2015-2016 Computer Science Courses
Introduction to Web Programming
The focus of this course is on the selection and interconnection of components that make up a computer. There are two essential categories of components in modern computers: the hardware (the physical medium of computation) and the software (the instructions executed by the computer). As technology becomes more complex, the distinction between hardware and software blurs. We will study why this happens, as well as why hardware designers need to be concerned with the way software designers write programs and vice versa. Along the way, we will learn how computers work from higher-level programming languages such as Java, Python, and C down to the basic zeroes and ones of machine code. Topics include Boolean logic, circuit design, computer arithmetic, assembly and machine languages, memory hierarchies, and parallel processing. Special attention will be given to the ARM family of instruction—set architectures, now the world's most common, general-purpose microprocessors. Time permitting, we will investigate the relationship between energy consumption and the rise of multicore and mobile architectures. Permission of the instructor is required. Students should have at least one semester of programming experience, preferably in C, C++, Java, or Python.
Introduction to Computer Programming
This lecture presents a rigorous introduction to computer science and the art of computer programming, using the elegant, eminently practical, yet easy-to-learn programming language Python. We will learn the principles of problem solving with a computer while gaining the programming skills necessary for further study in the discipline. We will emphasize the power of abstraction, the theory of algorithms, and the benefits of clearly written, well-structured programs. Fundamental topics include: how computers represent and manipulate numbers, text and other data (such as images and sound); variables and symbolic abstraction; Boolean logic; conditional, iterative, and recursive computation; functional abstraction ("black boxes"); and standard data structures such as arrays, lists, and dictionaries. We will learn introductory computer graphics and how to process simple user interactions via mouse and keyboard. We will also consider the role of randomness in otherwise deterministic computation, basic sorting and searching algorithms, how programs can communicate across networks, and some principles of game design. Toward the end of the semester, we will investigate somewhat larger programming projects and discuss file processing, modules and data abstraction, and object-oriented concepts such as classes, methods, and inheritance. As we proceed, we will debate the relative merits of writing programs from scratch versus leveraging existing libraries of code. Discussion topics will also include the distinction between decidable and tractable problems, the relationship between programming and artificial intellgence, the importance of algorithmic efficiency to computer security, Moore's Law and its impact on the evolution of programming languages and programming style. Weekly hands-on laboratory sessions will reinforce the programming concepts covered in class.
From Facebook, Twitter, and YikYak to massively multiplayer online games, to the Internet of Things, and to disruptive technologies ranging from Bitcoin to Uber, computer networks play an ever-increasing role in our daily lives. Where may this phenomenon be taking us in the immediate and not-so-immediate future? Is there (or should there be) anything we can (or should) do about it? The miniaturization of electronic computers and the resulting increase in computing power, decrease in short-term cost to harness that power, and ubiquity of computer networks bring people and places together, making distances formerly thought of as insurmountable ever more trivial. With the advent of gigabit fiber-optic networks, smart phones, and wearable computers, information of all kinds can flow, in an instant, between people and objects around the world and back again. In many ways, the plethora of smaller, cheaper, faster networked devices improves our quality of life; but we will also consider the dark side of a highly connected society: the more smart phones, the more workaholics; the more text messages and e-mails exchanged, the less privacy; the greater reach of the Internet, the more piracy, spam, and pornography. The nature of a course entitled Digital Zeitgeist is to move with the times, and those times move ever more rapidly. So even this description might seem outdated by the time you read it. Never fear, we will steer our discussion to the “bleeding edge,” as necessary. Consider these news stories (to name but a few) that would not have made it into this description were it written only a year earlier: the Gamergate controversy, “Citizen Four” (and its adoration), the Sony hack, the trial and conviction of the Silk Road founder, and the arrival of the Apple Watch. This is not a technical course, although at times we will discuss some details that lie behind certain crucial technologies—in particular, the Internet and the World Wide Web.
Data Structures and Algorithms
In this course, we will study a variety of data structures and algorithms that are important for the design of sophisticated computer programs, along with techniques for managing program complexity. We will use Java—a strongly typed, object-oriented programming language—throughout the course. Topics covered will include types and polymorphism, arrays, linked lists, stacks, queues, priority queues, heaps, dictionaries, balanced trees, and graphs, along with several important algorithms for manipulating these structures. We will also study techniques for analyzing the efficiency of algorithms. The central theme tying all of these topics together is the idea of abstraction and the related notions of information hiding and encapsulation, which we will emphasize throughout the course. Weekly lab sessions will reinforce the concepts covered in class through extensive hands-on practice at the computer. Students should have at least one semester of programming experience in an object-oriented language such as Python, Java, or C++.
Principles of Programming Languages
This course explores the principles of programming language design through the study and implementation of computer programs called interpreters, which process other programs as input. A famous computer scientist once remarked that if you don't understand interpreters, you can still write programs and even be a competent programmer; but you can't be a master. We will begin by studying functional programming, using the strangely beautiful and recursive programming language Scheme. After getting comfortable with Scheme and recursion, we will see how to design our own languages by starting from a high-level description and systematically deriving a low-level implementation through the application of a series of program transformations. Along the way, we will become acquainted with the lambda calculus (the basis of modern programming language theory), scoping mechanisms, continuations, lazy and nondeterministic evaluation, and other topics as time permits. We will use Scheme as our “meta-language” for exploring these issues in a precise, analytical way, similar to the way in which mathematics is used to describe phenomena in the natural sciences. Our great advantage over mathematics, however, is that we can test our ideas about languages, expressed in the form of interpreters, by directly executing them on the computer.
First-Year Studies: Achilles, the Tortoise, and the Mystery of the Undecidable
In this course, we will take an extended journey through Douglas Hofstadter’s Pulitzer Prize-winning book, Gödel, Escher, Bach, which has been called “an entire humanistic education between the covers of a single book.” The key question at the heart of the book is: How can minds possibly arise from mere matter? Few people would claim that individual neurons in a brain are “conscious” in anything like the normal sense in which we experience consciousness. Yet self-awareness somehow emerges out of a myriad of neuronal firings and molecular interactions. How can individually meaningless physical events in a brain, even vast numbers of them, give rise to meaningful awareness, to a sense of self? And could we duplicate such a process in a machine? Considering these questions will lead us to explore a wide range of ideas, from the foundations of mathematics and computer science to molecular biology, art, and music to the research frontiers of modern-day cognitive science and neuroscience. Along the way, we will closely examine Gödel's incompleteness theorem, mathematical logic and formal systems, the limits of computation, and the future prospects for artificial intelligence.