## Week 1

### Interfaces

- Use the
`Collection<E>`

and`List<E>`

interfaces defined in the Java Collection Framework - Explain when to use
`Collection<E>`

instead of`List<E>`

and vice versa - Demonstrate correct use of generics when declaring
`Collection<E>`

and`List<E>`

interfaces - Describe the implications of an interface extending another interface
- List two classes that implement the
`Collection<E>`

interface - List two classes that implement the
`List<E>`

interface

## Related Videos

### Array Based Lists

- Describe key differences between an array and an
`ArrayList<E>`

object - Implement classes and methods that make use of generics
- Write an array-based implementation of the
`List<E>`

interface, including the following methods: - Implement small software systems that use one or more
`ArrayList<E>`

objects - Describe key differences between the in class implementation and the
`java.util.ArrayList<E>`

implementation - Describe differences in the
`java.util.ArrayList`

implementation compared to the one created in lecture that affect the asymptotic time complexity of any of the methods

## Related Videos

- ArrayList Physical Demonstration
- ArrayList Overview
- Implementation of ArrayList Class
- java.util.ArrayList versus Our Implementation (also has graphical representation of class)
- Implementation of ArrayList Constructor
- Implementation of ArrayList size()/isEmpty()
- Implementation of ArrayList clear()
- Implementation of ArrayList add(E)
- Talking through ArrayList add(int, E)
- Implementation of ArrayList indexOf(Object)
- Implementation of ArrayList toArray()
`add(int, E)`

`contains(Object)`

`get(int)`

`set(int, E)`

`remove(int)`

`remove(Object)`

## Week 2

### Big-O Notation and Algorithm Efficiency

- Explain the purpose of Big-O notation
- Describe the limitations of Big-O notation
- Be familiar with the formal definition of Big-O
- Using Big-O notation, determine the asymptotic time complexity of an algorithm with a conditional
- Using Big-O notation, determine the asymptotic time complexity of an algorithm with a loop
- Determine the asymptotic time complexity of an algorithm with a nested loop
- Using Big-O notation, determine the asymptotic time complexity of an algorithm that calls other methods with known asymptotic time complexity
- Use time complexity analysis to choose between two competing algorithms
- Describe the meaning of the following symbols:
**T(n)**,**f(n)**, and**O(f(n))** - Given
**T(n)**expressed as a polynomial, determine the Big-O notation - Determine the asymptotic time complexity of the following methods from the
`ArrayList<E>`

class:`add(E)`

,`add(int, E)`

,`clear()`

,`contains(Object)`

,`get(int)`

,`indexOf(Object)`

,`isEmpty()`

,`remove(int)`

,`remove(Object)`

,`set(int, E)`

, and`size()`

## Related Videos

### Linked Lists

- Describe key differences between an array based list and a linked list
- Describe advantages and disadvantages of a singly linked list verses a doubly linked list
- Write an singly linked list implementation of the
`List<E>`

interface, including the following methods: - Describe key differences between a singly linked list and the
`LinkedList<E>`

class - Determine the asymptotic time complexity of the following methods from a singly linked list class developed in lecture:
`add(E)`

,`add(int, E)`

,`clear()`

,`contains(Object)`

,`get(int)`

,`indexOf(Object)`

,`isEmpty()`

,`remove(int)`

,`remove(Object)`

,`set(int, E)`

, and`size()`

- Describe differences in the JCF
`LinkedList`

implementation compared to the one created in lecture that affect the asymptotic time complexity of any of the methods - Implement small software systems that use one or more
`LinkedList<E>`

objects

## Related Videos

Note: It may be helpful to watch the unit and JUnit testing videos (see week 3 outcomes) before the remaining videos in this list.

`add()`

`clear()`

and description on`get()`

/`set()`

/`contains()`

`add(int, E)`

and`remove(Object)`

- Big-O on LinkedList (audio only) only after doing LinkedList implementation

## Week 3

### Iterators

- List the methods declared in the
`Iterator<E>`

interface - List the methods declared in the
`Iterable<E>`

interface - Implement the
`iterator()`

method in the`ArrayList`

class (returning a fully functional iterator) - Implement the
`iterator()`

method in the`LinkedList`

class (returning a fully functional iterator) - Explain why the enhanced for loop only works on classes that implement the
`Iterable<E>`

interface - Be familiar with the
`ListIterator<E>`

interface

## Related Videos

### Java Collection Framework and Testing

- Explain the purpose of the Java Collections Framework
- Be familiar with class/interface hierarchy for the Java Collections Framework
- Describe the following levels of testing: unit, integration, system, and acceptance
- Describe the differences between black-box testing and white-box testing
- List advantages and disadvantages of black-box testing verses white-box testing
- Develop tests that test boundary conditions

## Related Videos

## Week 4

### Stacks

- Enumerate and explain the methods that are part of a
**pure stack**interface - Define LIFO and explain how it relates to a stack
- Explain how the
`Stack<E>`

class is implemented in the Java Collection Framework - Describe the design flaw found in the
`Stack<E>`

implementation found in the Java Collection Framework - Implement a class that provides an efficient implementation of the pure stack interface using an
`ArrayList<E>`

- Implement a class that provides an efficient implementation of the pure stack interface using a
`LinkedList<E>`

- Define the term
**adaptor class**and be able to implement a simple adaptor class, e.g., stack, queue - Implement small software systems that use one or more stack data structures
- List at least two examples of when it makes sense to use a
`Stack`

## Related Videos

## Week 5

### Queues

- Enumerate and explain the methods that are part of a
**pure queue**interface - Define FIFO and explain how it relates to a queue
- The
`Queue<E>`

interface has multiple methods for insertion, removal, and accessing the front element. Describe how these methods differ. - Describe the design flaw found in the
`Queue<E>`

interface found in the Java Collection Framework - Implement a class that provides an efficient implementation of the pure queue interface using a
`LinkedList<E>`

