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Data Structure and Algorithm > Lesson1 > Flashcards

Lesson1 Flashcards

1
Q

These are the programmatic way of storing data so that data can e used efficiently.

A

Data Structures

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2
Q

This is the systematic way to organize data in order to use it efficiently.

A

Data Structure

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3
Q

Each data structure has this. It represents the set of operations that a data structure supports.

A

Interface

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4
Q

It only provides the list of supported operations, type of parameters they can accept and return type of these operations

A

Interface

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5
Q

This provides the internal representation of a data structure.

A

Implementation

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6
Q

It also provides the definition of the algorithms used in the operations of the data structure

A

Implementation

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7
Q

True or False:
Data structures are used to implement the physical forms of abstract data types.

A

True

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8
Q

Data Structures are a crucial part of designing what?

A

Efficient Software

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9
Q

True or False:
Data Structure play a critical role in algorithm design and how those algorithms are used within computer programs

A

True

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10
Q

What are the example of early programming languages

A

Fortran
C
C++

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11
Q

These enabled programmers to define their own data structures

A

Early Programming Languages

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12
Q

They uses algorithms that are tightly coupled with the data structure

A

Software Engineers

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13
Q

What are Algorithms that are tightly coupled with the data structure

A

Lists
Queues
Mappings

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14
Q

This is an index of those records using a data strucutre

A

Binary Tree

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15
Q

Data structures are used for efficient data persistence, such as specifying the collection of attributes and corresponding structures used to store records in a database management system.

A

Storing Data

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16
Q

Core operating system (OS) resources and services are enabled through the use of data structures such as linked lists for memory allocation, file directory management and file structure trees, as well as process scheduling queues.

A

Managing Resources and Services

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17
Q

Data structures define the organization of information
shared between applications, such as TCP/IP packets

A

Data Exchange

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18
Q

Data structures such as binary search trees – also known as an ordered or sorted binary tree – provide efficient methods of sorting objects, such as character strings used as tags. With data structures such as priority queues, programmers can manage items organized according to a specific priority.

A

Ordering and Sorting

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19
Q

Even more sophisticated data structures such as B-trees are used to index objects, such as those stored in a database.

A

Indexing

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20
Q

Indexes created using binary search trees, B-trees or hash tables speed the ability to find a specific sought-after item.

A

Searching

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21
Q

Big data applications use data structures for allocating and managing data storage across distributed storage locations, ensuring scalability and performance. Certain big data programming environments – such as Apache Spark – provide data structures that mirror the underlying structure of database records to simplify querying.

A

Scalability

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22
Q

What are three characteristics of data structures?

A

Linear or Non-Linear
Homogeneous or Heterogeneous
Static or Dynamic

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23
Q

This characteristic describes whether the data items are arranged in sequential order, such as with an array, or in an unordered sequence, such as with a graph.

A

Linear or Non-linear

24
Q

This characteristic describes whether all data items in a given repository are of the same type. One example is a collection of elements in an array, or of various types, such as an abstract data type defined as a structure in C or a class specification in Java

A

Homogeneous or Heterogeneous

25
Q

This characteristic describes how the data structures are compiled. Static data structures have fixed sizes, structures and memory locations at compile time. Dynamic data structures have sizes, structures and memory locations that can shrink or expand, depending on the use.

A

Static or Dynamic

26
Q

This talks about Consider an inventory of 1 million(106) items of a store. If the application is to search an item, it has to search an item in 1 million(106) items every time slowing down the search. As data grows, search will become slower

A

Data Search

27
Q

This talks about ____ ____ although being very high, falls limited if the data grows to billion records.

A

Processor Speed

28
Q

This talks about thousands of users can search data simultaneously on
a web server, even the fast server fails while searching the data.

A

Multiple Requests

29
Q

What are need for Data Structure

A

Data Search
Processor Speed
Multiple Request

30
Q

This is the scenario where a particular data structure operation takes maximum time it can take. If an operation’s worst case time is ƒ(n) then this operation will not take more than ƒ(n) time where ƒ(n) represents function of n.

A

Worst Case

31
Q

This is the scenario depicting the average execution time of an operation of a data structure. If an operation takes ƒ(n) time in execution, then m operations will take mƒ(n) time.

A

Average Case

32
Q

This is the scenario depicting the least possible execution time of an operation of a data structure. If an operation takes ƒ(n) time in execution, then the actual operation may take time as the random number which would be maximum as ƒ(n).

A

Best Case

33
Q

These are values or set of values

A

Data

34
Q

This refers to single unit of values

A

Data Item

35
Q

This talks about data items that are divided into sub items

A

Group items

36
Q

This talks about data items that cannot be divided

A

Elementary Items

37
Q

This is that which contains certain attributes

A

Entity

38
Q

These are entities of similar attributes form an entity set

A

Entity Set

39
Q

This is a single elementary unit of information representing an attribute of an entity

A

Field

40
Q

This is a collection of field values of a given entity

A

RecordT

41
Q

his is a collection of records of the entities in a given entity set

A

File

42
Q

This is a structure of fixed-size, which can hold items of the same data type.

A

Array

43
Q

This is a sequential structure that consists of a sequence of items in linear order which are linked to each other.

A

Linked List

44
Q

This can be commonly found in many programming
languages

A

Stack

45
Q

What is the meaning of LIFO

A

Last In First Out

46
Q

This can be commonly found in many programming
languages.

A

Queues

47
Q

What is the meaning of FIFO

A

First in First Out

48
Q

This is a data structure that stores values which have keys associated with each of them.

A

Hash Table

49
Q

This is a hierarchical structure where data is organized hierarchically and are linked together.

A

Tree

50
Q

This is used to implement expression parsers and expression solvers

A

Binary Trees

51
Q

This is used in many search applications where data are constantly entering and leaving

A

Binary Search Tree

52
Q

This is used by JVM to store Java Objects

A

Heaps

53
Q

This is used in wireless networking

A

Treaps

54
Q

This is a special case of a binary tree where the parent nodes are compared to their children with their values and are arranged accordingly

A

Heaps

55
Q
A

Data Structure and Algorithm (1 decks)

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