Introduces the theoretical, structural and algorithmic foundations of computer science. Topics include: sets, relations, functions, recursive data structures, recursive functions, induction, structural induction, probability, logic, Boolean algebra, proving program correctness, and the lambda calculus. Concepts are reinforced in programming exercises in the laboratory.
Examines the hierarchical structure of computing systems, from digital logic and micro- programming through machine and assembly languages. Topics include the structure and workings of the central processor, instruction execution, memory and register organization, addressing schemes, input and output channels and control sequencing. The course includes a weekly hardware/software laboratory where digital logic is explored and assembly language programming projects are implemented.
Introduces the systematic study of algorithms and their analysis with regard to time and space complexity. Topics include divide-and-conquer, dynamic programming, greediness, randomization, upper and lower-bound analysis, and introduction to NP completeness. Emphasis is placed on general design and analysis techniques that underlie algorithmic paradigms. Builds a foundation for advanced work in computer science.