Table of Contents

Code Challenges

1. Code Challenge 06

• link list insertions

2. Code Challenge 07

• link list kth

3. Code Challenge 08

• merge link lists

4. Code Challenge 11

• queue with stacks

5. Code Challenge 12

• fifo animal shelter

6. Code Challenge 13

• multi braket validation

7. Code Challenge 16

• fizz buzz tree

8. Code Challenge 17

• breadth fist

9. Code Challenge 18

• find maximum binary tree

10. Code Challenge 31

• repeated word

10. Code Challenge 32

• tree intersection

10. Code Challenge 33

• left join

DSA Implementation

1. Trees

• trees code

2. Hash Table

• hash table code

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Code Challenges

Code Challenge 06

Authors: Joseph Hangarter & Brandyn Vay

Challenge

• .append(value) which adds a new node with the given value to the end of the list
• .insertBefore(value, newVal) which add a new node with the given newValue immediately before the first value node
• .insertAfter(value, newVal) which add a new node with the given newValue immediately after the first value node

Approach & Efficiency

Solution

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Code Challenge 07

Authors: Joseph Hangarter & Brandyn Vay

Challenge

• k-th value from the end of a linked list.

Approach & Efficiency

Solution

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Code Challenge 08

Authors: Brad Smialek & Brandyn Vay

Challenge

• merge two linked list into one.

Approach & Efficiency

Solution

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Code Challenge 11

Authors: Brandyn Vay, Jonny Graybill, and Jeremy Lee

Challenge

• take two stacks and use queue implementation

Approach & Efficiency

Solution

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Code Challenge 12

Authors: Brandyn Vay, Brad Smialek

Challenge

• Create a class called AnimalShelter which holds only dogs and cats. The shelter operates using a first-in, first-out approach.

Approach & Efficiency

Solution

back to the topv

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Code Challenge 13

Authors: Brandyn Vay, Brad Smialek

Challenge

• Your function should take a string as its only argument, and should return a boolean representing whether or not the brackets in the string are balanced.

Approach & Efficiency

Solution

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Code Challenge 16

Authors: Brandyn Vay, Brad Smialek

Challenge

• Conduct “FizzBuzz” on a tree while traversing through it. Change the values of each of the nodes dependent on the current node’s value.

Approach & Efficiency

Solution

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Code Challenge 17

Authors: Brandyn Vay, Adrienne Easton

Challenge

• Write a breadth first traversal method which takes a Binary Tree as its unique input. Without utilizing any of the built-in methods available to your language, traverse the input tree using a Breadth-first approach; print every visited node’s value.

Approach & Efficiency

Solution

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Code Challenge 18

Authors: Brandyn Vay, Adrienne Easton

Challenge

• Write a function called find-maximum-value which takes binary tree as its only input. Without utilizing any of the built-in methods available to your language, return the maximum value stored in the tree. You can assume that the values stored in the Binary Tree will be numeric.

Approach & Efficiency

Solution

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Code Challenge 31

Authors: Brandyn Vay

Challenge

• Write a function that accepts a lengthy string parameter.

Approach & Efficiency

Solution

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Code Challenge 32

Authors: Brandyn Vay

Challenge

• Write a function called tree_intersection that takes two binary tree parameters.

Approach & Efficiency

Solution

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Code Challenge 33

Authors: Brandyn Vay

Challenge

• Write a function that LEFT JOINs two hashmaps into a single data structure.
• The first parameter is a hashmap that has word strings as keys, and a synonym of the key as values.
• The second parameter is a hashmap that has word strings as keys, and antonyms of the key as values.
• Combine the key and corresponding values (if they exist) into a new data structure according to LEFT JOIN logic.
• LEFT JOIN means all the values in the first hashmap are returned, and if values exist in the “right” hashmap, they are appended to the result row. If no values exist in the right hashmap, then some flavor of NULL should be appended to the result row.
• The returned data structure that holds the results is up to you. It doesn’t need to exactly match the output below, so long as it achieves the LEFT JOIN logic.

Approach & Efficiency

Solution

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DSA Implamentation

Trees

Challenge

create a binary tree and a binary search tree

Approach & Efficiency

API

1. Binary Tree

• preOrder()
• postOrder()
• inOrder()

2. Binary Search Tree

• add
• contains

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Hash Tables

Challenge

Implement a Hashtable with the following methods:

• add: takes in both the key and value. This method should hash the key, and add the key and value pair to the table, handling collisions as needed.
• get: takes in the key and returns the value from the table.
• contains: takes in the key and returns a boolean, indicating if the key exists in the table already.
• hash: takes in an arbitrary key and returns an index in the collection.

Approach & Efficiency

O(1)

API

1. Hash Table

• add()
• get()
• contains()
• hash()