- Explain why an
`ArrayList<E>`

is not an appropriate choice when implementing a pure queue interface - Explain how a circular queue differs from a standard queue
- Implement a class that provides an efficient implementation of a circular queue using an array
- Implement small software systems that use one or more queue data structures
- List at least two examples of when it makes sense to use a
`Queue`

## Related Videos

### Recursion

- For a given input, determine how many times a recursive method will call itself
- Explain the role of the base case and recursive step in recursive algorithms
- Use recursion to traverse a list
- Use recursion to search a sorted array
- Use the
`compareTo()`

method from the`Comparable`

interface to determine which of two objects is bigger - Write a generic class which implements the
`Comparable`

interface appropriately - Understand and apply recursion in algorithm development

## Related Videos

- Intro to recursion
- When to stop / conditional break points
- 1 + 2 + ... + n
- Fibonacci Sequence
- Recursive toString() for arrays
- CodingBat:
`bunnyEars()`

- CodingBat:
`triangle()`

- CodingBat:
`countHi()`

- Binary Search
- $O(\log n)$
- Binary Search Interface with Generics
- Binary Search Implementation
- Running Binary Search and O() Analysis
`RandomAccess`

Marker Interface

## Week 6

### Binary Trees

- Use the following terms to describe nodes in a tree: root, children, parent, sibling, leaf, ancestor, descendent
- Recognize empty trees and contents after any branch to be trees themselves, specifically subtrees
- Define node level recursively, starting with level 1 at the root. Define height as the maximum node level.
- Define binary tree (contrasted with a general tree) and explain the use of common types of binary trees: expression trees, Huffman trees, binary search trees
- Explain the criteria for binary trees that are full, perfect, and complete
- Explain preorder, inorder, and postorder traversal of trees using words and figures
- Explain the significance of each of these orders when applied to expression trees

## Related Videos

### Binary Tree Implementation

- Develop a
`BinaryTree<E>`

class with no-arg, one-arg (root node) and 3-arg (root node as well as left and right subtrees) constructors - Implement
`BinaryTree<E>`

methods: get{Left,Right}Subtree, isLeaf, and preOrderTraverse/toString methods

## Week 7

### Binary Search Trees

- Define the ordered relationship between parent and child nodes
- Implement a recursive
`contains()`

method - Implement a recursive
`size()`

method - Implement a recursive
`height()`

method - Describe how elements are added to a binary search tree
- Describe how elements are removed from a binary search tree

## Related Videos

## Week 8

### Sets and Maps

- Use the
`Set<E>`

and`Map<K, V>`

interfaces defined in the Java Collection Framework - Choose the appropriate interface to use from the following choices:
`Collection<E>`

,`List<E>`

,`Set<E>`

, and`Map<K, V>`

- List two classes that implement the
`Map<K, V>`

interface - Interpret and write Java code using the
`TreeMap`

and`TreeSet`

classes - State and explain the asymptotic time complexity of the following methods from a
`TreeSet`

:`add(E)`

,`clear()`

,`contains(Object)`

,`isEmpty()`

,`remove(Object)`

, and`size()`

## Related Videos

### Hash Tables

- Describe how elements are added to a hash table
- Describe how elements are removed from a hash table
- Explain the
**capacity**of a hash table and how it is used - Define the
**load factor**of a hash table and explain how it is used - Define a
**collision**as it relates to hash tables and describe ways of coping with collisions - Describe the
**open addressing**method for dealing with collisions within a hash table - Describe the
**chaining**method for dealing with collisions within a hash table - Write a hash table implementation (using chaining) that includes the following methods:
- Explain why the
`Object.hashCode()`

method must be overridden if the`Object.equals()`

method is overridden - Describe the criteria for a good
`hashCode()`

implementation - Interpret and develop simple hashing functions
- Interpret and write Java code using the
`HashMap`

and`HashSet`

classes - State and explain the asymptotic time complexity of the following methods from a
`HashSet`

:`add(E)`

,`clear()`

,`contains(Object)`

,`isEmpty()`

,`remove(Object)`

, and`size()`

## Related Videos

- Mapping Objects to Integers
- Introduction to Hashtables
- The
`HashMap`

- Changing the capacity of the Hashtable
- Weekly Outcomes
- Open Addressing
- Outcome Review
`HashTable`

structure`size()`

,`isEmpty()`

,`clear()`

, and`Constructor`

`contains()`

- Aside on
`String.hashCode()`

- Uniqueness of
`hashCode()`

values and Q and A`remove()`

`add()`

`add()`

continued

## Week 9

### Balanced Trees

- Describe the impact that balance has on the performance of binary search trees
- Implement the
`leftRotate()`

and`rightRotate()`

methods for a binary tree - Explain the mechanism used in AVL trees to ensure that they remain balanced
- Illustrate the steps required to balance an AVL tree upon insertion of an additional element

## Related Videos

- Introduction and Weekly Outcomes
- Tree Rotations
- All Possible Unbalanced Tree Scenarios
`leftRotate()`

Implementation- AVL Self-Balancing on
`add()`

/`remove()`

- Introduction/Final Exam Questions (bonus material)
- Red Black Tree Rules (bonus material)
- Red Black Tree Examples (bonus material)

### Deep verses Shallow Copies

- Distinguish between copying a reference and copying an object
- Demonstrate proper use of
`==`

and`.equals()`

- Describe approaches to making deep copies, e.g.,
`clone()`

and copy constructors

## Related Videos

## Videos Reviewing Big O