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Lab 08: Hashmaps


The FAQ for this lab can be found here.


In this lab, you’ll work on MyHashMap, a hashtable-based implementation of the Map61B interface. This will be very similar to Lab 06, except this time we’re building a HashMap rather than a TreeMap.

After you’ve completed your implementation, you’ll compare the performance of your implementation to a list-based Map implementation ULLMap as well as the built-in Java HashMap class (which also uses a hash table). We’ll also compare the performance of MyHashMap when it uses different data structures to be the buckets.



We’ve created a class MyHashMap in, with very minimal starter code. Your goal is to implement all of the methods in the Map61B interface from which MyHashMap inherits, except remove, keySet and iterator (optional for Lab 08). For these, feel free to throw an UnsupportedOperationException.

Note that your code will not compile until you implement all the methods of Map61B. You can implement methods one at a time by writing the method signatures of all the required methods, but throwing UnsupportedOperationExceptions for the implementations until you get around to actually writing them.

Refresher Animation

The following is a quick animation of how a hash table works. N refers to the number of items in the hash table, and M refers to the number of buckets.

We use an object’s hashCode modulo’d (%) by the number of buckets to determine which bucket the object (represented by a shape) falls into. When the load factor is reached, we multiply the number of buckets by the resizing factor and rehash all of the items, modulo-ing them by the new number of buckets.

For the video animation below, the hash function is arbitrary and outputs a random integer for each shape (the object) that is inputted.

Credits to Meshan Khosla for this animation!

Skeleton Code

You might recall from lecture that when we build a hash table, we can choose a number of different data structures to be the buckets. The classic approach is to choose a LinkedList. But we can also choose ArrayLists, TreeSets, or even other crazier data structures like PriorityQueues or even other HashSets!


During this lab, we will try out hash tables with different data structures for each of the buckets, and see empirically if there is an asymptotic difference between using different data structures as hash table buckets.

For this lab, we will be trying out LinkedList, ArrayList, HashSet, Stack, and ArrayDeque (unfortunately, no TreeSet or PriorityQueue like the diagram above shows due to excessive boilerplate, though you’re welcome to try it if you’d like). That’s a lot of classes!

You can imagine that if we implemented MyHashMap without much care, it would take a lot of effort with Find + Replace to be able to change out the bucket type with a different bucket type. For example, if we wanted to change all our ArrayList buckets to LinkedList buckets, we would have to Find + Replace for all occurrences of ArrayList and replace that with LinkedList. This is not ideal - for example, we may have a non-bucket component that relies on some ArrayList methods. We wouldn’t want to ruin our code by changing that to a LinkedList!

The purpose of the starter code is to have an easier way to try out different bucket types with MyHashMap. It accomplishes this through polymorphism and inheritance, which we learned about earlier this semester. It also makes use of factory methods and classes, which are utility code used to create objects. This is a common pattern when working with more advanced code, though the details are out-of-scope for 61B.

MyHashMap implements the Map61B interface through use of a hash table. In the starter code, we give the instance variable private Collection<Node>[] buckets, which is the underlying data structure of the hash table. Let’s unpack what this code means:

  • buckets is a private variable in the MyHashMap class.
    private Collection<Node>[] buckets;
  • It is an array (or table) of Collection<Node> objects, where each Collection of Nodes represents a single bucket in the hash table
  • Node is a private (nested) helper class we give that stores a single key-value mapping. The starter code for this class should be straightforward to understand, and should not require any modification.
    protected class Node {
      K key;
      V value;
      Node(K k, V v) {
          key = k;
          value = v;
  • java.util.Collection is an interface which most data structures inherit from, and it represents a group of objects. The Collection interface supports methods such as add, remove, and iterator. Many data structures in java.util implement Collection, including ArrayList, LinkedList, TreeSet, HashSet, PriorityQueue, and many others. Note that because these data structures implement Collection, we can assign them to a variable of static type Collection with polymorphism.
  • Therefore, our array of Collection<Node> objects can be instantiated by many different types of data structures, e.g. LinkedList<Node> or ArrayList<Node>. Make sure your buckets generalize to any Collection! See the below warning for how to do this.
  • When creating a new Collection<Node>[] to store in our buckets variable, be aware that in Java, you cannot create an array of parameterized type. Collection<Node> is a parameterized type, because we parameterize the Collection class with the Node class. Therefore, Java disallows new Collection<Node>[size], for any given size. If you try to do this, you will get a “Generic array creation” error.

