2025-2026 Course List

This course introduces the foundational concepts of programming languages, including the principles of language design, language constructs, and comparison of major languages. Topics include formal methods of examining syntax and semantics of languages and lexical analysis of language components and constructs, and propositional and predicate calculi.

Prerequisites:

CIS 223, CIS 224, and admission to major.

This course introduces the foundational concepts of Information Management, Database Systems, Data Modeling, Data Security, Secure Design, Defensive Programming, Security and Cryptography.

Prerequisites:

CIS 223, CIS 224, and admission to major.

An introduction to data communications and networks. The field encompasses local area networks, wide area networks, and wireless communication. Topics include digital signals, transmission techniques, error detection and correction, OSI model, TCP/IP model, network topologies, network protocols, and communications hardware.

Prerequisites:

CIS 223 and CIS 224 or EE 234

This course covers more advanced algorithmic areas, including tree, graph, and text algorithms, as well as the study of algorithmic strategies (e.g., divide-and-conquer, linear programming, etc.). There is an emphasis on the application of efficient algorithms to solve novel problems, and the development of an algorithmic mindset by students. Admission to Major or Permission.

Students learn and practice the essential elements of computer science through research, classical problem or industry project implementation: scoping, modeling, experimentation, analysis, modern tools, creativity, business plans, and global/societal/environmental impacts. Students learn and develop the elements of professionalism while operating in project teams. Topics include leadership, metacognition, teamwork, written and oral communication, ethics and professional and personal responsibility. Course must be taken concurrently with CS 495.

Prerequisites:

CIS 223 and MATH 280

Students learn and practice the essential elements of computer science through research, classical problem or industry project implementation: scoping, modeling, experimentation, analysis, modern tools, creativity, business plans, and global/societal/environmental impacts. Students learn and develop the elements of professionalism while operating in project teams. Topics include leadership, metacognition, teamwork, written and oral communication, ethics and professional and personal responsibility. Course must be taken concurrently with CS 495.

Prerequisites:

CIS 223 and MATH 280

Students further learn and practice the essential elements of computer science through research, classical problem or industry project implementation: scoping, modeling, experimentation, analysis, modern tools, creativity, business plans, and global/societal/environmental impacts. Students continue to learn and develop the elements of professionalism while operating in project teams. Topics include leadership, metacognition, teamwork, written and oral communication, ethics and professional and personal responsibility. Course must be taken concurrently with CS 495.

Prerequisites:

CS 391

Students further learn and practice the essential elements of computer science through research, classical problem or industry project implementation: scoping, modeling, experimentation, analysis, modern tools, creativity, business plans, and global/societal/environmental impacts. Students continue to learn and develop the elements of professionalism while operating in project teams. Topics include leadership, metacognition, teamwork, written and oral communication, ethics and professional and personal responsibility. Course must be taken concurrently with CS 495.

Prerequisites:

CS 391W

Study of theory and/or implementation topics related to operating systems such as security and protection, virtual machines, device management, file systems, real time and embedded systems, fault tolerance and system performance evaluation. Prerequisite: Admission to Major or Permission

Study of theory and/or implementation topics related to programming languages such as syntax analysis, semantic analysis, code generation, runtime systems, static analysis, advanced programming constructs, concurrency and parallelism, type systems, formal semantics, language pragmatics, and logic programming. Prerequisite: Admission to Major or Permission

Study of theory and/or implementation topics related to networking and computation such as mobility and social networking and expansion of topics covered in CS 306. Prerequisite: Admission to Major or Permission

Study of theory and/or implementation topics related to algorithms and computing such as advanced computational complexity, automata theory and computability, and advanced data structures algorithms and analysis. This includes the theoretical underpinnings of modern computer science, focusing on three main models of computation: DFA, PDA and Turing Machines. Students determine model capabilities and limitations: what is and is not computable by each of them.

Prerequisites:

Admission to major or permission.

