CS GRE

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?

• ETS Practice Booklet (PDF), from the Computer Science Exam page

(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))

• UCB notes from 2001
• GT notes from 2006

Books used to prepare

• Software Systems and Methodology
  • Peter Van Roy and Seif Haridi, Concepts, Techniques, and Models of Computer Programming, 1st Edition
  • Harold Abelson and Gerald Jay Sussman, Structure and Interpretation of Computer Programs, 2nd Edition
• Computer Organization and Architecture
  • John Hennessy and David Patterson, Computer Architecture: A Quantitative Approach, 4th Edition
• Theory and Mathematical Background
  • Thomas Cormen, Charles Leiserson and Ron Rivest, Introduction to Algorithms, 1st Edition
  • Michael Sipser, Introduction to the Theory of Computation, 1st Edition

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.