Course Information
 2017–2018 Courses:
 Browse by Course Number
 Browse by Term
Fall 2017

CS 111: Introduction to Computer Science
This course will introduce you to computer programming and the design of algorithms. By writing programs to solve problems in areas such as image processing, text processing, and simple games, you will learn about recursive and iterative algorithms, complexity analysis, graphics, data representation, software engineering, and objectoriented design. No previous programming experience is necessary. Students who have received credit for Computer Science 201 or above are not eligible to enroll in Computer Science 111. Students may not simultaneously enroll for CS 108 and CS 111 in the same term. 6 credit; Formal or Statistical Reasoning, Quantitative Reasoning Encounter; offered Fall 2017, Winter 2018, Spring 2018 · David LibenNowell, Blake S Howald, Sherri L Goings, Layla K Oesper, Eric C Alexander, David R Musicant 
CS 201: Data Structures
Think back to your favorite assignment from Introduction to Computer Science. Did you ever get the feeling that "there has to be a better/smarter way to do this problem?" The Data Structures course is all about how to store information intelligently and access it efficiently. How can Google take your query, compare it to billions of web pages, and return the answer in less than one second? How can one store information so as to balance the competing needs for fast data retrieval and fast data modification? To help us answer questions like these, we will analyze and implement stacks, queues, trees, linked lists, graphs and hash tables. Students who have received credit for a course for which Computer Science 201 is a prerequisite are not eligible to enroll in Computer Science 201. Prerequisites: Computer Science 111 or instructor permission 6 credit; Formal or Statistical Reasoning, Quantitative Reasoning Encounter; offered Fall 2017, Winter 2018, Spring 2018 · Layla K Oesper, Eric C Alexander, Jed C Yang, Blake S Howald 
CS 202: Mathematics of Computer Science
This course introduces some of the formal tools of computer science, using a variety of applications as a vehicle. You'll learn how to encode data so that when you scratch the back of a DVD, it still plays just fine; how to distribute "shares" of your floor's PIN so that any five of you can withdraw money from the floor bank account (but no four of you can); how to play chess; and more. Topics that we'll explore along the way include: logic and proofs, number theory, elementary complexity theory and recurrence relations, basic probability, counting techniques, and graphs. Prerequisites: Computer Science 111 and Mathematics 111 or instructor permission 6 credit; Formal or Statistical Reasoning; offered Fall 2017, Spring 2018 · Eric C Alexander, David LibenNowell 
CS 251: Programming Languages: Design and Implementation
What makes a programming language like "Python" or like "Java?" This course will look past superficial properties (like indentation) and into the soul of programming languages. We will explore a variety of topics in programming language construction and design: syntax and semantics, mechanisms for parameter passing, typing, scoping, and control structures. Students will expand their programming experience to include other programming paradigms, including functional languages like Scheme and ML. Prerequisites: Computer Science 201 or instructor permission 6 credit; Formal or Statistical Reasoning; offered Fall 2017, Spring 2018 · Jed C Yang 
CS 254: Computability and Complexity
An introduction to the theory of computation. What problems can and cannot be solved efficiently by computers? What problems cannot be solved by computers, period? Topics include formal models of computation, including finitestate automata, pushdown automata, and Turing machines; formal languages, including regular expressions and contextfree grammars; computability and uncomputability; and computational complexity, particularly NPcompleteness. Prerequisites: Computer Science 111 and Computer Science 202 (Mathematics 236 will be accepted in lieu of Computer Science 202) 6 credit; Formal or Statistical Reasoning; offered Fall 2017, Winter 2018 · Jed C Yang 
CS 257: Software Design
It's easy to write a mediocre computer program, and lots of people do it. Good programs are quite a bit harder to write, and are correspondingly less common. In this course, we will study techniques, tools, and habits that will improve your chances of writing good software. While working on several mediumsized programming projects, we will investigate code construction techniques, debugging and profiling tools, testing methodologies, UML, principles of objectoriented design, design patterns, and user interface design. Prerequisites: Computer Science 201 or instructor permission 6 credit; Formal or Statistical Reasoning; offered Fall 2017, Winter 2018, Spring 2018 · Amy Csizmar Dalal, Jeffrey R Ondich 
CS 298: Reading and Analysis Associated with External Computing Experience
An independent study course intended for students who require Curricular Practical Training (CPT) or Optional Practical Training (OPT) to go with an external activity related to computer science (for example, an internship or an externship). The student will choose and read academic material relating to a practical experience (e.g., internship), and write a paper describing what the student learned from the reading, and how it related to the practical experience.
