A first course in software engineering and software construction, this course focuses on bringing the programming concepts learned in a first course in data structures and algorithms together to begin to teach students how to build more complex systems. The course covers introductory topics in testing, software design principles, design patterns, functional programming, and data storage and manipulation. Completed CS 2100 with a C- or better.

Viruses, worms, and other malicious software are an ever-increasing threat to computer systems. There is an escalating battle between computer security specialists and the designers of malicious software. This course provides an essential understanding of the techniques used by both sides of the computer security battle. Prerequisite: CS 3710 with a grade of C- or better

This course will introduce students to the concepts and tools used in the development of modern 2-D and 3-D real-time interactive computer video games. Topics covered in this include graphics, parallel processing, human-computer interaction, networking, artificial intelligence, and software engineering. Prerequisite: CS 3140 with a grade of C- or better

Content varies, depending on instructor interests and the needs of the Department. Taught strictly at the undergraduate level. Prerequisite: Instructor permission; additional specific requirements vary with topics.

In-depth study of a computer science or computer engineering problem by an individual student in close consultation with departmental faculty. The study is often either a thorough analysis of an abstract computer science problem or the design, implementation, and analysis of a computer system (software or hardware). Prerequisite: Instructor permission.

This course provides an overview of the state of the art in software analysis including static and dynamic analysis techniques and verification and validation. It explores the various ways that the analyses are used to predict software behavior. The applications include inference, symbolic execution, fault localization, model checking, security and performance. The course combines theory with practical implementation and usage. Prerequisites: CS 3240.

The goal of this course is to understand the fundamental limits on what can be efficiently computed. These limits reveal properties about information, communication, and computing, as well as practical issues about how to solve problems. Introduces computation theory including grammars, automata, and Turing machines. Prereq: CS 3100 with a grade of C- or better

Builds upon previous analysis of algorithms and the effects of data structures on them. Algorithms selected from areas such as searching, shortest paths, greedy algorithms, backtracking, divide-and-conquer, dynamic programming, and machine learning. Analysis techniques include asymptotic worst case, expected time, amortized analysis, and reductions. Prerequisites: CS 2100 & CS 2120. Background in topics covered in a first course in Calculus is required. CS 3140 is recommended.

Analyzes process communication and synchronization; resource management; virtual memory management algorithms; file systems; and networking and distributed systems. Prerequisite: CS 3130 with a grade of C- or better.

This course covers topics on the computer architecture abstraction hierarchy ranging from a step above silicon to a step below modern programming languages. Students in this course will learn to write low-level code in C and Assembly, how data is stored in memory, the basics of hardware design from gates and registers through general-purpose computers, and legal, ethical, and security issues related to these topics. CS 1100 - CS 1199 and either familiarity with Java, C++, or another C-like language, or concurrent enrollment in CS 2100