WGU C949 STUDY GUIDE | DATA STRUCTURES &
ALGORITHMS 1 | LATEST 2025 UPDATE | WITH
COMPLETE SOLUTION
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
ALGORITHMS 1 | LATEST 2025 UPDATE | WITH
COMPLETE SOLUTION
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