Prerequisites: Instructor's permission 1 credit; S/CR/NC; Does not fulfill a curricular exploration requirement; offered Fall 2017, Winter 2018 · Jeffrey R Ondich 
CS 322: Natural Language Processing
Computers are poor conversationalists, despite decades of attempts to change that fact. This course will provide an overview of the computational techniques developed in the attempt to enable computers to interpret and respond appropriately to ideas expressed using natural languages (such as English or French) as opposed to formal languages (such as C++ or Lisp). Topics in this course will include parsing, semantic analysis, machine translation, dialogue systems, and statistical methods in speech recognition. Prerequisites: Computer Science 201 and Computer Science 202 (Mathematics 236 will be accepted in leiu of Computer Science 202) 6 credit; Formal or Statistical Reasoning; offered Fall 2017 · Blake S Howald 
CS 332: Operating Systems
The thing that we call a computer is actually a complex collection of interacting devices. To ensure that these devices work together effectively without excessive human intervention, people have developed operating systems software that coordinates the behavior of the devices and gives programmers ways to control those devices. This course will address the fundamental problems that operating systems need to solve, including those concerned with process management, file organization, memory management, and input/output control. We will also study the structure of the Linux operating system.
Prerequisites: Computer Science 201 and 208 or instructor permission 6 credit; Formal or Statistical Reasoning; offered Fall 2017 · Sherri L GoingsExtended departmental description for CS 332
If you're working in the lab, you might be editing a file while waiting for a program to compile. Meanwhile, the onscreen clock ticks, a program keeps watch for incoming email, and other users can log onto your machine from elsewhere in the network. Not only that, but if you write a program that reads from a file on the hard drive, you are not expected to concern yourself with turning on the drive's motor or moving the read/write arms to the proper location over the disk's surface. Coordinating all this hardware and software is the job of the operating system.
In this course we will study the fundamental problems faced by operating system designers. We will look at interprocess communication, memory management, file systems, and input/output in general and in the context of particular operating systems. We will also study some parts of the Linux source code.

CS 399: Senior Seminar
As part of their senior capstone experience, majors will work together in teams (typically four to seven students per team) on facultyspecified topics to design and implement the first stage of a project. Required of all senior majors.
Prerequisites: Senior standing. Students are strongly encouraged to complete Computer Science 252 and either Computer Science 204 or 257 before starting Computer Science 399. 3 credit; S/CR/NC; Does not fulfill a curricular exploration requirement; offered Fall 2017 · Jeffrey R Ondich, David LibenNowell, Eric C Alexander, Amy Csizmar Dalal
Winter 2018

CS 111: Introduction to Computer Science
This course will introduce you to computer programming and the design of algorithms. By writing programs to solve problems in areas such as image processing, text processing, and simple games, you will learn about recursive and iterative algorithms, complexity analysis, graphics, data representation, software engineering, and objectoriented design. No previous programming experience is necessary. Students who have received credit for Computer Science 201 or above are not eligible to enroll in Computer Science 111. Students may not simultaneously enroll for CS 108 and CS 111 in the same term. 6 credit; Formal or Statistical Reasoning, Quantitative Reasoning Encounter; offered Fall 2017, Winter 2018, Spring 2018 · David LibenNowell, Blake S Howald, Sherri L Goings, Layla K Oesper, Eric C Alexander, David R Musicant 
CS 201: Data Structures
Think back to your favorite assignment from Introduction to Computer Science. Did you ever get the feeling that "there has to be a better/smarter way to do this problem?" The Data Structures course is all about how to store information intelligently and access it efficiently. How can Google take your query, compare it to billions of web pages, and return the answer in less than one second? How can one store information so as to balance the competing needs for fast data retrieval and fast data modification? To help us answer questions like these, we will analyze and implement stacks, queues, trees, linked lists, graphs and hash tables. Students who have received credit for a course for which Computer Science 201 is a prerequisite are not eligible to enroll in Computer Science 201. Prerequisites: Computer Science 111 or instructor permission 6 credit; Formal or Statistical Reasoning, Quantitative Reasoning Encounter; offered Fall 2017, Winter 2018, Spring 2018 · Layla K Oesper, Eric C Alexander, Jed C Yang, Blake S Howald 
