct errors in programs with multiple runs of test data.

4.  Write documentation for each program so that is easy to understand and use.

5.  2-3 exams, including final exam.

Methods of Evaluation/Basis of Grade.

Writing: Assessment tools that demonstrate writing skill and/or require students to select, organize and explain ideas in writing.		Writing 10 - 20%
Written program documentation
Problem solving: Assessment tools, other than exams, that demonstrate competence in computational or non-computational problem solving skills.		Problem Solving 20 - 60%
Computer programming assignments
Skill Demonstrations: All skill-based and physical demonstrations used for assessment purposes including skill performance exams.		Skill Demonstrations 0 - 0%
None
Exams: All forms of formal testing, other than skill performance exams.		Exams 20 - 60%
2-3 exams, including final exam.
Other: Includes any assessment tools that do not logically fit into the above categories.		Other Category 0 - 0%
None

Representative Textbooks and Materials:

Data Structures and other Objects Using C++, by Michael Main and Walter Savitch,  Addison Wesley Longman, 5th edition, 2013.

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