Homework 1
... Repeat the above calculations when we randomly throw n log n balls into n bins. §2 The simplest model for a random graph consists of n vertices, and tossing a random fair coin for each pair {i, j} to decide whether this edge should be present in the graph. For each k compute the expected number of k ...
... Repeat the above calculations when we randomly throw n log n balls into n bins. §2 The simplest model for a random graph consists of n vertices, and tossing a random fair coin for each pair {i, j} to decide whether this edge should be present in the graph. For each k compute the expected number of k ...
6.851 Advanced Data Structures (Spring`07)
... 1-universal. Deterministic y-fast tries. Suppose you have a dynamic perfect hash function h such that: • h is constructible in deterministic linear time; • h(x) can be evaluated in O(1) worst case, deterministic time; • insertions and deletions take O(lg5 u) worst case time; Use h to modify the y-fa ...
... 1-universal. Deterministic y-fast tries. Suppose you have a dynamic perfect hash function h such that: • h is constructible in deterministic linear time; • h(x) can be evaluated in O(1) worst case, deterministic time; • insertions and deletions take O(lg5 u) worst case time; Use h to modify the y-fa ...
Hash Table - Touque.ca
... If we want to assign an ID to each student name, we could use their student number. However, if the greatest student number is “351000005”, there would be 351,000,005 elements in the array. This is a lot more than what is required to store the names of 500 students. ...
... If we want to assign an ID to each student name, we could use their student number. However, if the greatest student number is “351000005”, there would be 351,000,005 elements in the array. This is a lot more than what is required to store the names of 500 students. ...
CSC 2500 Computer Organization
... Another data structure could be used to resolve the collisions; for example, binary search trees. Why do we use linked lists instead? We define the load factor, λ, of a hash table to be the ratio of the number of elements in the table to the table size. The average length of a list is λ. The effort ...
... Another data structure could be used to resolve the collisions; for example, binary search trees. Why do we use linked lists instead? We define the load factor, λ, of a hash table to be the ratio of the number of elements in the table to the table size. The average length of a list is λ. The effort ...
投影片 1 - CSIE -NCKU
... Network applications such as IP traceback , route lookup, TCP flow state monitoring, and malware detection often require large data storage resources, fast queries, and frequent updates. Hash tables are traditional data structures that allow large amounts of data to be stored, queried, and updated ...
... Network applications such as IP traceback , route lookup, TCP flow state monitoring, and malware detection often require large data storage resources, fast queries, and frequent updates. Hash tables are traditional data structures that allow large amounts of data to be stored, queried, and updated ...
Trees
... Efficient data structure to implement search, delete and insert operations. Two main possibilities: ...
... Efficient data structure to implement search, delete and insert operations. Two main possibilities: ...
Hash Table
... • A hash function transforms a key (k) into a table address (0…m-1) • What makes a good hash function? (1) Easy to compute (2) Approximates a random function: for every input, every output is ...
... • A hash function transforms a key (k) into a table address (0…m-1) • What makes a good hash function? (1) Easy to compute (2) Approximates a random function: for every input, every output is ...
Untersuchungen zur MAC Address Translation (MAT)
... Packet Classification and Hash Functions Packet Classification Problem: In huge rule sets a search takes much time and/or demands huge memories Hash functions have a search complexity of ideally O(1) and memory demand of O(N) Problem when using (hardware) hash functions: High performance fo ...
... Packet Classification and Hash Functions Packet Classification Problem: In huge rule sets a search takes much time and/or demands huge memories Hash functions have a search complexity of ideally O(1) and memory demand of O(N) Problem when using (hardware) hash functions: High performance fo ...
Data Structures (810:052) Lecture 20 Name:_________________
... 3. Unfortunately, perfect hash functions are a rarity, so in general two or more target values might get mapped to the same hash-table index, called a collision. Collisions are handled by two approaches: chaining, closed-address, or external chaining: all target values hashed to the same home addr ...
... 3. Unfortunately, perfect hash functions are a rarity, so in general two or more target values might get mapped to the same hash-table index, called a collision. Collisions are handled by two approaches: chaining, closed-address, or external chaining: all target values hashed to the same home addr ...
Bitwise Operators
... Queues • First in, first out data structure. • “Insert” and “Remove” operations. ...
... Queues • First in, first out data structure. • “Insert” and “Remove” operations. ...
Heap Sort
... data structure implemented as an array of objects, where the search keys correspond to the array indices ► Insert and find operations involve straight forward array accesses: O(1) time complexity ...
... data structure implemented as an array of objects, where the search keys correspond to the array indices ► Insert and find operations involve straight forward array accesses: O(1) time complexity ...
ppt (new version
... (i) Indicate what data structure B and pre-processing function PreProcess can be used to speed-up IsMember. What is the worstcase complexity of PreProcess? (ii) Write a function IsMember I that takes advantage of the data structure B. What is the worst-case complexity of IsMember ? What is pre-proce ...
... (i) Indicate what data structure B and pre-processing function PreProcess can be used to speed-up IsMember. What is the worstcase complexity of PreProcess? (ii) Write a function IsMember I that takes advantage of the data structure B. What is the worst-case complexity of IsMember ? What is pre-proce ...