CS 208: Computer Organization and Architecture
Computer processors are extraordinarily complex systems. The fact that they work at all, let alone as reliably as they do, is a monumental achievement of human collaboration. In this course, we will study the structure of computer processors, with attention to digital logic, assembly language, performance evaluation, computer arithmetic, data paths and control, pipelining, and memory hierarchies. Prerequisites: Computer Science 111 or instructor permission 6 credit; Formal or Statistical Reasoning; offered Winter 2018, Spring 2018 · Sherri L Goings 
CS 231: Computer Security
Hackers, phishers, and spammersat best they annoy us, at worst they disrupt communication systems, steal identities, bring down corporations, and compromise sensitive systems. In this course, we'll study various aspects of computer and network security, focusing mainly on the technical aspects as well as the social and cultural costs of providing (or not providing) security. Topics include cryptography, authentication and identification schemes, intrusion detection, viruses and worms, spam prevention, firewalls, denial of service, electronic commerce, privacy, and usability. Prerequisites: Computer Science 201 or 202 or 208 6 credit; Formal or Statistical Reasoning; offered Winter 2018 · Jeffrey R Ondich 
CS 252: Algorithms
A course on techniques used in the design and analysis of efficient algorithms. We will cover several major algorithmic design paradigms (greedy algorithms, dynamic programming, divide and conquer, and network flow). Along the way, we will explore the application of these techniques to a variety of domains (natural language processing, economics, computational biology, and data mining, for example). As time permits, we will include supplementary topics like randomized algorithms, advanced data structures, and amortized analysis. Prerequisites: Computer Science 201 and Computer Science 202 (Mathematics 236 will be accepted in lieu of Computer Science 202) 6 credit; Formal or Statistical Reasoning; offered Winter 2018, Spring 2018 · David LibenNowell, Layla K Oesper 
CS 254: Computability and Complexity
An introduction to the theory of computation. What problems can and cannot be solved efficiently by computers? What problems cannot be solved by computers, period? Topics include formal models of computation, including finitestate automata, pushdown automata, and Turing machines; formal languages, including regular expressions and contextfree grammars; computability and uncomputability; and computational complexity, particularly NPcompleteness. Prerequisites: Computer Science 111 and Computer Science 202 (Mathematics 236 will be accepted in lieu of Computer Science 202) 6 credit; Formal or Statistical Reasoning; offered Fall 2017, Winter 2018 · Jed C Yang 
CS 257: Software Design
It's easy to write a mediocre computer program, and lots of people do it. Good programs are quite a bit harder to write, and are correspondingly less common. In this course, we will study techniques, tools, and habits that will improve your chances of writing good software. While working on several mediumsized programming projects, we will investigate code construction techniques, debugging and profiling tools, testing methodologies, UML, principles of objectoriented design, design patterns, and user interface design. Prerequisites: Computer Science 201 or instructor permission 6 credit; Formal or Statistical Reasoning; offered Fall 2017, Winter 2018, Spring 2018 · Amy Csizmar Dalal, Jeffrey R Ondich 
CS 298: Reading and Analysis Associated with External Computing Experience
An independent study course intended for students who require Curricular Practical Training (CPT) or Optional Practical Training (OPT) to go with an external activity related to computer science (for example, an internship or an externship). The student will choose and read academic material relating to a practical experience (e.g., internship), and write a paper describing what the student learned from the reading, and how it related to the practical experience.
