Computer Science Test
Important: The last administration of the GRE® Computer Science Test will be in April 2013. The test will be discontinued after the April 2013 administration. Scores will be reportable for five years.
All other GRE Subject Tests will continue to be administered.
- 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
- Compilers, interpreters and run-time systems
- Operating systems, including resource management and protection/security
- Networking, Internet and distributed systems
- 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
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)
C. Discrete structures
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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