WGU C949 STUDY GUIDE
Array -answer A data structure that stores an ordered list of items, with each item is
directly accessible by a positional index.
Linked List -answer A data structure that stores ordered list of items in nodes, where
each node stores data and has a pointer to the next node.
Bianary Search Tree -answer A data structure in which each node stores data and has up
to two children, known as a left child and a right child.
Hash Table -answer A data structure that stores unordered items by mapping (or hashing)
each item to a location in an array (or vector).
Hashing -answer mapping each item to a location in an array (in a hash table).
Chaining -answer handles hash table collisions by using a list for each bucket, where each
list may store multiple items that map to the same bucket.
Hash key -answer value used to map an index
bucket -answer each array element in a hash table
ie A 100 elements hash table has 100 buckets
modulo hash function -answer computes a bucket index from the items key.
It will map (num_keys / num_buckets) keys to each bucket.
,ie... keys range 0 to 49 will have 5 keys per bucket.
= 5
hash table searching -answer Hash tables support fast search, insert, and remove.
Requires on average O(1)
Linear search requires O(N)
modulo operator % -answer common has function uses this. which computes the integer
remainder when dividing two numbers.
Ex: For a 20 element hash table, a hash function of key % 20 will map keys to bucket indices 0 to
19.
Max-Heap -answer A binary tree that maintains the simple property that a node's key is
greater than or equal to the node's childrens' keys. (Actually, a max-heap may be any tree, but is
commonly a binary tree).
*a max-heap's root always has the maximum key in the entire tree.
Heap storage -answer Heaps are typically stored using arrays. Given a tree representation
of a heap, the heap's array form is produced by traversing the tree's levels from left to right and
top to bottom. The root node is always the entry at index 0 in the array, the root's left child is
the entry at index 1, the root's right child is the entry at index 2, and so on.
Max-heap insert -answer An insert into a max-heap starts by inserting the node in the
tree's last level, and then swapping the node with its parent until no max-heap property
violation occurs.
The upward movement of a node in a max-heap is sometime called percolating.
,Complexity O(logN)
Max-heap remove -answer Always a removal of the root, and is done by replacing the
root with the last level's last node, and swapping that node with its greatest child until no max-
heap property violation occurs.
Complexity O(logN)
Percolating -answer The upward movement of a node in a max-heap
Min-Heap -answer Similar to a max-heap, but a node's key is less than or equal to its
children's keys.
Heap - Parent and child indices -answer Because heaps are not implemented with node
structures and parent/child pointers, traversing from a node to parent or child nodes requires
referring to nodes by index. The table below shows parent and child index formulas for a heap.
ie
1) parent index for node at index 12? 5
*** ((12-1) // 2) = 5 or 12 //2 -1 = 5
2) child indices for a node at index 6? 13 & 14
*** 2 * 6 + 1 = 13 and 2 * 6 + 2 = 14
**Double# and add 1, double# and add 2
Node index Parent Index Child Indices
0 N/A 1, 2
1 0 3, 4
, 2 0 5, 6
3 1 7, 8
4 1 9, 10
5 2 11, 12
Heap - parent_index -answer parent_index = (node_index - 1) // 2
or node_index // 2 - 1
Heap - left_child_index -answer left_child_index = 2 * node_index + 1
Heap - right_child_index -answer right_child_index = 2 * node_index + 2
Implementing priority queues with heaps. -answer Both functions return the value in the
root, but the Pop function removes the value and the Peek function does not. Pop is worst-case
O(logN) and Peek is worst-case O(1).
Push and pop operate have runtime O(logN). All other operations (Peek, IsEmpty, GetLength)
happen in constant time O(1).
Array based list -answer A list ADT implemented using an array. An array-based list
supports the common list ADT operations, such as append, prepend, insert after, remove, and
search.
Linked list vs Array -answer If a program requires fast insertion of new data, a linked list is
a better choice than an array.
Abstract Data Type (ADT) -answer A data type described by predefined user operations,
such as "insert data at rear," without indicating how each operation is implemented.