To get around this, you should instead create a new Collection[size], where size is the desired size.

  • The elements of a Collection[] can be a collection of any type, like a Collection<Integer> or a Collection<Node>. For our purposes, we will only add elements of type Collection<Node> to our Collection[].

The mechanism by which different implementations of the hash table implement different buckets is through a factory method protected Collection<Node> createBucket(), which simply returns a Collection. For, you can choose any data structure you’d like. For example, if you choose LinkedList, the body of createBucket would simply be:

protected Collection<Node> createBucket() {
	return new LinkedList<>();

Instead of creating new bucket data structures with the new operator, you must use the createBucket method instead. This might seem useless at first, but it allows our factory classes to override the createBucket method in order to provide different data structures as each of the buckets.

In MyHashMap, you can just have this method return a new LinkedList or ArrayList.

Implementation Requirements

You should implement the following constructors:

public MyHashMap();
public MyHashMap(int initialCapacity);
public MyHashMap(int initialCapacity, double loadFactor);

Some additional requirements for MyHashMap are below:

  • Your hash map should initially have a number of buckets equal to initialCapacity. You should increase the size of your MyHashMap when the load factor exceeds the maximum loadFactor threshold. Recall that the current load factor can be computed as loadFactor = N/M, where N is the number of elements in the map and M is the number of buckets. The load factor represents the amount of elements per bucket, on average. If initialCapacity and loadFactor aren’t given, you should set defaults initialCapacity = 16 and loadFactor = 0.75 (as Java’s built-in HashMap does).
  • You should handle collisions with separate chaining. You should not use any libraries other than the bucket classes, Collection, Iterator, Set, and HashSet. For more detail on how you should implement separate chaining, see the Skeleton Code section above.
  • Because we use a Collection<Node>[] for our buckets, when implementing MyHashMap, you are restricted to using methods that are specified by the Collection interface. When you are searching for a Node in a Collection, iterate over the Collection, and find the Node whose key is .equals() to the desired key.
  • If the same key is inserted more than once, the value should be updated each time (i.e., no Nodes should be added). You can assume null keys will never be inserted.
  • When resizing, make sure to multiplicatively (geometrically) resize, not additively (arithmetically) resize. You are not required to resize down.
  • MyHashMap operations should all be constant amortized time, assuming that the hashCode of any objects inserted spread things out nicely (recall: every Object in Java has its own hashCode() method).

hashCode() can return a negative value! Java’s modulo operator % will return a negative value for negative inputs, but we need to send items to a bucket in the range $[0, M)$. There are a myriad of ways to handle this:

  1. (Recommended) You can use Math.floorMod() in place of % for the modulo operation. This has a non-negative range of values, similar to Python’s modulo.
  2. If the resulting value after the % operation is negative, you can add the size of the array to it.
  3. You can use the Math.abs() function to convert the negative value to a positive value. Note that $|x| \, \mathrm{mod} \, m$, $|x \, \mathrm{mod} \, m|$, and $x \, \mathrm{mod} \, m$ are not equivalent in general! We’re just using the modulo operation here to make sure we have a valid index. We don’t necessarily care too much about the exact bucket the item goes into, because a good hash function should spread things out nicely over positive and negative numbers.
  4. Option (3) but with a bitmask (don’t worry if you don’t know what this means). This is out-of-scope for 61B, but some of the resources do this, which is why we’ve put it here.

Complete the MyHashMap class according to the specifications in Map61B and the guidelines above.