Prerequisites: Instructor's permission 1 credit; S/CR/NC; Does not fulfill a curricular exploration requirement; offered Fall 2017, Winter 2018 · Jeffrey R Ondich 
CS 321: Artificial Intelligence
How can we design computer systems with behavior that seems "intelligent?" This course will examine a number of different approaches to this question, including intelligent search computer game playing, automated logic, machine learning (including neural networks), and reasoning with uncertainty. The coursework is a mix of problem solving and computer programming based on the ideas that we discuss. Prerequisites: Computer Science 201. Additionally Computer Science 202 is strongly recommended. 6 credit; Formal or Statistical Reasoning; offered Winter 2018 · Blake S Howald 
CS 362: Computational Biology
Recent advances in highthroughput experimental techniques have revolutionized how biologists measure DNA, RNA and protein. The size and complexity of the resulting datasets have led to a new era where computational methods are essential to answering important biological questions. This course focuses on the process of transforming biological problems into well formed computational questions and the algorithms to solve them. Topics include approaches to sequence comparison and alignment; molecular evolution and phylogenetics; DNA/RNA sequencing and assembly; and specific disease applications including cancer genomics. Prerequisites: Computer Science 201 and Computer Science 202 (Mathematics 236 will be accepted in leiu of Computer Science 202) 6 credit; Formal or Statistical Reasoning; offered Winter 2018 · Layla K Oesper 
CS 400: Integrative Exercise
Beginning with the prototypes developed in the Senior Seminar, project teams will complete their project and present it to the department. Required of all senior majors. Prerequisites: Computer Science 399 3 credit; S/NC; offered Winter 2018 · Jeffrey R Ondich, David LibenNowell, Eric C Alexander, Amy Csizmar Dalal
Spring 2018

CS 102: Art, Interactivity, and Robotics
In this handson studio centered course, we'll explore and create interactive three dimensional art. Using basic construction techniques, microprocessors, and programming, this class brings together the fundamentals of computer science, sculpture, engineering, and aesthetic design. Students will engage the nutsandbolts of fabrication, learn to program computers, and study how robots think. Collaborative labs and individual projects will culminate in a campus wide exhibition. No prior building or programming experience is required.
Prerequisites: Not open to students who have taken IDSC 120, Studio Arts 120, Computer Science 201 or any course for which Computer Science 201 is a prerequisite 6 credit; Arts Practice; offered Spring 2018 · David R Musicant, Stephen Mohring 
CS 111: Introduction to Computer Science
This course will introduce you to computer programming and the design of algorithms. By writing programs to solve problems in areas such as image processing, text processing, and simple games, you will learn about recursive and iterative algorithms, complexity analysis, graphics, data representation, software engineering, and objectoriented design. No previous programming experience is necessary. Students who have received credit for Computer Science 201 or above are not eligible to enroll in Computer Science 111. Students may not simultaneously enroll for CS 108 and CS 111 in the same term. 6 credit; Formal or Statistical Reasoning, Quantitative Reasoning Encounter; offered Fall 2017, Winter 2018, Spring 2018 · David LibenNowell, Blake S Howald, Sherri L Goings, Layla K Oesper, Eric C Alexander, David R Musicant 
CS 201: Data Structures
Think back to your favorite assignment from Introduction to Computer Science. Did you ever get the feeling that "there has to be a better/smarter way to do this problem?" The Data Structures course is all about how to store information intelligently and access it efficiently. How can Google take your query, compare it to billions of web pages, and return the answer in less than one second? How can one store information so as to balance the competing needs for fast data retrieval and fast data modification? To help us answer questions like these, we will analyze and implement stacks, queues, trees, linked lists, graphs and hash tables. Students who have received credit for a course for which Computer Science 201 is a prerequisite are not eligible to enroll in Computer Science 201. Prerequisites: Computer Science 111 or instructor permission 6 credit; Formal or Statistical Reasoning, Quantitative Reasoning Encounter; offered Fall 2017, Winter 2018, Spring 2018 · Layla K Oesper, Eric C Alexander, Jed C Yang, Blake S Howald 
CS 202: Mathematics of Computer Science
This course introduces some of the formal tools of computer science, using a variety of applications as a vehicle. You'll learn how to encode data so that when you scratch the back of a DVD, it still plays just fine; how to distribute "shares" of your floor's PIN so that any five of you can withdraw money from the floor bank account (but no four of you can); how to play chess; and more. Topics that we'll explore along the way include: logic and proofs, number theory, elementary complexity theory and recurrence relations, basic probability, counting techniques, and graphs. Prerequisites: Computer Science 111 and Mathematics 111 or instructor permission 6 credit; Formal or Statistical Reasoning; offered Fall 2017, Spring 2018 · Eric C Alexander, David LibenNowell 
