Application of Data Structures Flashcards

1
Q

Structure of Data:

refers to the relationships among data elements

A

Logical structure

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2
Q

Structure of Data:

pertains to how data is stored in computer memory

A

Physical Structure

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3
Q

is described as a set of data elements with certain logical relationships, stored in computer memory with corresponding operations encapsulated

A

data structure

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4
Q

Basic Principles in data structure design

A

Problem Analysis
Preliminary Design
Attention to Extensibility
Consideration of time and space cost of algorithm

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5
Q

these structures include linear tables, stacks, and queues

A

Linear structures

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6
Q

these structures encompass trees, sets, and graphs

A

Nonlinear structures

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7
Q

A one-to-one relationship exists in the data elements of this structure

A

Linear structure

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8
Q

is described as a finite sequence of instructions, representing specific and limited operation steps taken to solve a particular problem.

A

algorithm

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9
Q

common storage
structures of different types of data structures

A
  • sequential storage structure
  • chain storage structure
  • hash storage structure
  • index storage structure
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10
Q

two traversal modes in graph

A

depth-first traversal
breadth-first traversal

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11
Q

Data elements stored one after another in contiguous memory

A

Sequential Storage Structure

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12
Q

Data elements linked via pointers, allowing dynamic allocation

A

Chain Storage Structure

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13
Q

Data elements stored based on hashed keys in a hash table

A

Hash Storage Structure

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14
Q

Maintains an index mapping keys to data element positions

A

Index Storage Structure

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15
Q

Traversal Modes:

It involves exploring a graph or tree by first visiting the starting node and then recursively visiting its adjacent nodes (children or neighbors) in depth, prioritizing exploration of deeper nodes before backtracking

A

Depth-First Traversal

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16
Q

Traversal Modes:

In this method, exploration begins at the starting node, and all adjacent nodes at the current level are visited before moving to the next level. It involves systematically visiting all nodes at the same level before progressing to deeper levels, ensuring a broad exploration of the graph or tree.

A

Breadth-First Traversal

17
Q

two algorithms for generating minimum spanning trees in graphs

A

Prim’s Algorithm
Kruskal’s Algorithm

18
Q

Algorithms:

based on selecting the smallest edge to form a collection

A

Prim’s Algorithm

19
Q

Algorithms:

based on selecting the smallest edge until a unified connected component is obtained

A

Kruskal’s Algorithm

20
Q

involves removing nodes with zero in-degree and their adjacent edges until either the process ends or only one loop remains. It is used to solve problems related to partial order and total order in directed acyclic graphs

A

Topological Sorting

21
Q

two ways of expressing graphs

A
  • adjacency matrix
  • adjacency list
22
Q

implies that all elements can be compared

A

Total order

23
Q

indicates that only some elements can be compared

A

Partial order

24
Q

explores all neighboring nodes at the current depth level before moving to the next depth level, similar to hierarchical traversal of a tree using queues

A

Breadth-first traversal

25
Q

explores as far as possible along each branch before backtracking, resembling preorder traversal of a tree

A

Depth-first traversal