Array -answer A data structure that stores an ordered list of items, with each item is
directly accessible by a positional index.
Linked List -answer A data structure that stores ordered list of items in nodes, where
each node stores data and has a pointer to the next node.
Bianary Search Tree -answer A data structure in which each node stores data and has up
to two children, known as a left child and a right child.
Hash Table -answer A data structure that stores unordered items by mapping (or hashing)
each item to a location in an array (or vector).
Hashing -answer mapping each item to a location in an array (in a hash table).
Chaining -answer handles hash table collisions by using a list for each bucket, where each
list may store multiple items that map to the same bucket.
Hash key -answer value used to map an index
bucket -answer each array element in a hash table
ie A 100 elements hash table has 100 buckets
modulo hash function -answer computes a bucket index from the items key.
It will map (num_keys / num_buckets) keys to each bucket.
,ie... keys range 0 to 49 will have 5 keys per bucket.
= 5
hash table searching -answer Hash tables support fast search, insert, and remove.
Requires on average O(1)
Linear search requires O(N)
modulo operator % -answer common has function uses this. which computes the integer
remainder when dividing two numbers.
Ex: For a 20 element hash table, a hash function of key % 20 will map keys to bucket indices 0 to
19.
Max-Heap -answer A binary tree that maintains the simple property that a node's key is
greater than or equal to the node's childrens' keys. (Actually, a max-heap may be any tree, but is
commonly a binary tree).
*a max-heap's root always has the maximum key in the entire tree.
Heap storage -answer Heaps are typically stored using arrays. Given a tree representation
of a heap, the heap's array form is produced by traversing the tree's levels from left to right and
top to bottom. The root node is always the entry at index 0 in the array, the root's left child is
the entry at index 1, the root's right child is the entry at index 2, and so on.
Max-heap insert -answer An insert into a max-heap starts by inserting the node in the
tree's last level, and then swapping the node with its parent until no max-heap property
violation occurs.
The upward movement of a node in a max-heap is sometime called percolating.
,Complexity O(logN)
Max-heap remove -answer Always a removal of the root, and is done by replacing the
root with the last level's last node, and swapping that node with its greatest child until no max-
heap property violation occurs.
Complexity O(logN)
Percolating -answer The upward movement of a node in a max-heap
Min-Heap -answer Similar to a max-heap, but a node's key is less than or equal to its
children's keys.
Heap - Parent and child indices -answer Because heaps are not implemented with node
structures and parent/child pointers, traversing from a node to parent or child nodes requires
referring to nodes by index. The table below shows parent and child index formulas for a heap.
ie
1) parent index for node at index 12? 5
*** ((12-1) // 2) = 5 or 12 //2 -1 = 5
2) child indices for a node at index 6? 13 & 14
*** 2 * 6 + 1 = 13 and 2 * 6 + 2 = 14
**Double# and add 1, double# and add 2
Node index Parent Index Child Indices
0 N/A 1, 2
1 0 3, 4
, 2 0 5, 6
3 1 7, 8
4 1 9, 10
5 2 11, 12
Heap - parent_index -answer parent_index = (node_index - 1) // 2
or node_index // 2 - 1
Heap - left_child_index -answer left_child_index = 2 * node_index + 1
Heap - right_child_index -answer right_child_index = 2 * node_index + 2
Implementing priority queues with heaps. -answer Both functions return the value in the
root, but the Pop function removes the value and the Peek function does not. Pop is worst-case
O(logN) and Peek is worst-case O(1).
Push and pop operate have runtime O(logN). All other operations (Peek, IsEmpty, GetLength)
happen in constant time O(1).
Array based list -answer A list ADT implemented using an array. An array-based list
supports the common list ADT operations, such as append, prepend, insert after, remove, and
search.
Linked list vs Array -answer If a program requires fast insertion of new data, a linked list is
a better choice than an array.
Abstract Data Type (ADT) -answer A data type described by predefined user operations,
such as "insert data at rear," without indicating how each operation is implemented.