CS 208: Computer Organization and Architecture
Computer processors are extraordinarily complex systems. The fact that they work at all, let alone as reliably as they do, is a monumental achievement of human collaboration. In this course, we will study the structure of computer processors, with attention to digital logic, assembly language, performance evaluation, computer arithmetic, data paths and control, pipelining, and memory hierarchies. Prerequisites: Computer Science 111 or instructor permission 6 credit; Formal or Statistical Reasoning; offered Winter 2018, Spring 2018 · Sherri L Goings 
CS 251: Programming Languages: Design and Implementation
What makes a programming language like "Python" or like "Java?" This course will look past superficial properties (like indentation) and into the soul of programming languages. We will explore a variety of topics in programming language construction and design: syntax and semantics, mechanisms for parameter passing, typing, scoping, and control structures. Students will expand their programming experience to include other programming paradigms, including functional languages like Scheme and ML. Prerequisites: Computer Science 201 or instructor permission 6 credit; Formal or Statistical Reasoning; offered Fall 2017, Spring 2018 · Jed C Yang 
CS 252: Algorithms
A course on techniques used in the design and analysis of efficient algorithms. We will cover several major algorithmic design paradigms (greedy algorithms, dynamic programming, divide and conquer, and network flow). Along the way, we will explore the application of these techniques to a variety of domains (natural language processing, economics, computational biology, and data mining, for example). As time permits, we will include supplementary topics like randomized algorithms, advanced data structures, and amortized analysis. Prerequisites: Computer Science 201 and Computer Science 202 (Mathematics 236 will be accepted in lieu of Computer Science 202) 6 credit; Formal or Statistical Reasoning; offered Winter 2018, Spring 2018 · David LibenNowell, Layla K Oesper 
CS 257: Software Design
It's easy to write a mediocre computer program, and lots of people do it. Good programs are quite a bit harder to write, and are correspondingly less common. In this course, we will study techniques, tools, and habits that will improve your chances of writing good software. While working on several mediumsized programming projects, we will investigate code construction techniques, debugging and profiling tools, testing methodologies, UML, principles of objectoriented design, design patterns, and user interface design. Prerequisites: Computer Science 201 or instructor permission 6 credit; Formal or Statistical Reasoning; offered Fall 2017, Winter 2018, Spring 2018 · Amy Csizmar Dalal, Jeffrey R Ondich 
CS 331: Computer Networks
The Internet is composed of a large number of heterogeneous, independentlyoperating computer networks that work together to transport all sorts of data to points all over the world. The fact that it does this so well given its complexity is a minor miracle. In this class, we'll study the structure of these individual networks and of the Internet, and figure out how this "magic" takes place. Topics include TCP/IP, protocols and their implementations, routing, security, network architecture, DNS, peertopeer networking, and WiFi along with ethical and privacy issues. Prerequisites: Computer Science 201 or instructor permission 6 credit; Formal or Statistical Reasoning; offered Spring 2018 · Amy Csizmar Dalal 
CS 344: HumanComputer Interaction
The field of humancomputer interaction addresses two fundamental questions: how do people interact with technology, and how can technology enhance the human experience? In this course, we will explore technology through the lens of the end user: how can we design effective, aesthetically pleasing technology, particularly user interfaces, to satisfy user needs and improve the human condition? How do people react to technology and learn to use technology? What are the social, societal, health, and ethical implications of technology? The course will focus on design methodologies, techniques, and processes for developing, testing, and deploying user interfaces. Prerequisites: Computer Science 201 or instructor permission 6 credit; Formal or Statistical Reasoning, Quantitative Reasoning Encounter; offered Spring 2018 · Eric C Alexander 
CS 358: Quantum Computing
Quantum computing is a promising technology that may (or may not) revolutionize computer science over the next few decades. By exploiting quantum phenomena such as superposition and entanglement, quantum computers can solve problems in a fundamentally different way from that of conventional computers. This course surveys the computer science and mathematics of quantum algorithms, including Shor's and Grover's algorithms, error correction, and cryptography. No prior experience with quantum theory is needed.
Prerequisites: Computer Science 201, Mathematics 232, and Computer Science 202 (Mathematics 236 will be accepted in lieu of Computer Science 202) 6 credit; Formal or Statistical Reasoning; offered Spring 2018 · Josh Davis