ArrayList

You are to code an ArrayList, which is a list data structure backed by an array where all of the data is

contiguous and aligned with index $0$ of the array.

The ArrayList must follow the requirements stated in the javadocs of each method you must implement.

A constructor stub is provided for you to fill out.

Capacity

The starting capacity of the ArrayList should be the constant INITIAL CAPACITY defined in ArrayList.java.

Reference the constant as$-$is$.$ Do not simply copy the value of the constant. Do not change the constant.

If$,$ while adding an element, the ArrayList does not have enough space, you should regrow the backing

array to twice its old capacity. Do not resize the backing array when removing elements.

Adding

You will implement three add$()$ methods. One will add to the front, one will add to the back, and one

will add to anywhere in the list given a specific index. When adding to the front or the middle of the

list, subsequent elements must be shifted back one position to make room for the new data. See the

javadocs for more details.

Removing

You will also implement three remove$()$ methods $-$ from the front, the back, or anywhere in the list given

a specific index. When removing from the front or from the middle of the list, the element should be

removed and all subsequent elements should be shifted forward by one position. When removing from

the back, the last element should be set to null in the array. All unused positions in the backing

array must be set to null. See the javadocs for more details.

Amortized Efficiency

The efficiency of methods and algorithms in this course is often analyzed using a $$per operation$$ analysis.

That is$,$ what is the worst this algorithm can do on any one instance? However, there are times where this

type of analysis is unrealistically pessimistic. For example, in this homework, the addToBack$()$ method

is O$(1)$ for the most part except in the case of resizing, which is O$($n$).$ However, a resize operation is

rare enough that it$$d be misleading to say that the method is O$($n$).$

In cases like this, we use an amortized analysis. This type of analysis adds up the cost of a series of

operations and then averages the cost. Here, the resize step is O$($n$),$ but since we double the capacity

whenever the array gets full, we will not need to resize for another n add operations. So$,$ putting that

together with the common, cheap O$(1)$ operations, we get O$(1)$ using this analysis. Whenever this type

of analysis is used, we will prefix the Big$-$O with the word amortized.

Equality

There are two ways of defining objects as equal: reference equality and value equality.

Reference equality is used when using the $==$ operator. If two objects are equal by reference equality, that means that they have the exact same memory locations. For example, say we have a Person

object with a name and id field. If you$$re using reference equality, two Person objects won$$t be considered

equal unless they have the exact same memory location $($are the exact same object$),$ even if they have

the same name and id$.$

Value equality is used when using the $.$equals$()$ method. Here, the definition of equality is custom

$4$

Homework $1$: ArrayList Due: See Canvas

made for the object. For example, in that Person example above, we may want two objects to be considered equal if they have the same name and id$.$

Keep in mind which makes more sense to use while you are coding. You will want to use value

equality in most cases in this course when comparing objects. Notable cases where you$$d

use reference equality include checking for null or comparing primitives $($in this case, it$$s

just the $==$ operator being overloaded$).$