Computer Science Curriculum

At Gettysburg College, the Computer Science curriculum is designed to empower students to become innovative problem solvers and ethical leaders in a rapidly evolving digital world. Rooted in a liberal arts tradition, the program emphasizes both the theoretical foundations and practical applications of computer science, preparing students to think critically, collaborate effectively, and adapt to new technologies and challenges throughout their careers.

From the very first course, students are immersed in the logic and creativity that drive modern computing. The curriculum begins with a solid grounding in core areas such as programming, algorithms, data structures, and computer systems. As students progress, they delve into advanced topics including software engineering, databases, artificial intelligence, cybersecurity, and operating systems. The program encourages exploration and flexibility, allowing students to tailor their studies to align with their interests—whether that’s web development, machine learning, game design, or computational science.

Hands-on learning is a hallmark of the curriculum. Students gain extensive experience through team-based projects, open-ended assignments, and research opportunities alongside faculty. These experiences help them develop not only technical expertise, but also the communication and project management skills that are highly valued in the workplace. A capstone course allows seniors to bring together everything they’ve learned to create a substantial, real-world software project, often in collaboration with campus partners or local organizations.

The department also fosters a strong sense of community and mentorship. With small class sizes and accessible faculty, students benefit from close guidance and support throughout their academic journey. Many students choose to double major or pursue interdisciplinary interests—pairing computer science with fields like physics, music, economics, or biology—which broadens their perspectives and enhances their impact.

A degree in computer science from Gettysburg opens the door to a wide array of careers. Graduates are well prepared to enter the tech industry, pursue graduate study, or apply their skills in education, health care, finance, public service, and more. Alumni have gone on to work for leading companies, contribute to start-ups, and conduct groundbreaking research. They carry with them the adaptability, creativity, and ethical grounding that come from a Gettysburg education.

Whether you're drawn to writing elegant code, solving complex problems, or imagining the next big innovation, the computer science curriculum at Gettysburg College offers the tools, experiences, and inspiration to help you thrive.

Requirements for the Computer Science major

The requirements for a Bachelor of Arts in computer science are 10 courses in computer science at the level of Computer Science 111 or above. One of the courses may be selected from a list of approved courses offered by other departments.

The 10 courses must include:

Plus three CS elective courses (non-core) at the 200- or 300-level, optionally including at most one from the following list:

In addition to the 10 courses in computer science, students must take:

• Equivalent of Mathematics 111 or above (usually taken during the first year)

Bachelor of Science major in Computer Science

A Bachelor of Science major in Computer Science has the same requirements as a Bachelor of Arts major in Computer Science plus four additional courses from formal and/or natural science departments. At most two of the additional courses may be at the 100-level.

Requirements for the Computer Science minor

The minor in Computer Science consists of any six Computer Science courses numbered 111 or above and must include CS216 and at least one 300 level course (other than CS301).

Grade Requirements: All courses taken to satisfy the requirements for the major or minor must be taken using the A–F grading system. To advance to a course with prerequisites, a minimum grade of C– is required for each prerequisite course. A student completing a Computer Science major course may not concurrently or subsequently be enrolled in a prerequisite, alternate prerequisite, or non-major Computer Science course. For example,

• 216 disallows 103, 107, 111, 112
• 112 disallows 103, 107, 111
• 111 disallows 103, 107
• 107 disallows 103
 

Note: Starting with Fall 2020 CS107 is no longer equivalent to CS111.

