Consider the adjacency matrix below. Upload a picture (it can be hand drawn) of the adjacency list of the graph. Note: File size must not exceed 1 MB.* A 1 1 1 C 1 0. 1. 1. A, 1. E
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- Assume we wish to resize an existing hash table because the current hash table is becoming too small for the application. Without writing code briefly describe the process of resizing a hash table by "copying" the old data to the new hash table. What is the expected complexity of your process using Big-O notation. Justify your complexity measure. An example of a hash table before resizing is given.you need to design, analyze, and implement algorithms to read in a sequence of characters from standard input and maintain the characters in a linked list with no duplicates. When you read in a previously unseen character, insert it at the front of the list. When you read in a duplicate character, delete it from the list and reinsert it at the beginning. The program implements the well-known move-to-front strategy which is useful for caching, data compression, and many other applications where items that have been recently accessed are more likely to be re-accessed. Requirements: The program should read a sequence of characters. The program should insert unseen character at the front of the list. The program should check if the character is not in the list to be inserted at the front of the list. The program should delete a duplicate character and delete it from the list and insert it at the beginning of the list. The program should check if the character is already in the list and…Write a Python script that implements the CHF (the Casual Hash Function.) The input data should be split into blocks of 32 bits. If the last block is smaller than 32 bits, the remaining bits should be filled with 1 followed by as many zeros as required. A and B are 2 buffers with specific values (see below). Each block in the message should be combined as shown in the image below. All resulting blocks (i.e. FBI) should be combined with "&" to produce the digest. The size of the digest is 64 bits. Calculate the digest for the string: "Alright, but apart from the sanitation, the medicine, education, wine, public order, irrigation, roads, the fresh-water system, and public health, what have the Romans ever done for us?" steps on how are in the attached pictures
- Write a Python script that implements the CHF (the Casual Hash Function.) The input data should be split into blocks of 32 bits. If the last block is smaller than 32 bits, the remaining bits should be filled with 1 followed by as many zeros as required. A and B are 2 buffers with specific values (see below). Each block in the message should be combined as shown in the image below. All resulting blocks (i.e. FBI) should be combined with "&" to produce the digest. The size of the digest is 64 bits. Calculate the digest for the string: "Alright, but apart from the sanitation, the medicine, education, wine, public order, irrigation, roads, the fresh-water system, and public health, what have the Romans ever done for us?"Consider a list of data components L[0:5] = 23, 14, 98, 45, 67, and 53. Let's look for the K = 53 key. Naturally, the search moves down the list, comparing key K with each element until it discovers it as the final element in the list. When looking for the key K = 110, the search moves forward but eventually drops off the list, making it a failed search. Write the algorithmic steps for both sorted and unordered linear searches, along with the times involved.Consider an extensible hash table that uses 4-bit hash keys and stores two recordsper bucket. Simulate the insertion, into an initially empty hash table, of records with(hash values of) keys 1111, 1110, 1101,..., 0001, 0000, in that order. Simulate all 16insertions, indicating what happens after each insertion. Start with i=0 bit.
- Suppose that we are using extendable hashing on a file that contains recordswith the following search-key values:2, 3, 5, 7, 11, 17, 19, 23, 29, 31Show the extendable hash structure for this file if the hash function is h(x) = xmod 8 and buckets can hold three records.code in python attached please Define a hash table with an associated hash function ℎ(?)h(k) mapping keys ?k to their associated hash value. b) In simple uniform hashing, each key is assumed to have equal probability to map to any of the hashes in a given table of size m. Given an open-address table of size 500500 and 22 random keys, what is the probability that they hash to the same value? What is the probability that they hash to different values?Question 5 Assume you have a hash table of size 13, insert the following keys using open addressing with linear probing, assuming that the H(Key) = key % size and the bucket size is equal to 1. Keys: 25, 66, 710, 150, 82, 111, 70,17 a. index key 0 1 66 2 3 4 82 5 70 6 17 7 150 8 710 9 111 10 11 25 12 b. index key 1 2 66 3 4 5 82 6 70 7 17 8 150 9 710 10 111 11 12 13 25 c. index key 0 1 66 2 3 4 82 5 70 6 17 7 150 8 111 9 710 10 11 12 25 d. index key 0 1 66 2 3 4 82 5 70 6 17 7 150 8 710 9 111 10 11 12 25
- In this exercise we will be processing some data stored as a list of dictionaries in order to be able to answer queries on the data. In our case we simply have a list of student records, where each record is a dictionary that has the student's name and their GPA. An example of the data set is below: roster = [{'name': 'Alice', 'gpa': 4.0}, {'name': 'Bob', 'gpa': 3.5}, {'name': 'Cody', 'gpa': 3.75}, {'name': 'David', 'gpa': 3.65} {'name': 'Archy', 'gpa': 3.39}, {'name': 'Nadia', 'gpa': 2.39}, {'name': 'Cesya', 'gpa': 3.34}, {'name': 'Kellie', 'gpa': 2.32}, {'name': 'Jordana', 'gpa': 3.64}, {'name': 'Wilton', 'gpa': 2.59}, {'name': 'Meagan', 'gpa': 3.45}, {'name': 'Leela', 'gpa': 2.66}, {'name': 'Kaela', 'gpa': 2.71}, {'name': 'Isabelita', 'gpa': 3.47}, {'name': 'Phillipe', 'gpa': 2.95}, {'name': 'Eula', 'gpa': 3.46}, {'name': 'Odetta', 'gpa': 3.56}, {'name': 'Christian', 'gpa': 3.4}, {'name': 'Zared', 'gpa': 2.84}, {'name': 'Devondra', 'gpa': 2.02}, {'name': 'Scarface', 'gpa':…In Python, implement a hashing table data structure of size 20, which can cope with collisions. Thus, you must implement the closed collision system in its three modes: Linear scanQuadratic scanDouble hashing scan. For halt use halt(k)= (k mod (m - 1)) + 1, where m is the size of the table. The data to be managed are students from a certain university who have a 5-digit registration number and it is unique. In addition, the student has a name, age and address. Create a .txt file with 10 students (one for each line) and have them loaded into your program. Build a menu of options where you can: - Find a student and print his data if found and position in the table. Otherwise print a "Not Found" message.In Python, implement a hashing table data structure of size 20, which can cope with collisions. Thus, you must implement the closed collision system in its three modes: Linear scanQuadratic scanDouble hashing scan. For halt use halt(k)= (k mod (m - 1)) + 1, where m is the size of the table. The data to be managed are students from a certain university who have a 5-digit registration number and it is unique. In addition, the student has a name, age and address. Create a .txt file with 10 students (one for each line) and have them loaded into your program. Build a menu of options where you can: - Enter a new student. For this option, that only allows entering the 5-digit license plate and that random data is automatically generated for the name, age and address. Return the position where it was entered and if it is not possible to enter it, print a message that explains why the entry was not obtained.