CSCI 2720: Data Structures

Spring 2025 • Face-to-Face Course


Course Description & Overview

This course focuses on the design, analysis, and implementation of data structures and their associated algorithms. Major topics include:

Expected Learning Outcomes

  1. Analyze algorithms using asymptotic notations (Big O, Ω, Θ).
  2. Design, analyze, and implement recursive solutions.
  3. Design, analyze, and implement generic, reusable Abstract Data Types (ADTs).
  4. Apply algorithm design methods to solve a variety of complex programming problems.
  5. Implement and analyze algorithms for sorting, searching, hashing, and graph-based solutions.
  6. Choose and defend the selection of appropriate data structures for real-world problems.

ABET Learning Outcomes

  1. Analyze a complex computing problem and apply principles of computing and other relevant disciplines to identify solutions.
  2. Design, implement, and evaluate a computing-based solution to meet a given set of requirements.
  3. Communicate effectively in a variety of professional contexts.
  4. Apply computer science theory and software development fundamentals to produce computing-based solutions.

Logistics

Section Days Time Location
Section A Tu/Th 3:55–5:10 PM Biological Sciences Bldg (0404D)
Section A W 4:10–5:00 PM Biological Sciences Bldg (0404A)
Section B Tu/Th 5:30–6:45 PM Poultry Science (0014)
Section B W 5:20–6:10 PM Poultry Science (0014)

Instructor & TA Information

Piazza

Prerequisites

Course Materials & Textbooks

Technologies: Java 17 (LTS), Maven, IntelliJ, JUnit 5, access to Odin server, Survey Monkey as needed.

Note: You must bring your own laptop (with necessary software) for in-class coding exercises.

Grading Policy

Category Weight
Assignments (coding, analysis, video demo; 2 lowest dropped for excused absences) 60%
Quizzes (in-class, 2 lowest dropped for excused absences) 5%
Exam 1 (before withdrawal deadline) 10%
Exam 2 (after withdrawal deadline) 10%
Final Exam 15%

Note: For the weekly schedule and topics, see the Schedule. Exact due dates for assignments will be posted on eLC.

Grading Philosophy

The general grading philosophy applies to programs, projects, written work, and other required elements. We use the College Board’s convention for converting percentages to letter grades.

Late Policy

Assignments are due on the date/time specified. Start early!

Expected Class Workload

Assignment Quality

Each assignment must meet the following criteria:

  1. Code Quality: Clean, well-structured, following established coding standards.
  2. Comments: Clear, concise, and explanatory without compromising readability.
  3. File Relevance: Submit only necessary files; no extraneous content.
  4. Test Cases: Include boundary tests and error checking.

Team Work

All assignments are individual unless explicitly specified otherwise.

Grade Appeals

Any request for a grade adjustment or appeal (including exams) must be made within 7 days of the grade being posted. Use a private Piazza post or speak with the instructor. Regrades can take time.

Decorum

Students must maintain a high standard of courtesy and respect in all class-related interactions, both in-person and online (including social media). Disruptive or disrespectful behavior may result in removal from class and/or further administrative action.

Other Class Policies

Academic Honesty

UGA Student Honor Code:
"I will be academically honest in all of my academic work and will not tolerate academic dishonesty of others."
A Culture of Honesty, the University's policy and procedures for handling cases of suspected dishonesty, can be found at honesty.uga.edu. Every course syllabus should include the instructor's expectations related to academic honesty.

All work must comply with UGA’s academic honesty policy.

In addition to UGA's policy, you agree not to make any portion of your assignments public (e.g., GitHub, Discord, etc.) or share solutions with others. Posting code or providing line-by-line assistance (including AI or external websites) is considered unauthorized assistance unless explicitly allowed.

UGA Well-Being Resources

UGA Well-being Resources promote student success by cultivating a culture that supports a more active, healthy, and engaged student community.

Anyone needing assistance is encouraged to contact Student Care & Outreach (SCO) at 706-542-8479 or visit sco.uga.edu. They help navigate difficult circumstances by connecting students with resources or services. They also administer the Embark@UGA program, which supports students experiencing or having experienced homelessness, foster care, or housing insecurity.

UGA provides both clinical and non-clinical options to support student well-being and mental health, any time, any place. Whether on campus or learning remotely, UGA Well-being Resources are here to help.

Additional info, including free digital resources, can be accessed through the UGA app or at https://well-being.uga.edu.

Syllabus Disclaimer

The course syllabus is a general plan for the course; deviations announced to the class by the instructor may be necessary.