Overview

This course will focus on building applications for Android. Android serves as a useful case study for the broader concerns involved in the design and implementation of modern applications. The concepts we cover in the course are broadly applicable to iOS, web applications, and other types of user-facing software systems.

The high-level goals and ideas we will cover include:

• Managing state

• Event-driven programming and inversion of control

• Persistence and data management

• Asynchrony and concurrency

• UI representation and design

• Reusability, modularity, and testability

• Design patterns

• Testing strategies for mobile applications

• Client–server architectures and backend development

• Cloud service integration

• Interoperability and mixing programming languages in Android development

• Integrating AI and machine learning capabilities into mobile applications

Throughout the course, we will often begin by solving problems using a naive or “obvious” approach, then iteratively refine those solutions using common design patterns and architectural techniques to avoid scalability, maintainability, and correctness pitfalls.

The course is designed around a big team project. Students will work in teams of three and will be evaluated multiple times throughout the semester. The project emphasizes building a complete, end-to-end system that integrates mobile, backend, and cloud components.

In addition, there will be several shorter assignments that apply course concepts in smaller, focused applications.

Learning Objectives

By the end of this course, students should be able to:

• Build software using the fundamentals of mobile application development, including event-driven programming and the application lifecycle

• Recognize and apply design patterns and tools specific to a mobile-app platform; on Android, for example, the Model–View–ViewModel (MVVM) pattern and the principles of Material Design

• Design, implement, and test Android applications using appropriate tools and testing strategies

• Build and integrate backend servers and cloud-based services to support mobile applications

• Create applications that interact with local and external events and services, such as sensors, network APIs, and dynamic cloud storage

• Incorporate AI and machine learning features into mobile applications where appropriate

• Use and interoperate between multiple programming languages and technologies within an Android application

• Work effectively in teams to deliver polished products despite vague or evolving client requirements

• Continually extend an existing code and improve its implementation through high-level refactoring

• Present designs and code clearly to both informed and uninformed audiences

Textbook

None required.

Schedule

The course meets Tuesday, Thursday, 12:25-1:45PM in HEB 2008 (https://map.utah.edu/index.html?code=HEB)

Course Staff

Instructor: Nabil Makarem
Email: nabil@cs.utah.edu
Office: MEB 3124
Office Hours: T/TH 11:00 AM - 12:00 PM

TAs:

• Logan Pu. Email: u1261116@utah.edu, Github user: Logan256.
  Help hours (CADE Lab): TBD
  
• Matthew Luerssen. Email: u1458845@umail.utah.edu, GitHub user: Leftie520.
  Help hours (CADE Lab): TBD

Grade breakdown

Grades in this course will be determined by:

• 15% Midterm
• 15% Final
• 25% Individuals Assignments
• 40% Team Project
• 5% In-Class Practices

The letter grading policy is as follows:

Score Range	Letter Grade
94–100	A
90–93	A−
87–89	B+
84–86	B
80–83	B−
77–79	C+
74–76	C
70–73	C−
67–69	D+
64–66	D
60–63	D−
0–59	E

I do, however, reserve the right to adjust this scale if need be.

Important Dates

The midterm exam will be in class on Tuesday, February 17, 2026 during the class meeting.

The final exam will be Monday, April 27, 10:30 AM – 12:30 PM as per the university schedule, in our regular classroom.

If you have conflicts with these exam times, reach out ASAP!

Late Policy

10% off per day late for the first 3 days. To submit after that, you'll need to meet with me, and we'll try to come up with a deadline by which you can earn 70% on the assignment.

Given that these are crazy times inside and outside the classroom, reach out to me if there are circumstances that prevent you from doing your best work and I'll try to make appropriate accommodations. The earlier you can let me know, the better.

Course Policies

KSoC policies, including academic misconduct policies can be found here: https://handbook.cs.utah.edu

COE policies can be found here: https://www.coe.utah.edu/students/current/semester-guidelines/

AI tools

At this point in your education, we expect that you're capable programmers, and want to give you the opportunity to use "real world tools." The use of Github copilot for "code completion" is allowed in this course IF THE FOLLOWING CONDITION IS MET. In any commit that has code written with the help of Copilot is, your commit message must contain a discussion of what code Copilot helped with.

If you use ChatGPT or similar tools, cite your usage like you would any other external resource.

The use of AI tools without following the above conditions is considered academic misconduct as you are present working which was not written by you as your own.