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CS GRE: Difference between revisions

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**'''CLR''': Thomas Cormen, Charles Leiserson and Ron Rivest, ''[http://www.amazon.com/Introduction-Algorithms-Second-Thomas-Cormen/dp/0262032937 Introduction to Algorithms]''. First edition, 19th printing.
**'''CLR''': Thomas Cormen, Charles Leiserson and Ron Rivest, ''[http://www.amazon.com/Introduction-Algorithms-Second-Thomas-Cormen/dp/0262032937 Introduction to Algorithms]''. First edition, 19th printing.
**'''SIPSER''': Michael Sipser, ''[http://www.amazon.com/Introduction-Theory-Computation-Michael-Sipser/dp/053494728X Introduction to the Theory of Computation]''. First edition, first printing.
**'''SIPSER''': Michael Sipser, ''[http://www.amazon.com/Introduction-Theory-Computation-Michael-Sipser/dp/053494728X Introduction to the Theory of Computation]''. First edition, first printing.
**'''CINP''': Michael Garey and David Johnson, ''[http://www.amazon.com/Computers-Intractability-NP-Completeness-Mathematical-Sciences/dp/0716710455 Computers and Intractability: A Guide to the Theory of NP-Completeness]''. First edition, 26th printing.
**'''KNUTH2''': Donald Knuth, ''[http://www.amazon.com/gp/product/0201896842 The Art of Computer Programming, Vol. 2: Seminumerical Algorithms]''. Third edition, first printing.
**'''KNUTH2''': Donald Knuth, ''[http://www.amazon.com/gp/product/0201896842 The Art of Computer Programming, Vol. 2: Seminumerical Algorithms]''. Third edition, first printing.
Further texts are listed in the applicable sections below.
Further texts are listed in the applicable sections below.
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|-
|-
| Computational complexity, including NP-completeness
| Computational complexity, including NP-completeness
*: ''[http://www.amazon.com/Methods-Verification-Specification-Prentice-Hall-Software/dp/0133288072/ Formal Methods of Program Verification and Specification]''
* Garey and Johnson, ''[http://www.amazon.com/Computers-Intractability-NP-Completeness-Mathematical-Sciences/dp/0716710455 Computers and Intractability: A Guide to the Theory of NP-Completeness]''
| '''SIPSER''' 7, 8
| '''SIPSER''' 7, 8
|-
|-
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|-
|-
| Models of computation (finite automata, Turing machines)
| Models of computation (finite automata, Turing machines)
* Hopcroft and Ullman, ''[http://www.amazon.com/Introduction-Automata-Theory-Languages-Computation/dp/0201441241 Introduction to Automata Theory, Languages and Computation]''
| '''SIPSER''' 1, 3
| '''SIPSER''' 1, 3
|-
|-
| Formal languages and grammars (regular and context free)
| Formal languages and grammars (regular and context free)
* Gurari, ''[http://www.cse.ohio-state.edu/~gurari/theory-bk/theory-bk.html An Introduction to the Theory of Computation]''
| '''SIPSER''' 2
| '''SIPSER''' 2
|-
|-

Revision as of 09:54, 7 September 2009

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))

<countdown time="10/10/2009 8:30 AM UTC-0500"><D> days, <H> hours, <M> minutes, seconds until the 2009-10-10 CS GRE</countdown>

Books we're using for general preparation

Further texts are listed in the applicable sections below.

Online courseware

Subject Material

Outline taken from the ETS CS GRE page, 2009-07-30 1500 UTC)

Area vocabulary listings follow each area in small, italicized, bolded text References and Supplements
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 general- vs special-purpose registers, condition word, load-store vs register-memory architectures, addressing alignment, register vs immediate vs displacement vs indexed etc addressing, instruction sizes, control flow instructions, opcode expansion, reduced vs complex sets H&P4 1.3, Appx A
Computer arithmetic and number representation signed magnitude, one's complement, signed zeros, two's complement, binary coded decimal, IEEE 754, biased representation, denormalization, positive and negative infinity, NaN, nearest rounding, directed rounding, overflow, underflow, carry indicator, arbitrary precision
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 Big-O (<math>O(f())</math>), Big-Theta (<math>\Theta(f())</math>), Big-Omega (<math>\Omega(f())</math>), Little-O (<math>o(f()))</math>), Little-Omega (<math>\omega(f())</math>) Asymptotic Notation and Recurrences lecture from MIT's 6.046J
Algorithmic design techniques (e.g. greedy, dynamic programming, divide and conquer) Divide+Conquer, Dynamic Programming and Greedy algorithm lectures from MIT's 6.046J
Upper and lower bounds on the complexity of specific problems
Computational complexity, including NP-completeness SIPSER 7, 8
Automata and language theory
Models of computation (finite automata, Turing machines) SIPSER 1, 3
Formal languages and grammars (regular and context free) SIPSER 2
Decidability SIPSER 4, 5, 6.2, 6.3
Discrete structures
Mathematical logic
Elementary combinatorics and graph theory connected, connectivity, directed (digraph), eccentricity, circumference, acyclic, path, weighted, subgraph, expander, hypergraph, multigraph, tournament, complete (<math>K_n</math>), scorpion, set cover, vertex cover
Discrete probability, recurrence relations, and number theory
OTHER TOPICS - 5% "Example areas include..."
Numerical analysis
Artificial intelligence
Computer graphics
Cryptography
Security
...and social issues.