You may find the following resources useful

The following may contain antiquated code or use unfamiliar techniques, but should still be useful:

  • (provided), a working unordered linked list based Map61B implementation


You can test your implementation using Some of the tests are quite tricky and do weird stuff we haven’t learned in 61B. The comments will prove useful to see what the tests are actually doing.

If you’ve correctly implemented generic Collection buckets, you should also be passing the tests in The file simply calls methods in for each of the different map subclasses that implement a different bucket data structure. Make sure you’ve correctly implemented MyHashMap using the factory methods provided (i.e., createBucket) for to pass.

If you choose to implement the additional remove, keySet, and iterator methods, we provide some tests in

Speed Testing

There are two interactive speed tests provided in and Do not attempt to run these tests before you’ve completed MyHashMap. Once you’re ready, you can run the tests in IntelliJ.

The InsertRandomSpeedTest class performs tests on element-insertion speed of your MyHashMap, ULLMap (provided), and Java’s built-in HashMap. It works by asking the user for an input size N, then generates N Strings of length 10 and inserts them into the maps as <String, Integer> pairs.

Try it out and see how your data structure scales with N compared to the naive and industrial-strength implementations. Record your results in the provided file named src/results.txt. There is no standard format required for your results, and there is no required number of data points. We expect you to write at least a sentence or two with your observations, though.

Now try running InsertInOrderSpeedTest, which behaves similarly to InsertRandomSpeedTest, except this time the Strings in <String, Integer> key-value pairs are inserted in lexicographically-increasing order. Your code should be in the rough ballpark of Java’s built in solution – say, within a factor of 10 or so. What this tells us is that state-of-the-art HashMaps are relatively easy to implement compared to state-of-the-art TreeMaps. Consider this relation with BSTMap/TreeMap and other data structures - are there certain instances where a Hashmap might be better? Discuss this with your peers, and add your answer to results.txt.

Different Bucket Types

If you’ve correctly implemented generic Collection buckets, most of the work is done! We can directly compare the different data structures used to implement buckets. We provide speed/, which is an interactive test that queries the user for an integer L for the length of string to use on subsequent operations. Then, in a loop, it queries the user for an integer N, and runs a speed test on your MyHashMap using different types of buckets.

Try it out and compare how the different implementations scale with N. Discuss your results with your peers, and record your responses in results.txt.

You might notice that our implementation using HashSets as buckets searches for a Node by iterating over the entire data structure. But we know hash tables support more efficient lookups than that. Would our hash table speed up asymptotically if we were able to use a constant-time search over the HashSet? You do not need to implement anything new here, just discuss with your peers, and record your ideas in results.txt.

Run the above speed tests in the speed directory and record your results in results.txt.

Deliverables and Scoring

The lab is out of 5 points. There is one hidden test on Gradescope (that checks your results.txt). The rest of the tests are local. If you pass all the local tests and fill out the results.txt file sufficiently, you will get full credit on Gradescope.

Each of the following is worth $\frac{5}{11}$ points and corresponds to a unit test:

  • Generics
  • clear
  • containsKey
  • get
  • size
  • put
  • Functionality
  • Resizing
  • Edge cases
  • Buckets (all of TestMyHashMapBuckets)
  • results.txt (not tested locally, but on the Gradescope autograder)

As mentioned, if you are not implementing the optional exercises, throw an UnsupportedOperationException, like below:

throw new UnsupportedOperationException(); 


Just as you did for the previous assignments, add, commit, then push your Lab 08 code to GitHub. Then, submit to Gradescope to test your code.

Optional Exercises

These will not be graded, but you can still receive feedback with the given tests.

Implement the methods remove(K key) and remove(K key, V value), in your MyHashMap class. For an extra challenge, implement keySet() and iterator() without using a second instance variable to store the set of keys.

For remove, you should return null if the argument key does not exist in the MyHashMap. Otherwise, delete the key-value pair (key, value) and return the associated value.