CyberCrimeDatabase.java

• DO NOT add new import statements.

• DO NOT change any of the method’s signatures.

Methods to be implemented by you:

initializeDatabase() [PROVIDED]

This method reads lines from an input file and calls the following two methods to create a Hacker object and insert it into the hackerDatabase Hash Table.

You are given input files containing different Hacker information as well as their incident information. Each hacker has 7 lines, formatted as follows.

For IPs and URLs, we used a one-way hash called MD5 in order to de-identify URLs and IPs that could be malicious. We aren’t working with real IPs and URLs to avoid links to malicious sites.

• Hacker Name
• IP Address Hash
• Location
• OS
• Web Server
• Date
• URL Hash

Do not update this method, it has been implemented for you. IMPLEMENT the first two methods (readSingleHacker and addHacker).

1. readSingleHacker()

This method reads the information for a single incident for a single hacker and creates the corresponding objects.

Remember that the order you will read items in is as follows, and each is contained on one line:

• Hacker Name (string that may contain spaces, use StdIn.readLine() to read)

• IP Address Hash (a string)

• Location (a string that may contain spaces)

• OS (a string that may contain spaces)

• Web Server (a string that may contain spaces)

• Date (a string YYYY-MM-DD)

• URL Hash (a string)

You can assume StdIn.setFile() has already been called, and simply call StdIn.readLine() once for each above bullet.

Create an Incident object, using the OS, Web Server, Date, Location, IP Address Hash, and URL Hash (the constructor is not necessarily in the same order as the input file). Then, create a Hacker object using the name, and Incident. Remember that hackers have an ArrayList of incidents. 

Return that Hacker object.

Test this using initializeDatabase AFTER you have implemented the addHacker method. Use the debugger in VS Code to verify that items are being read and created correctly on each iteration of this method.

EARLY SUBMISSION CONSISTS OF THIS METHOD AND addHacker. Make sure you submit BOTH methods for early submission; we will not make exceptions if you only implement this method.

2. addHacker(Hacker toAdd)

This method inserts a Hacker into the hash table stored at hackerDatabase.

You are given a Hacker object to insert, via the method parameters. This is the candidate that we will attempt to insert – no duplicates are allowed.

Calculate which Hash Table index this hacker belongs to with Math.abs(hacker.hashCode()) % tableLength (where tableLength is the length of the hackerDatabase array). 

Then, check the Linked List found at that Hash Table index:

• If the list is empty, add that Hacker to the list. YOU MUST increment numHackers by 1 when a unique hacker is added, even when the list is empty, and you MUST call resize if the load factor is met even when inserting into an empty list.

• If the hacker’s name already exists in that list, then add all of the toAdd Hacker’s incidents to the existing Hacker object you found.

  • You can use hacker.getIncidents().addAll( toAdd.getIncidents() ) to add the new Hacker’s incidents to the existing Hacker (replace “hacker” with the existing Hacker object you found).

• If the hacker’s name is not found in the list at that index, add the hacker to the END of the list and increment numHackers by 1.

AFTER YOU INSERT, check if the number of hackers in the table (numHackers) is >= the length of hackerDatabase divided by 2. If it is, then call the resize() method (seen below). DO NOT do this if you did not insert a new LLNode.

Early submission. Implement the first two methods for extra credit: readSingleHacker() and addHacker(). We will not make exceptions if you only implement one method. You do NOT need to implement resize() for early submission; we’ll only test early submission with tables that do not resize. 

This is the expected output in the driver when attempting to run hackerTest.in (which does NOT rehash).

You can view incidents by clicking the “View Incidents” button.

Here’s a text based representation:

Index 0
{Suspect: Hacker7658, Num Incidents: 1}
        {OS: Linux, Web Server: Apache, URL Hash: 1a320cc7e82d4e9dd0b251cda1e5149b, IP Hash: 8692d611f3c49198155ffaa6f2f4e8fe, Location: Indonesia}
Index 1
Index 2
Index 3
{Suspect: Hacker6313, Num Incidents: 2}
        {OS: Linux, Web Server: Apache, URL Hash: a6e869c4ae9a48eb1bc2b54fa03db660, IP Hash: 126e7450a80a4689d5977980cce05883, Location: France}
        {OS: Linux, Web Server: Apache, URL Hash: 775c0a468b31b4321922c66177f4f8b0, IP Hash: 126e7450a80a4689d5977980cce05883, Location: France}
Index 4
Index 5
{Suspect: Hacker8850, Num Incidents: 2}
        {OS: Linux, Web Server: Apache, URL Hash: b2aec8b43de6bfb640e8bc361f02e926, IP Hash: 157ef7f43422d9fae16234410796f823, Location: United States}
        {OS: Linux, Web Server: Apache, URL Hash: b61bd74247657f91c4540359d635f403, IP Hash: 157ef7f43422d9fae16234410796f823, Location: United States}
Index 6
{Suspect: Hacker6879, Num Incidents: 2}
        {OS: Linux, Web Server: Apache, URL Hash: 22d9f5148e5ff424df1897c502ae756f, IP Hash: dea0daf8749639f8618c64c7b092325c, Location: European Uni}
        {OS: Linux, Web Server: Apache, URL Hash: ed55ac2ae85cf97caac5c6ce30255149, IP Hash: ecc205bf2f3cc3b8ce8e48503bcf5c5d, Location: Italy}
Index 7
Index 8
Index 9