CSC-200 CS3: Data Structures

CS3: Data Structures covers the fundamentals of data structures, introduction to analysis of algorithms, and team development of software applications. This course is the third in a series of three required programming courses for a traditional computer science degree. Data structures covered include sets, lists, stacks, queues, linked lists, binary trees, and heaps. Advanced topics include, binary search trees, search and sort algorithms, recursion, and algorithm efficiencies in software development. Students will be introduced to project management and team dynamics through the development of a large software solution.

Credits

4

Prerequisite

CSC-190

Department

• Computer Science

Semesters Course Will Be Offered

• Fall
• Spring

For more detailed course information view the Course Outline

CSC 200: CS3: Data Structures

Department

Computer Science

Course Description

CS3: Data Structures covers the fundamentals of data structures, introduction to analysis of algorithms, and team development of software applications. This course is the third in a series of three required programming courses for a traditional computer science degree. Data structures covered include sets, lists, stacks, queues, linked lists, binary trees, and heaps. Advanced topics include, binary search trees, search and sort algorithms, recursion, and algorithm efficiencies in software development. Students will be introduced to project management and team dynamics through the development of a large software solution.

Credit Hours

4

Contact Hours

Lecture	4
Lab	1
Other	0

Grading Scheme

Letter

Semester(s) Course Will Be Offered

Fall, Spring

Prerequisites

CSC-190

Capstone Course

Yes

Course Learning Outcomes

1. Identify and implement advanced data structures for the manipulation of data
2. Integrate multiple algorithms to form a complex computer solution
3. Analyze and evaluate the efficiencies of available data structures in order to select the appropriate solution for a given algorithm
4. Plan, prioritize, and build a complex computer solution within a collaborative work environment

Topic Outline

1. The Recursive method and the benefits of using recursion
2. Benefits of generics
3. Explore the relationship between interfaces and classes in the Java Collections Framework hierarchy
4. Store unordered, nonduplicate elements using a set
5. Compare the performance of sets and lists
6. Estimate algorithm efficiency using Big O notation
7. Explain growth rates and why constants and non dominating terms can be ignored in an estimation
8. Determine the complexity of various types of algorithms
9. Describe common growth functions
10. Study and analyze time complexity of various sorting algorithms
11. Design and implement a linked list using a linked structure
12. Design and implement a stack class using an array list and a queue class using a linked list
13. Design and implement a priority queue using a heap
14. Design and implement a binary search tree
15. Analyze the complexity of search, insertion, and deletion operations in AVL trees
16. Understand what hashing is and what hashing is used for
17. Model real-world problems using graphs
18. Describe the graph terminologies:
    1. Vertices
    2. Edges
    3. Simple graphs
    4. Weighted/unweighted graphs
    5. Directed/undirected graphs
19. Multithreading overview
20. Create threads to run tasks using the Thread class
21. Explain terms:
    1. TCP
    2. IP
    3. domain name
    4. domain name server
    5. steam-based communications
    6. packet-based communications
22. Develop an example of a client/server application
23. Work in a team to develop a software application
24. Understand professional responsibilities and liabilities associated with software development
    August