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CS GRE

From dankwiki

Anything above a 800 (it's on a 200-990-point scale) seems pretty good. It appears that quality single-volume preparation materials cannot be had at any price. Perhaps one ought be written?

(This second link is pretty dubiously-formed; YMMV. Go to the GRE page, click on Subject Info details, click on Computer Science Dank 14:58, 30 July 2009 (UTC))

Subject Material

Area (outline taken from the ETS CS GRE page, 2009-07-30 1500 UTC) References
SOFTWARE SYSTEMS AND METHODOLOGY - 40%
Data Organization
Data types
Data structures and implementation techniques
Program control and structure
Iteration and recursion
Procedures, functions, methods, and exception handlers
Concurrency, communication, and synchronization
Programming languages and notation
Constructs for data organization and program control
Scope, binding, and parameter passing
Expression evaluation
Software engineering
Formal specifications and assertions
Verification techniques
Software development models, patterns, and tools
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

COMPUTER ORGANIZATION AND ARCHITECTURE — 15%

  • Digital logic design
    • Implementation of combinational and sequential circuits
    • Optimization and analysis
  • Processors and control units
    • Instruction sets
    • Computer arithmetic and number representation
    • Register and ALU organization
    • Data paths and control sequencing
  • Memories and their hierarchies
    • Performance, implementation, and management
    • Cache, main, and secondary storage
    • Virtual memory, paging, and segmentation
  • Networking and communications
    • Interconnect structures (e.g., buses, switches, routers)
    • I/O systems and protocols
    • Synchronization
  • High-performance architectures
    • Pipelining superscalar and out-of-order execution processors
    • Parallel and distributed architectures

THEORY AND MATHEMATICAL BACKGROUND — 40%

  • 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
  • Automata and language theory
    • Models of computation (finite automata, Turing machines)
    • Formal languages and grammars (regular and context free)
    • Decidability
  • Discrete structures
    • Mathematical logic
    • Elementary combinatorics and graph theory
    • Discrete probability, recurrence relations, and number theory

OTHER TOPICS — 5%

Example areas include numerical analysis, artificial intelligence, computer graphics, cryptography, security, and social issues.

Books used to prepare