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Software Engineering (PhD) Doctor of Philosophy

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- Center for World University Rankings, 2024

In Best Value Among Arizona's Public Universities

- Payscale, 2022

The University of Arizona's College of Engineering has launched the Software Engineering PhD degree in response to the high demand for individuals trained in the software engineering discipline. The degree program is critical in driving student success in a rapidly changing world and tackling essential problems at the edges of human endeavor. 

As a student graduating with a PhD in Software Engineering, you will be better positioned to develop the skills and mindsets to be leaders in software development, computing, machine learning, ever-increasing automation and connectivity, human and intelligent systems, data science, and network sciences.

Through the PhD program, you'll demonstrate the ability to design, develop, test, integrate, and evaluate software applications/products/systems in diverse computing and engineering domains. You'll also be able to critically analyze and review published research results and other literature related to your area of study. You'll also demonstrate your ability to articulate all aspects of the research in your software engineering specialization area, describe and defend the significance of your work, explain your research methodologies, and summarize your findings. 

The global software engineering market alone will be worth $64 billion by 2025, and it is a vital part of a larger industry. Some factors behind this growth include increased automation in multiple sectors, the demand for cloud-based solutions, the Internet of Things, and an increased number of devices that can be used in daily life for convenience. Thus, pursuing a Software Engineering PhD will give you a competitive edge in this fast-growing industry.

No GRE is required for this graduate degree program.

A minor is required for this program and will be determined by the student and advisor.

Students who do not have a degree equivalent to the University of Arizona Bachelor of Science degree in a computing-related program may be admitted into the graduate program but may be required to complete additional graduate-level pre-requisite courses prior to enrolling in some graduate courses. 

Proficiency in one or more programming languages OR one to two years of industry experience in a software-related position is required.

*Residents of some U.S. Territories may not be eligible. Please see our Eligibility & State Authorization page for more information.

Courses for this program include: 

SFWE 502: Software DevSecOps

This course will allow you to explore key principles of a DevSecOps approach to software development. Development (Dev) and operations (Ops) are the union of people, processes, and technology to continually automate and develop higher-quality/more reliable software products faster. Security (Sec) is integrated into a typical DevOps pipeline to address potential security issues in code as soon as possible in the software development lifecycle.

SFWE 503: Software Project Management

In this course, you will learn how to plan, track, and communicate the status of large-scale software projects to a diverse group of stakeholders. Using modern traditional and Agile software development methodologies and tools and emulating a realistic software development project, students will be immersed in the activities used by industry to develop, manage, and monitor software product development throughout the semester. You’ll learn why planning a software project is important, what constitutes a good plan, how to adapt to the unexpected and unknowns that are likely to occur throughout the project development, and how to track and share the status of the project with your team members, other teams, and the customers/business managers.

SFWE 504: Software Requirements Analysis & Test

Learn how to derive and develop software requirements that are measurable, testable, and lead to a compliant software design and implementation. Using industry best practices and tools, you will learn how to elicit, analyze, specify, and validate functional requirements (what should the software system do) and non-functional software requirements (how should the software system fulfill the functional requirements). You will develop software requirement models and specifications that capture the customer/user's needs.

SFWE 505: Software Architecture & Design

In this course, you'll explore different architectural styles and patterns and learn to apply modern processes, methods, and tools in architecting, modeling, and designing software systems. They will also learn the importance of developing a sound software architecture as part of the overall software design.  

SFWE 506: Distributed Computing

In this course, you will explore the unique aspects and considerations required to develop a large-scale software product in a distributed computing environment. Distributed computing refers to a system where processing and data storage are distributed across multiple devices or systems rather than being handled by a single central device. In a distributed system, each device or system has its own processing capabilities and may also store and manage its own data. 

SFWE 507: Foundations of Software Engineering

Gain foundational skills and knowledge used by software engineers in diverse industries. The course introduces you to the different software development lifecycle (SDLC) phases used in developing, delivering, and maintaining software products for a wide variety of applications. Common software process models will be introduced, along with developing an understanding of the importance of defining software requirements, developing software architectures and designs, and the various forms of testing that go into delivering reliable and resilient software systems.