Document
... 4.)* Download the Graph Theory Demo and implement a minimum spanning tree algorithm by Kruskal (the algorithm is easy but you will need to understand the original code written in lectures). Test it with a sufficiently large Graph. 5.)* Implement a simple Hash-Table, using the LinkedList method for c ...
... 4.)* Download the Graph Theory Demo and implement a minimum spanning tree algorithm by Kruskal (the algorithm is easy but you will need to understand the original code written in lectures). Test it with a sufficiently large Graph. 5.)* Implement a simple Hash-Table, using the LinkedList method for c ...
Hashing
... Insert and find operations can be implemented using a BST with average insert/find time of O(logn). However, a BST is generally a more powerful data structure than a hash table as it can easily support routines that require order, for example, finding the smallest/largest element. ...
... Insert and find operations can be implemented using a BST with average insert/find time of O(logn). However, a BST is generally a more powerful data structure than a hash table as it can easily support routines that require order, for example, finding the smallest/largest element. ...
Hashing
... Perfect hashing Goal: worst-case O(1) search space used O(m) static set of elements n = m2 ...
... Perfect hashing Goal: worst-case O(1) search space used O(m) static set of elements n = m2 ...
Notes 33 Royden
... •Index functions are not always simple functions that compute an integer value from integer inputs. ...
... •Index functions are not always simple functions that compute an integer value from integer inputs. ...
Power Point 2000
... Basic idea: each table entry is associated with multiple (key, value) pairs Sequentially look through those pairs + incremental growth of the table - poor performance when an entry is associated with too many (key, value) pairs ...
... Basic idea: each table entry is associated with multiple (key, value) pairs Sequentially look through those pairs + incremental growth of the table - poor performance when an entry is associated with too many (key, value) pairs ...
Split-Ordered Lists: Lock-Free Extensible Hash Tables
... bits (LSB) of the key determines the bucket. It turns out that the so called recursive split-ordering is achieved by binary reversal of the keys. For example, the split-order of key 13 is reverse(1310 ) = reverse(000011012 ) = 101100002 , as shown in Figure 1. For technical reasons, it is convenient ...
... bits (LSB) of the key determines the bucket. It turns out that the so called recursive split-ordering is achieved by binary reversal of the keys. For example, the split-order of key 13 is reverse(1310 ) = reverse(000011012 ) = 101100002 , as shown in Figure 1. For technical reasons, it is convenient ...
word - Courses
... given input k should always produce the same output h(k ) . Since U m , and in general U is much larger than m, there must be at least two keys that have the same hash value, and therefore avoiding collisions altogether is impossible. Thus, while a well designed random looking hash function can mi ...
... given input k should always produce the same output h(k ) . Since U m , and in general U is much larger than m, there must be at least two keys that have the same hash value, and therefore avoiding collisions altogether is impossible. Thus, while a well designed random looking hash function can mi ...
HashingFinal
... • Polynomial accumulation: for strings of a natural language, combine the character values (ASCII or Unicode) a 0 a 1 ... a n-1 by viewing them as the coefficients of a polynomial: a 0 + a 1 x + ...+ a n-1 x n-1 • For instance, choosing x = 33, 37, 39, or 41 gives at most 6 collisions on a vocabular ...
... • Polynomial accumulation: for strings of a natural language, combine the character values (ASCII or Unicode) a 0 a 1 ... a n-1 by viewing them as the coefficients of a polynomial: a 0 + a 1 x + ...+ a n-1 x n-1 • For instance, choosing x = 33, 37, 39, or 41 gives at most 6 collisions on a vocabular ...
Data Structures (810:052) Lab 11 - Hashing Name:_________________
... function. A perfect hash function would take your set of target values and map each to a unique list/array index. Unfortunately, perfect hash functions are a rarity, so in general two or more target values might get mapped to the same hash-table index, called a collision. Collisions are handled by t ...
... function. A perfect hash function would take your set of target values and map each to a unique list/array index. Unfortunately, perfect hash functions are a rarity, so in general two or more target values might get mapped to the same hash-table index, called a collision. Collisions are handled by t ...
notes
... • The key is usually a number, but can be a string or any other data type. – Non-numbers are converted to numbers when applying hashing. ...
... • The key is usually a number, but can be a string or any other data type. – Non-numbers are converted to numbers when applying hashing. ...
CS 61B Data Structures and Programming Methodology
... – Unfortunately, declaring an array of length 2645 is out of the question. – English has fewer than one million words, so we should be able to do better. ...
... – Unfortunately, declaring an array of length 2645 is out of the question. – English has fewer than one million words, so we should be able to do better. ...
Rainbow table
A rainbow table is a precomputed table for reversing cryptographic hash functions, usually for cracking password hashes. Tables are usually used in recovering a plaintext password up to a certain length consisting of a limited set of characters. It is a practical example of a space/time trade-off, using less computer processing time and more storage than a brute-force attack which calculates a hash on every attempt, but more processing time and less storage than a simple lookup table with one entry per hash. Use of a key derivation function that employs a salt makes this attack infeasible.Rainbow tables are an application of an earlier, simpler algorithm by Martin Hellman.