Courses

Jump to level: 100 • 200 • 300 • 400

• CS-102 Security, Privacy, and Data
  Introduction to cybersecurity and privacy and their intersection with data analysis. Topics include confidentiality, integrity, availability (CIA triad), authentication, cyberattacks, legal issues, intellectual property and anonymity. Throughout the course, students will study the use and influence of data analysis using tools such as spreadsheets or programming languages.
• CS-103 Introduction to Computing
  Liberal arts introduction to the discipline of computer science and the use of computers in a variety of fields. Topics include a historical survey of technology and the use of computers, computer application, software systems design, programming with scripts, computer hardware and digital logic design, and implications of computing. Course is laboratory-oriented and includes several hands-on laboratory projects. Tailored for non-majors interested in learning about the field of Computer Science. Concurrent registration with CS 107 or CS 111 is not allowed; credit cannot be received for CS 103 after credit received for CS 107 or CS 111. Prerequisite: none.
• CS-107 Introduction to Scientific Computation
  Introduction to computer science with a scientific computation language (e.g., MATLAB or Python). Emphasis is on fundamental programming constructs, algorithmic thinking and problem-solving, fundamental data structures, and recursion. Course projects include common scientific computing challenges and data visualization. Tailored for non-majors interested in mathematics or the sciences. Concurrent registration with CS 103 or CS 111 is not allowed; credit cannot be received for CS 107 after credit received for CS 111. Prerequisite: none..
• CS-111 Computer Science I
  Introduction to computer science with an emphasis on fundamental programming constructs, algorithmic thinking and problem-solving, fundamental data structures, and recursion. Students implement projects using the Java programming language. This course is the usual beginning course for students planning to pursue a major or minor in computer science. Prerequisite: none.
• CS-112 Computer Science II
  Second course in the introductory sequence for computer science majors and students interested in the principles of programming. Special attention is given to object-oriented program design methods, algorithms, and elementary data structures. Prerequisite: Computer Science 111.
• CS-201 The Mathematics of Computation
  Study of the mathematics needed for an understanding of the theoretical foundations of computation. Topics include mathematical logic, set theory, mathematical induction, mathematical definitions and proofs, graph theory, and an introduction to finite-state automata. Applications and illustrative examples are drawn from computer science topics such as digital circuits, analysis and correctness of algorithms, automata, decidable problems, and efficient searching. Prerequisites: Computer Science 107/111 and Mathematics 111.
• CS-216 Data Structures and Algorithms
  Introduction to major data structures and some of their applications. Topics include sets, queues, stacks, linked lists, string processing, trees, graphs, arrays, tables, files, and an introduction to the analysis of algorithms. Prerequisite: Computer Science 112.
• CS-221 Computer Organization and Assembly Language Programming
  Programming at the machine level, with emphasis on the logical connection of the basic components of the computer and systems programs. Topics include machine and assembly language programming, basic computer operations, data representation, hardware organization, systems software, and compilers. Prerequisite: Computer Science 112.
• CS-301 The Theory of Computation
  Study of the basic theoretical principles of the computational model. Topics include finite automata, regular expressions, context-free grammars, Turing Machines, Church’s Thesis, P and NP classes, the halting problem, unsolvability, computational complexity, and program verification. Prerequisite: Computer Science 201.
• CS-322 Introduction to Computer Networks
  Introduction to principles used to analyze and build a network of computers. Course covers concepts and issues relating to low-level communications and protocols of computer networking. Students study formal methods for integrating communication events into normal process cycles of the computer, then concentrate on a study of practices for defining and specifying a formal communications protocol. Throughout the course, students apply principles that they study to existing networks within the department. Prerequisite: Computer Science 216. Offered alternate years.
• CS-324 Principles of Operating Systems
  Study of fundamental concepts of operating systems. Topics include sequential processes, concurrent processes, processor management, memory management, scheduling algorithms, and computer security. Projects include writing of a program to simulate major components of an operating system. Prerequisite: Computer Science 216. Offered alternate years.
• CS-327 Parallel and Distributed Processing
  Introduction to techniques used to implement multiple processor problem-solving environments. Investigation includes several different environments for parallel computing, including SIMD (Single Instruction Multiple Data stream), MIMD (Multiple Instructions Multiple Data stream), and computing in a distributed workstation environment. Students work with actual implementations of each of these environments and explore their advantages and design algorithms appropriate for these environments. Prerequisite: Computer Science 216. Offered alternate years.
• CS-341 Principles of Programming Languages
  Study of fundamental concepts in the design of programming languages. Concepts include BNF grammar specification, abstract syntax trees, variables, expressions typing, scope, lexical address, procedures, data types, static/dynamic binding, and environment-passing interpreters. Special emphasis is placed on the development of an interpreter using a functional programming language. Other languages are introduced to further illustrate these concepts. Prerequisite: Computer Science 216. Offered alternate years.
• CS-360 Principles of Database Systems
  Study of fundamental concepts of database systems. Topics include physical organization of databases, indexing techniques, and query processing. Particular models studied include the Entity-Relationship and Relational. Class projects stress design and implementation of a database. Prerequisite: Computer Science 216. Offered alternate years.
• CS-371 Introduction to Artificial Intelligence
  Study of modern techniques for creating software that behaves intelligently. Topics include uninformed and heuristic search, constraint satisfaction, stochastic optimization, game-tree search, propositional reasoning, probabilistic reasoning, Bayesian networks with Markov chain Monte Carlo techniques, and robotics. Course concludes with a class robotics project. Prerequisite: Computer Science 216. Offered alternate years.
• CS-373 Computer Graphics
  Study of methods and issues surrounding the construction of graphical images on the computer. Topics include windowing systems and user input, two-dimensional graphics packages, curve drawing techniques, modeling in three dimensions, use of lighting and shading techniques, and the process of rendering images. Student work consists both of using existing packages to create images and of implementing algorithms used in graphical systems. Prerequisite: Computer Science 216. Offered alternate years.
• CS-374 Compilers
  Introduction to techniques used to translate high-level computer languages into machine code. Course covers current implementation techniques and relevant theory. Topics include lexical scanning, parsing, abstract syntax trees, semantic analysis, intermediate code generation, and code generation. Students complete a major project involving the compilation of a particular computer language. Prerequisite: Computer Science 216. Offered alternate years.
• CS-391 Selected Topics
• CS-392 Selected Topics
• CS-440 Advanced Systems Design
  Senior capstone course teaching a formal approach to techniques of computer project development. Integral part of course is the involvement of students, working as a team, in the development of a large project. Topics include formal requirement and specification, software testing techniques, written and spoken communication skills in technology, and user interfaces. Research option is available by permission of the instructor with a faculty research sponsor and recommendation from a previous research supervisor. Prerequisites: Computer Science 216, two 300-level computer science course (other than CS 301; one may be taken concurrently), and senior status or permission of department.
• CS-453 Individualized Study-Tutorial
  Individualized tutorial not counting in the minimum requirements in a major or minor, graded S/U
• CS-463 Individualized Study-Research
  Individualized research not counting in the minimum requirements in a major or minor, graded S/U. In consultation with faculty advisor students prepare course proposal that includes description of topic of study, readings list, and course schedule. Prerequisite: Computer Science 216 and permission of department.
• CS-477 Half Credit Internship
  Half credit internship, graded S/U.