Difference between revisions of "2022 Paper 1 Revision Quiz"
(→Abstract Data Types & Dynamic vs Static) |
|||
(7 intermediate revisions by the same user not shown) | |||
Line 101: | Line 101: | ||
<quiz display=simple> | <quiz display=simple> | ||
+ | {When considering arrays, which of the following are correct | ||
+ | |type="[]"} | ||
+ | +You must declare a size when creating the array | ||
+ | ||Correct | ||
+ | -You don't need to specify a size when creating an array | ||
+ | ||Incorrect | ||
+ | +The memory for the entire structure is allocated when it is created | ||
+ | ||Correct | ||
+ | -Only the initial memory is allocated when creating, the rest is allocated when we add items | ||
+ | ||Incorrect | ||
+ | |||
+ | {When using arrays the square brackets [] : | ||
+ | |type="()"} | ||
+ | -Are used to access the whole array | ||
+ | ||Incorrect | ||
+ | -Contain the data value to look up in the array | ||
+ | ||Incorrect | ||
+ | +Are used to access a specific element in the array | ||
+ | ||Correct | ||
+ | -Contain the data value store in the array | ||
+ | ||Incorrect | ||
+ | |||
+ | {An array can be of any data type or class. | ||
+ | |type="()"} | ||
+ | +True | ||
+ | ||Correct | ||
+ | -False | ||
+ | ||Incorrect | ||
+ | |||
+ | {A 2D array can still only be of one data type or class. | ||
+ | |type="()"} | ||
+ | +True | ||
+ | ||Correct | ||
+ | -False | ||
+ | ||Incorrect | ||
+ | |||
+ | {An Array is a: | ||
+ | |type="()"} | ||
+ | -Abstract Data Structure | ||
+ | ||Incorrect | ||
+ | -Dynamic Data Structure | ||
+ | ||Incorrect | ||
+ | +Static Data Structure | ||
+ | ||Correct | ||
+ | -Strong Data Structure | ||
+ | ||Incorrect | ||
</quiz> | </quiz> | ||
=Abstract Data Types & Dynamic vs Static= | =Abstract Data Types & Dynamic vs Static= | ||
<quiz display=simple> | <quiz display=simple> | ||
+ | |||
+ | {A Abstract Data type is: | ||
+ | |type="[]"} | ||
+ | -Defined by how it is implemented | ||
+ | ||Incorrect | ||
+ | +Not defined by how it is implemented | ||
+ | ||Correct | ||
+ | +Can be implemented in many ways | ||
+ | ||Correct | ||
+ | -Can only be implement in one way | ||
+ | ||Incorrect | ||
+ | |||
+ | {When considering dynamic structures, which of the following are correct | ||
+ | |type="[]"} | ||
+ | -You must declare a size when creating the structure | ||
+ | ||incorrect | ||
+ | -You don't need to specify a size when creating the structure | ||
+ | ||Correct | ||
+ | -The memory for the entire structure is allocated when it is created | ||
+ | ||Incorrect | ||
+ | +Only the initial memory is allocated when creating, the rest is allocated when we add items | ||
+ | ||Correct | ||
+ | |||
+ | {The benefits of static structures are: | ||
+ | |type="[]"} | ||
+ | -Makes the most efficient use of memory because it only allocates what is needed | ||
+ | ||Incorrect | ||
+ | +Memory allocation is fixed so adding and removing data items should be straight forward | ||
+ | ||Correct | ||
+ | +The size of the structure is known so you don't need to calculate the size of the structure | ||
+ | ||Correct | ||
+ | -Are very flexible and items can be added and removed without worrying about where they are in the structure | ||
+ | ||Incorrect | ||
+ | |||
+ | {The drawbacks of a static structure are: | ||
+ | |type="()"} | ||
+ | -It is possible for the structure to overflow or underflow | ||
+ | ||Incorrect | ||
+ | +Can be very inefficient with memory because memory is allocated whether it is needed or not | ||
+ | ||Correct | ||
+ | -The memory allocated will be fragmented so will take longer to read | ||
+ | ||Incorrect | ||
+ | - You might need to code basic function to get the size or number of items stored | ||
+ | ||Incorrect | ||
+ | |||
+ | {The benefits of dynamic structures are: | ||
+ | |type="[]"} | ||
+ | +Makes the most efficient use of memory because it only allocates what is needed | ||
+ | ||Correct | ||
+ | -Memory allocation is fixed so adding and removing data items should be straight forward | ||
+ | ||Incorrect | ||
+ | -The size of the structure is known so you don't need to calculate the size of the structure | ||
