An introduction to techniques and building blocks for organizing large programs. Topics include: modules, abstract data types, recursion, algorithmic efficiency, and the use and implementation of standard data structures and algorithms, such as lists, trees, graphs, stacks, queues, priority queues, tables, sorting, and searching. Students become familiar with these concepts through weekly programming assignments using the Java programming language.

An introduction to the design and analysis of fundamental algorithms. General techniques covered: divide-and-conquer algorithms, dynamic programming, greediness, probabilistic algorithms. Topics include: sorting, searching, graph algorithms, compression, cryptography, computational geometry, and NP-completeness.

This course offers an introduction to the theory of computation. Topics include languages, regular expressions, finite automata, grammars, pushdown automata, and Turing machines. The first part of the course covers the Chomsky hierarchy of languages and their associated computational models. The second part of the course focuses on decidability issues and unsolvable problems. The final part of the course investigates complexity theory.

This course examines how computers run programs, introducing key software and hardware abstractions and implementations between programming languages and transistors. The course traces representation and translation of data and programs through three broad topics in computer systems: computer hardware implementation, including digital logic, computer arithmetic, and machine organization; the hardware-software interface, including instruction set architecture, assembly code, and the C programming language; and abstractions for practical systems, including the physical memory hierarchy, the operating system process model, virtual memory, and memory management. Students complete extensive hands-on projects in hardware and software systems. Students are required to attend one three-hour laboratory weekly.

Combinatorics is the art of counting possibilities: for instance, how many different ways are there to distribute 20 apples to 10 kids? Graph theory is the study of connected networks of objects. Both have important applications to many areas of mathematics and computer science. The course will be taught emphasizing creative problem-solving as well as methods of proof, such as proof by contradiction and induction. Topics include: selections and arrangements, generating functions, recurrence relations, graph coloring, Hamiltonian and Eulerian circuits, and trees.