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 object-oriented 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.

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.

Are you curious what’s really going on when a computer runs your code? In this course we will demystify the machine and the tools that we use to program it. Our broad survey of how computer systems execute programs, store information, and communicate will focus on the hardware/software interface, including data representation, instruction set architecture, the C programming language, memory management, and the operating system process model.

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.

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.

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 finite-state automata, pushdown automata, and Turing machines; formal languages, including regular expressions and context-free grammars; computability and uncomputability; and computational complexity, particularly NP-completeness.

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 medium-sized programming projects, we will investigate code construction techniques, debugging and profiling tools, testing methodologies, UML, principles of object-oriented design, design patterns, and user interface design.

As part of their senior capstone experience, majors will work together in teams (typically four to seven students per team) on faculty-specified topics to design and implement the first stage of a project. Required of all senior majors.

Beginning with the prototypes developed in the Senior Seminar (CS 399), project teams will complete their project and present it to the department. Required of all senior majors. Each CS 400 is paired with a particular section of CS 399, and the prerequisite for CS 400 must be filled by satisfactory completion of that CS 399.

An introduction to the differential and integral calculus. Derivatives, antiderivatives, the definite integral, applications, and the fundamental theorem of calculus.