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

Analyzes modern software engineering practice for multi-person projects; methods for requirements specification, design, implementation, verification, and maintenance of large software systems; advanced software development techniques and large project management approaches; project planning, scheduling, resource management, configuration control, and documentation. Prerequisite: CS 2150 or CS 3140 with a grade of C- or better

A second course in computing with an emphasis on foundational data structures and program analysis. The course provides a introduction to object oriented programming and the Java programming language, concurrency, and inheritance / polymorphism. Additionally, foundational data structures and related algorithms / analysis are studied. These include lists, stacks, queues, trees, hash tables, and priority queues. Prereq: CS 1110 or CS 1111 or CS 1112 or CS 1113 or place out test for CS 1110 or CS 2100  

Presents the fundamental concepts of programming language design and implementation. Emphasizes language paradigms and implementation issues. Develops working programs in languages representing different language paradigms. Many programs oriented toward language implementation issues. Prerequisite: CS 2150 or (CS 2120 and 3140) with a grade of C- or better

Supports the writing of the technical report component of the fourth-year thesis, credit for which is given in STS 4600. Students will write the report assuming a non-technical audience. The course is part of the CS 4XXX elective option in the fourth-year CS thesis track. BS CS 4th years (both first & second majors) and pre- or co-requisite STS 4500

An introduction to machine learning: the study of algorithms that improve their performance through experience. Covers both machine learning theory and algorithms. Introduces algorithms, theory, and applications related to both supervised and unsupervised learning, including regression, classification, and optimization and major algorithm families for each.Prerequisites: CS 2150 or CS 3100 with a grade of C- or better; APMA 3100, APMA 3110, MATH 3100, or equivalent and Math 3350 or APMA 3080 or equivalent

Introduces discrete mathematics and proof techniques involving first order predicate logic and induction. Application areas include sets, tuples, functions, relations, and combinatorial problems. Prereq: Must have completed CS 1110 or CS 1111 or CS 1112 or CS 1113 with a grade of C- or better OR successfully completed the CS 1110 or CS 2100 place out test.

Introduces artificial intelligence. Covers fundamental concepts and techniques and surveys selected application areas. Core material includes state space search, logic, and resolution theorem proving. Application areas may include expert systems, natural language understanding, planning, machine learning, or machine perception. Provides exposure to AI implementation methods, emphasizing programming in Common LISP. Prerequisite: CS 2150 or CS 3100 with a grade of C- or better

An introduction to testing for assuring software quality. Covers concepts and techniques for testing software, including testing at the unit, module, subsystem, and system levels; automatic and manual techniques for generating and validating test data; the testing process; static vs. dynamic analysis; functional testing; inspections; testing in specific application domains; and reliability assessment.Prerequisite: CS 2150 or (CS 2100 and CS 2120) with a grade of C- or better

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.