I. SOFTWARE SYSTEMS AND METHODOLOGY — 40%

A. Data organization
• Data types
• Data structures and implementation techniques

B. Program control and structure
• Iteration and recursion
• Procedures, functions, methods, and exception handlers
• Concurrency, communication, and synchronization

C. Programming languages and notation
• Constructs for data organization and program control
• Scope, binding, and parameter passing
• Expression evaluation

D. Software engineering
• Formal specifications and assertions
• Verification techniques
• Software development models, patterns, and tools

E. Systems
• Compilers, interpreters, and run-time systems
• Operating systems, including resource management and protection/security
• Networking, Internet, and distributed systems
• Databases
• System analysis and development tools

II. COMPUTER ORGANIZATION AND ARCHITECTURE — 15%

A. Digital logic design
• Implementation of combinational and sequential circuits
• Optimization and analysis

B. Processors and control units
• Instruction sets
• Computer arithmetic and number representation
• Register and ALU organization
• Data paths and control sequencing

C. Memories and their hierarchies
• Performance, implementation, and management
• Cache, main, and secondary storage
• Virtual memory, paging, and segmentation

D. Networking and communications
• Interconnect structures (e.g., buses, switches, routers)
• I/O systems and protocols
• Synchronization

E. High-performance architectures
• Pipelining superscalar and out-of-order execution processors
• Parallel and distributed architectures

III. THEORY AND MATHEMATICAL BACKGROUND — 40%

A. Algorithms and complexity
• Exact and asymptotic analysis of specific algorithms
• Algorithmic design techniques (e.g. greedy, dynamic programming, divide and conquer)
• Upper and lower bounds on the complexity of specific problems
• Computational complexity, including NP-completeness

B. Automata and language theory
• Models of computation (finite automata, Turing machines)
• Formal languages and grammars (regular and context free)
• Decidability

C. Discrete structures
• Mathematical logic
• Elementary combinatorics and graph theory
• Discrete probability, recurrence relations, and number theory

IV. OTHER TOPICS — 5%

Example areas include numerical analysis, artificial intelligence, computer graphics, cryptography, security, and social issues.
Note: Students are assumed to have a mathematical background in the areas of calculus and linear algebra as applied to computer science.