Study of theory and/or implementation topics related to parallel and distributed computing such as parallel algorithms, architecture, and performance, distributed systems, cloud computing, and formal models and semantics. These have been called techniques for High Performance Computing. Topics also include application areas and basic concepts of parallel computing, hardware design of modern HPC platforms and parallel programming models, methods of measuring and characterizing serial and parallel performance.

Prerequisites:

Admission to major or permission.

Study of theory and/or implementation topics related to computer architecture and organization such as functional organization, multiprocessing and alternative architectures, and performance enhancements. This includes topics in computer architecture including a major emphasis on measuring and improving computer performance. Topics include advances in pipelining and analysis and optimization of storage systems and networks, multiprocessor challenges and trends.

Prerequisites:

Admission to major or permission.

Study of theory and/or implementation topics related to intelligent systems such as Basic Search Strategies, Basic Knowledge Representation and Reasoning, Basic Machine Learning, Advanced Search, Advanced Representation and Reasoning, Reasoning Under Uncertainty, Agents, Natural Language Processing, Advanced Machine Learning, Robotics, and Perception and Computer Vision. Prerequisite: Admission to Major or Permission

Study of theory and/or implementation topics related to information management such as indexing, relational databases, query languages, transaction processing, distributed databases, physical database design, data mining, information storage and retrieval and multimedia systems. Prerequisite: Admission to Major or Permission

Study of theory and/or implementation topics related to information assurance and security, such as defensive programming, threats and attacks, network security, cryptography, web security, platform security, security policy and governance, digital forensics, and secure software engineering. Prerequisite: Admission to Major or Permission

Study of theory and/or implementation topics related to computational science such as modeling and simulation, processing, interactive visualization, data, information and knowledge, and numerical analysis. Prerequisite: Admission to Major or Permission

Study of theory and/or implementation topics related to graphics and visualization such as basic and advanced rendering, geometric modeling, computer animation and visualization. Topics include game programming with concentration on 3D graphics including modeling, rendering, and animation for computer games and graphic simulations. Programs are created using a current graphics and game development environment.

Prerequisites:

Admission to major or permission.

Study of theory and/or implementation topics related to human computer interaction such as designing interaction, programming interactive systems, user-centered design and testing, new interactive technologies, collaboration & communication, statistical methods for HCI, human factors and security, design-oriented HCI, and mixed, augmented and virtual reality. This course builds on the use of modern compilers. Related topics covered include lexical scanning, parsing, type checking, code generation and translation, optimization, and compile-time and run-time support for modern programming languages.

Prerequisites:

Admission to major or permission.

Study of theory and/or implementation topics related to software engineering such as software processes, project management, requirements engineering, software design, construction, verification and validation, reliability, and formal methods. These relate to advanced programming for general-purpose software development. Topics include tools and processes appropriate for employing object-oriented designs and programming within a significant software development environment and advanced data structures and algorithms, graphical user interfaces, and software development processes.

Prerequisites:

Admission to major or permission.

Study of topics theory and/or implementation related to the fundamental differences that Platform-Based Development has over traditional software development addressing topics such as Web Platforms, Mobile Platforms, Industrial Platforms, and Game Platforms. Prerequisite: Admission to Major or Permission

Students gain experience working with a team to solve a substantial problem in the field of computer science using concepts that span several topic areas in computer science related to cognitive science. Class time focuses primarily on project design and implementation. Senior standing in the Cognitive Science major with a Computer Science Focus.

Prerequisites:

Senior standing and successful completion of all core requirements.

The first in a two-semester sequence of capstone design. Students build on the experience gained in CS 391W/392W to bring their research or project implementation and leadership to that expected of contributing computer scientists in industry or research. Course must be taken concurrently with CS 495.

Prerequisites:

CS 301, CS 302, CS 303, CS 304, CS 392

The first in a two-semester sequence of capstone design. Students build on the experience gained in CS 391W/392W to bring their research or project implementation and leadership to that expected of contributing computer scientists in industry or research. Course must be taken concurrently with CS 495.

Prerequisites:

CS 301, CS 302, CS 303, CS 304, CS 392W