Computer Science

Computer Science

Sitterson Hall, CB# 3175
(919) 590-6200

First Session, 2024

COMP 110 Introduction to Programming and Data Science (3)

Introduces students to programming and data science from a computational perspective. With an emphasis on modern applications in society, students gain experience with problem decomposition, algorithms for data analysis, abstraction design, and ethics in computing. No prior programming experience expected. Foundational concepts include data types, sequences, boolean logic, control flow, functions/methods, recursion, classes/objects, input/output, data organization, transformations, and visualizations. Students may not enroll in COMP 110 after receiving credit for COMP 210. Honors version available.

COMP 116 Introduction to Scientific Programming (3)

An introduction to programming for computationally oriented scientists. Fundamental programming skills, typically using MATLAB or Python. Problem analysis and algorithm design with examples drawn from simple numerical and discrete problems.

COMP 210 Data Structures and Analysis (3)

This course will teach you how to organize the data used in computer programs so that manipulation of that data can be done efficiently on large problems and large data instances. Rather than learning to use the data structures found in the libraries of programming languages, you will be learning how those libraries are constructed, and why the items that are included in them are there (and why some are excluded).

COMP 283 Discrete Structures (3)

Introduces discrete structures (sets, tuples, relations, functions, graphs, trees) and the formal mathematics (logic, proof, induction) used to establish their properties and those of algorithms that work with them. Develops problem-solving skills through puzzles and applications central to computer science. Honors version available.

COMP 301 Foundations of Programming (3)

Prerequisites, COMP 210; COMP 283 or MATH 381; a grade of C or better is required. Students will learn how to reason about how their code is structured, identify whether a given structure is effective in a given context, and look at ways of organizing units of code that support larger programs. In a nutshell, the primary goal of the course is to equip students with tools and techniques that will help them not only in later courses in the major but also in their careers afterwards.

COMP 550 Algorithms and Analysis (3)

Formal specification and verification of programs. Techniques of algorithm analysis. Problem-solving paradigms. Survey of selected algorithms.

Second Session, 2024

COMP 110 Introduction to Programming and Data Science (3)

Introduces students to programming and data science from a computational perspective. With an emphasis on modern applications in society, students gain experience with problem decomposition, algorithms for data analysis, abstraction design, and ethics in computing. No prior programming experience expected. Foundational concepts include data types, sequences, boolean logic, control flow, functions/methods, recursion, classes/objects, input/output, data organization, transformations, and visualizations. Students may not enroll in COMP 110 after receiving credit for COMP 210. Honors version available.

COMP 116 Introduction to Scientific Programming (3)

An introduction to programming for computationally oriented scientists. Fundamental programming skills, typically using MATLAB or Python. Problem analysis and algorithm design with examples drawn from simple numerical and discrete problems.

COMP 210 Data Structures and Analysis (3)

This course will teach you how to organize the data used in computer programs so that manipulation of that data can be done efficiently on large problems and large data instances. Rather than learning to use the data structures found in the libraries of programming languages, you will be learning how those libraries are constructed, and why the items that are included in them are there (and why some are excluded).

COMP 301 Foundations of Programming (3)

Prerequisites, COMP 210; COMP 283 or MATH 381; a grade of C or better is required. Students will learn how to reason about how their code is structured, identify whether a given structure is effective in a given context, and look at ways of organizing units of code that support larger programs. In a nutshell, the primary goal of the course is to equip students with tools and techniques that will help them not only in later courses in the major but also in their careers afterwards.

COMP 520 Compilers (3)

Design and construction of compilers. Theory and pragmatics of lexical, syntactic, and semantic analysis. Interpretation. Code generation for a modern architecture. Run-time environments. Includes a large compiler implementation project.