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(Data Structures, Algorithms, and Complexity)
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== Data Structures, Algorithms, and Complexity ==
== Data Structures, Algorithms, and Complexity ==
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*[[/index.php/Memory_Allocation|Memory Allocation]]  
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*[[Memory Allocation|Memory Allocation]]  
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*[[/index.php/Asymptotic_Measures|Asymptotic Measures]]  
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*[[Asymptotic Measures|Asymptotic Measures]]  
*Algorithms
*Algorithms
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#Searching
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#[[Searching|Seaching]]  
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#Sorting
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#[[Sorting|Sorting]]
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*[[/index.php/Primitive_Structures|Primitive Structures]]  
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*[[Abstract Data Types|Abstract Data Types]]  
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*Unstructured Collections
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#Sets
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#Maps and Dictionaries
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#Hash Tables
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*[[Primitive Structures|Primitive Structures]]
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*[[Concept of an Element (Node)|Concept of an Element (Node)]]
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*[[Abstract Data Types|Abstract Data Types]]
*Linear Structures
*Linear Structures
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#Lists
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#[[Lists|Lists]]
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#Stacks
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#[[Stacks|Stacks]]
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#Queues
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#[[Queues|Queues]]
*Trees
*Trees
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#Binary Trees
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#[[Binary Trees|Binary Trees]]
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#Binary Search Trees
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#Binary Search Trees  
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#AVL Trees
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#AVL Trees  
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#Red-Black Trees
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#Red-Black Trees  
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#Splay Trees
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#Splay Trees  
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#Heaps
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#Heaps  
#B-Trees
#B-Trees
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*Graphs
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*Graphs  
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*UnOrdered Collections
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#Sets
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#Maps and Dictionaries
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#Hash Tables
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Revision as of 14:31, 24 March 2009

Introduction (needs to be written)

Data Structures

A data structure is a means of organizing data in a computer’s memory to try to optimize either the memory needed or the time to access the data. This brings up the classic trade-off in Computer Science: the trade-off between Time and Space. In most situations today, it seems that we are primarily interested in minimizing the Time aspect. But, given smaller and smaller devices that increasingly do more (think of the evolution of the cell phone), minimizing the Space aspect can be important also.

There is sometimes a difference made between a data structure and an abstract data type (ADT). An ADT describes the public interface of a data structure: the type of data and the valid operations on the data. An ADT, however, does not consider an implementation, and this is the essential difference.

Data Structures, Algorithms, and Complexity

  1. Seaching
  2. Sorting
  1. Lists
  2. Stacks
  3. Queues
  • Trees
  1. Binary Trees
  2. Binary Search Trees
  3. AVL Trees
  4. Red-Black Trees
  5. Splay Trees
  6. Heaps
  7. B-Trees
  • Graphs
  • UnOrdered Collections
  1. Sets
  2. Maps and Dictionaries
  3. Hash Tables


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