Nov 27, 2021
CIS 228 - Algorithms and Data Structures
This course introduces the basics of algorithms and data structures, including sorting, runtime complexity, lists, stacks, queues, hash tables, trees, and graphs. Students develop in-depth understanding of data structures, their representations, and role as the foundation in the development of computer algorithms.
Credit Hours: 3
Contact Hours: 3
School: School of Workforce Development
Department: Computer Information Systems
Last Revision Date Effective:
Course Review & Revision Year: 2025-2026
Program Requirement- Offering designed to meet the learning needs of students in a specific GRCC program.
Lecture - 1:1
General Education Requirement: None
General Education Outcomes:
ILO Competencies (Communication Skills):
ILO Competencies (Critical Thinking Skills):
Create and/or organize data and information into meaningful patterns in order to interpret and draw inferences from it. (CT3), Use creativity and alternative thinking to brainstorm new ideas and possible solutions to problems or issues. (CT8)
ILO Competencies (Social Responsibility Skills):
ILO Competencies (Personal Responsibility Skills):
Course Learning Outcomes/ILO Competencies:
- Explain the relationship between data structures and algorithms.
- Illustrate abstract data types and describe their most common pre-defined operations.
- Classify algorithms based on efficiency, computational complexity, and worst-case runtime.
- Use Big-O Notation to perform algorithm analysis and derive worst-case runtime approximations.
- Compare and contrast various sorting algorithms, such as Selection Sort, Insertion Sort, Shell Sort, Quicksort, and Merge sort.
- Develop implementations of Abstract Data Types using Java, such as Lists, Stacks, Queues, and Hash Tables.
- Design Binary Search Trees in Java that contain algorithms for searching, inserting, removing, and inorder transversal.
- Create graphs using vertices and edges to represent paths between nodes that describe algorithm implementations, such as breadth-first search, or depth-first search.
- Create and/or organize data and information into meaningful patterns in order to interpret and draw inferences from it. (CT3)
- Use creativity and alternative thinking to brainstorm new ideas and possible solutions to problems or issues. (CT8)
I. Introduction to Data Structures and Algorithms
II. Abstract Data Types
III. Algorithm Analysis and Big-O Notation
IV. Searching Algorithms
V. Sorting Algorithms
IX. Hash Tables
XI. Introduction to Graphs
XII. Advanced Topics in Graphs
Mandatory CLO Competency Assessment Measures:
Name of Industry Recognize Credentials: None
Facilitated discussion: 0-20%
Group work: 0-10%
Applied work: 10-40%
Mandatory Course Components:
Academic Program Prerequisite: None
Prerequisites/Other Requirements: CIS 123 (C or Higher) and CIS 117 (C or Higher)
English Prerequisite(s): None
Math Prerequisite(s): None
Course Corerequisite(s): None
Course-Specific Placement Test: None
Consent to Enroll in Course: No Department Consent Required
Total Lecture Hours Per Week: 3
Is this course offered in Modules?:
Faculty Credential Requirements:
Master’s Degree (GRCC general requirement), 18 graduate credit hours in discipline being taught (HLC Requirement), Other (list below)
Faculty Credential Requirement Details: The instructor must possess a Master's Degree in Computer Science; at least five years of programming experience that includes object-oriented programing; and the ability to clearly explain the topics covered in the course.
General Room Request:
Maximum Course Enrollment:
Equivalent Courses: None
Dual Enrollment Allowed?: Yes
Number of Times Course can be taken for credit: 1
First Term Valid: Fall 2021 (8/1/2021)
1st Catalog Year: 2021-2022
People Soft Course ID Number: 105057
Non-Credit GRCC Agreement exist?:
If yes, with which Departments?:
Corporate Articulation Agreement exist?:
If yes, with which Companies?:
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