SFWE 509: Cloud Computing Principles and Practices

This introductory course on cloud computing delves into the fundamental technologies and ideas that make up contemporary cloud computing infrastructure. You'll get hands-on practice using cloud service models (IaaS, PaaS, SaaS, FaaS), virtualization, data centers, cloud management, and essential Linux commands. The course also covers advanced topics such as cloud storage, containers, microservices, serverless computing, cloud security, emerging trends in cloud IoT, mobile clouds, edge computing, and big data processing.

SFWE 510: Cloud Native Software Engineering

This course introduces the design and implementation of decentralized systems with up-to-date software architecture and relevant development frameworks. Topics include inter-module communication, asynchronous processing, security, concurrency, parallelism, and an overview of contemporary enterprise technology and challenges. The course also dives into the development, infrastructure, best practices, and DevOps practices for monitoring and debugging such systems.

Earning your Doctor of Philosophy in Software Engineering (PhD) will build core skills, including:

• Agile methodology
• Algorithm design & optimization
• Artificial Intelligence
• Cloud & distributed computing
• Continuous deployment
• Continuous integration
• Cybersecurity practices & standards
• Full stack development
• Machine learning algorithms & approaches
• Programming language proficiency
• Software Development Lifecycle
• Software engineering

Potential Career Paths

Graduates of the Software Engineering PhD program will be prepared to pursue careers in the following fields, among many others:

• Artificial Intelligence/Machine Learning
• Aerospace & Defense
• Space Exploration
• Data Science & Analytics
• Medical Devices Technologies
• Financial Systems & Technologies
• Quantum Computing
• Automotive/Vehicle Networking/Autonomous Driving
• Cybersecurity Analysis
• Engineering
• Systems & Software Solutions Architecture
• Mobile Computing
• Computer Vision
• Cloud Computing/Networking

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Doctor of Philosophy in Software Engineering

Program description.

The PhD in Software Engineering program is tailored to the student. The student must arrange a course program with the guidance and approval of a faculty member chosen as their graduate advisor. Adjustments can be made as the student’s interests develop and a specific dissertation top is chosen.

The software engineering researchers in the Department of Computer Science are focused on issues related to effectively developing large-scale, complex systems. In particular, new categories of applications are emerging such as big data, cyber physical, and autonomous adaptable systems, which continue to drive leading edge research in software engineering on diverse topics. Key research areas include requirements engineering, architecture, design, service-oriented computing, testing and verification, static analysis, software maintenance and multi-agent systems.

Career Opportunities

Virtually all major companies and corporations need software related core competencies. Software engineers are central in developing and making use of these competencies. They work in teams that interface extensively with clients, company executives, IT managers, data scientists, security and domain experts.

Software engineering professionals are creative, highly collaborative, well paid, and in very high demand with employers. Graduates of the program seek academic positions at universities, as well as positions as researchers, senior software engineers and data scientists. Graduates often become industry experts in various fields like cybersecurity, artificial intelligence, machine learning and natural language processing.

Marketable Skills

Review the marketable skills for this academic program.

Application Requirements

Test score required:  Yes

Deadlines:  University  deadlines  apply.

Admission Option One

• Degree requirements:  A master’s degree in computer science or its equivalent
• GPA:  Minimum of 3.5
• Test score:  Minimum revised GRE scores of 308, 153, 155, and 4 for the combined, verbal, quantitative and analytical writing components, respectively, are advisable.

Admission Option Two

• Degree requirements:  A BS degree in related area that includes two semesters of calculus and linear algebra.
• GPA:  Minimum of 3.5 in the last 60 semester credit hours.
• Test score:  Minimum revised GRE scores of 315, 156, 159 and 4 for the combined, verbal, quantitative and analytical writing components, respectively, are advisable.

Applicants are admitted on a competitive basis.

Contact Information

Admissions Email: [email protected]

Shyam Karrah Email: [email protected] Phone: 972-883-4197 Office: ECSS 4.704 Website: personal.utdallas.edu/~skarrah

Erik Jonsson School of Engineering and Computer Science The University of Texas at Dallas, ECW41 800 W. Campbell Road Richardson, TX 75080-3021 Email: [email protected]

cs.utdallas.edu engineering.utdallas.edu

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