GRE Subject Computer Science
- Tuesday, June 14, 2011, 8:00
- GRE, Test Prep
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Download the Computer Science Practice Booklet (PDF)
- The test consists of approximately 70 multiple-choice questions, some of which are grouped in sets and based on such materials as diagrams, graphs and program fragments.
- The approximate distribution of questions in each edition of the test according to content categories is indicated by the following outline.
- The percentages given are approximate; actual percentages will vary slightly from one edition of the test to another.
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.
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