+ | ||Incorrect | ||
+ | +Are very flexible and items can be added and removed without worrying about where they are in the structure | ||
+ | ||Correct | ||
+ | |||
+ | {The drawbacks of a dynamic structure are: | ||
+ | |type="[]"} | ||
+ | +It is possible for the structure to overflow or underflow | ||
+ | ||Correct | ||
+ | -Can be very inefficient with memory because memory is allocated whether it is needed or not | ||
+ | ||Incorrect | ||
+ | +The memory allocated will be fragmented so will take longer to read | ||
+ | ||Correct | ||
+ | + You might need to code basic function to get the size or number of items stored | ||
+ | ||Correct | ||
</quiz> | </quiz> | ||
Line 121: | Line 233: | ||
A new item must be added to the { back|rear|tail } of the queue. | A new item must be added to the { back|rear|tail } of the queue. | ||
You must remove the item at the { front|head } of the queue. | You must remove the item at the { front|head } of the queue. | ||
+ | |||
+ | {In a Linear queue, the front of the queue will move further back as items are taken from the front of the queue. | ||
+ | |type="()"} | ||
+ | +True | ||
+ | ||Correct | ||
+ | -False | ||
+ | ||Incorrect | ||
+ | |||
+ | {In a Linear queue, when an item is removed from the front of the queue the remaining items are moved forward. | ||
+ | |type="()"} | ||
+ | -True | ||
+ | ||Incorrect | ||
+ | +False | ||
+ | ||Correct | ||
+ | |||
+ | {A circular queue works by using pointers. The front pointer will point to: | ||
+ | |type="()"} | ||
+ | -The back of the queue | ||
+ | ||Incorrect | ||
+ | -The location for the next item onto the queue | ||
+ | ||Incorrect | ||
+ | +The first item in the queue | ||
+ | ||Correct | ||
+ | -The second item in the queue | ||
+ | ||Incorrect | ||
+ | |||
+ | {A circular queue works by using pointers. The rear pointer will point to: | ||
+ | |type="()"} | ||
+ | +The back of the queue | ||
+ | ||Correct | ||
+ | -The location for the next item onto the queue | ||
+ | ||Incorrect | ||
+ | -The first item in the queue | ||
+ | ||Incorrect | ||
+ | -The second item in the queue | ||
+ | ||Incorrect | ||
+ | |||
+ | {To make a circular queue you must reset either pointer back to 1 when: | ||
+ | |type="()"} | ||
+ | -Number of Items = Max Queue Size | ||
+ | ||Incorrect | ||
+ | -Number of Items = 0 | ||
+ | ||Incorrect | ||
+ | +When the Pointer Value = Max Queue Size | ||
+ | ||Correct | ||
+ | |||
+ | {in a circular queue you must test for empty by: | ||
+ | |type="()"} | ||
+ | -Number of Items = Max Queue Size | ||
+ | ||Incorrect | ||
+ | +Number of Items = 0 | ||
+ | ||Correct | ||
+ | -When the Pointer Value = Max Queue Size | ||
+ | ||Incorrect | ||
+ | |||
+ | {in a circular queue you must test for full by: | ||
+ | |type="()"} | ||
+ | +Number of Items = Max Queue Size | ||
+ | ||Correct | ||
+ | -Number of Items = 0 | ||
+ | ||Incorrect | ||
+ | -When the Pointer Value = Max Queue Size | ||
+ | ||Incorrect | ||
</quiz> | </quiz> | ||
Line 369: | Line 544: | ||
<quiz display=simple> | <quiz display=simple> | ||
+ | {Depth First Traversal uses a: | ||
+ | |type="()"} | ||
+ | -Queue | ||
+ | ||Incorrect | ||
+ | +Stack | ||
+ | ||Correct | ||
+ | -List | ||
+ | ||Incorrect | ||
+ | -Dictionary | ||
+ | ||Incorrect | ||
+ | |||
+ | {Breadth First Traversal uses a: | ||
+ | |type="()"} | ||
+ | +Queue | ||
+ | ||Correct | ||
+ | -Stack | ||
+ | ||Inorrect | ||
+ | -List | ||
+ | ||Incorrect | ||
+ | -Dictionary | ||
+ | ||Incorrect | ||
+ | |||
+ | {Complete the following: | ||
+ | |type="{}"} | ||
+ | For Depth First & Breadth First traversals it is important to know when a node has been { discovered }. | ||
+ | When you evaluate a node the { neighbours } of the current node will be add to the Stack or Queue. | ||
+ | It is important to also record when you have { fully|completely } explored the current node. | ||
</quiz> | </quiz> | ||
Latest revision as of 16:58, 3 June 2022
Contents
Recursion
Arrays
Abstract Data Types & Dynamic vs Static
Queues
Stacks
Graphs
Trees
Graph Traversal
Searching Algorithms
Sorting Algorithms
Optimisation Algorithms
Order of Complexity