Java Structures: Data Structures for the Principled Programmer

... larger programs in Python. In more significant programs there begins to be a concern about how to structure and manipulate the data for efficient access. Python enjoys a rich set of data types for holding data—arrays, lists, dictionaries, and others—but our eventual focus will be what to do when the ...

... larger programs in Python. In more significant programs there begins to be a concern about how to structure and manipulate the data for efficient access. Python enjoys a rich set of data types for holding data—arrays, lists, dictionaries, and others—but our eventual focus will be what to do when the ...

Base Table - People.csail.mit.edu

... This manual is for SLIB (version 3b4, May 2013), the portable Scheme library. c 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, Copyright 2006, 2007, 2008 Free Software Foundation, Inc. Permission is granted to copy, distribute and/or modify this document under the t ...

... This manual is for SLIB (version 3b4, May 2013), the portable Scheme library. c 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, Copyright 2006, 2007, 2008 Free Software Foundation, Inc. Permission is granted to copy, distribute and/or modify this document under the t ...

A Practical Introduction to Data Structures and Algorithm

... 2. Related to costs and benefits is the notion of tradeoffs. For example, it is quite common to reduce time requirements at the expense of an increase in space requirements, or vice versa. Programmers face tradeoff issues regularly in all phases of software design and implementation, so the concept ...

... 2. Related to costs and benefits is the notion of tradeoffs. For example, it is quite common to reduce time requirements at the expense of an increase in space requirements, or vice versa. Programmers face tradeoff issues regularly in all phases of software design and implementation, so the concept ...

LSH Forest: Self-Tuning Indexes for Similarity Search

... The solution is to develop indexes that, given any query, will select only a small set of “candidate” objects to compare the query against. The “best” indexes have the following properties: A Accuracy: The set of candidates retrieved by the index should contain the most similar objects to the query. ...

... The solution is to develop indexes that, given any query, will select only a small set of “candidate” objects to compare the query against. The “best” indexes have the following properties: A Accuracy: The set of candidates retrieved by the index should contain the most similar objects to the query. ...

I n - Computer Science at Virginia Tech

... Asymptotic Analysis: Big-oh Definition: For T(n) a non-negatively valued function, T(n) is in the set O(f(n)) if there exist two positive constants c and n0 such that T(n) <= cf(n) for all n > n0. Usage: The algorithm is in O(n2) in [best, average, worst] case. Meaning: For all data sets big enough ...

... Asymptotic Analysis: Big-oh Definition: For T(n) a non-negatively valued function, T(n) is in the set O(f(n)) if there exist two positive constants c and n0 such that T(n) <= cf(n) for all n > n0. Usage: The algorithm is in O(n2) in [best, average, worst] case. Meaning: For all data sets big enough ...

I n - Read

... Asymptotic Analysis: Big-oh Definition: For T(n) a non-negatively valued function, T(n) is in the set O(f(n)) if there exist two positive constants c and n0 such that T(n) <= cf(n) for all n > n0. Usage: The algorithm is in O(n2) in [best, average, worst] case. Meaning: For all data sets big enough ...

... Asymptotic Analysis: Big-oh Definition: For T(n) a non-negatively valued function, T(n) is in the set O(f(n)) if there exist two positive constants c and n0 such that T(n) <= cf(n) for all n > n0. Usage: The algorithm is in O(n2) in [best, average, worst] case. Meaning: For all data sets big enough ...

Data Structures and Algorithms with JavaScript

... An example of a data structure that leads to efficient algorithms is the binary search tree (BST). A binary search tree is designed so that it is easy to find the minimum and maximum values of a set of data, yielding an algorithm that is more efficient than the best search algorithms available. Prog ...

... An example of a data structure that leads to efficient algorithms is the binary search tree (BST). A binary search tree is designed so that it is easy to find the minimum and maximum values of a set of data, yielding an algorithm that is more efficient than the best search algorithms available. Prog ...

Open Data Structures (in C++)

... Processor speeds: At the time of writing, even a very fast desktop computer can not do more than one billion (109 ) operations per second.1 This 1 Computer speeds are at most a few gigahertz (billions of cycles per second), and each operation typically takes a few cycles. ...

... Processor speeds: At the time of writing, even a very fast desktop computer can not do more than one billion (109 ) operations per second.1 This 1 Computer speeds are at most a few gigahertz (billions of cycles per second), and each operation typically takes a few cycles. ...

Open Data Structures (in Java)

... Processor speeds: At the time of writing, even a very fast desktop computer can not do more than one billion (109 ) operations per second.1 This 1 Computer speeds are at most a few gigahertz (billions of cycles per second), and each operation typically takes a few cycles. ...

... Processor speeds: At the time of writing, even a very fast desktop computer can not do more than one billion (109 ) operations per second.1 This 1 Computer speeds are at most a few gigahertz (billions of cycles per second), and each operation typically takes a few cycles. ...

SMALTA: Practical and Near

... SMALTA at the IETF [19] drawing significant community interest, and will continue our work to publish SMALTA as an informational RFC. In all, we find that SMALTA shrinks FIB memory by about one-half. This leads to a roughly 25% improvement in the number of memory accesses for FIB lookup. This also e ...

... SMALTA at the IETF [19] drawing significant community interest, and will continue our work to publish SMALTA as an informational RFC. In all, we find that SMALTA shrinks FIB memory by about one-half. This leads to a roughly 25% improvement in the number of memory accesses for FIB lookup. This also e ...

Open Data Structures (in C++)

... There are plenty of books that teach introductory data structures. Some of them are very good. Most of them cost money, and the vast majority of computer science undergraduate students will shell-out at least some cash on a data structures book. There are a few free data structures books available o ...

... There are plenty of books that teach introductory data structures. Some of them are very good. Most of them cost money, and the vast majority of computer science undergraduate students will shell-out at least some cash on a data structures book. There are a few free data structures books available o ...

Evaluating Data Structures for RuntimeStorage of Aspect Instances

... potentially many different places in the code, into separated modules called aspects. An aspect describes the behavioural effect1 of the crosscutting concern on the base program. In many cases the code that implements the functionality of the crosscutting concern needs to access state which is share ...

... potentially many different places in the code, into separated modules called aspects. An aspect describes the behavioural effect1 of the crosscutting concern on the base program. In many cases the code that implements the functionality of the crosscutting concern needs to access state which is share ...

Screen PDF - Open Data Structures

... Processor speeds: At the time of writing, even a very fast desktop computer can not do more than one billion (109 ) operations per second.1 This 1 Computer speeds are at most a few gigahertz (billions of cycles per second), and each operation typically takes a few cycles. ...

... Processor speeds: At the time of writing, even a very fast desktop computer can not do more than one billion (109 ) operations per second.1 This 1 Computer speeds are at most a few gigahertz (billions of cycles per second), and each operation typically takes a few cycles. ...

Fundamental Data Structures

... Functional ADT definitions Another way to define an ADT, closer to the spirit of functional programming, is to consider each state of the structure as a separate entity. In this view, any operation that modifies the ADT is modeled as a mathematical function that takes the old state as an argument, a ...

... Functional ADT definitions Another way to define an ADT, closer to the spirit of functional programming, is to consider each state of the structure as a separate entity. In this view, any operation that modifies the ADT is modeled as a mathematical function that takes the old state as an argument, a ...

Join processing in relational databases

... are identical in all re spects. Thus, one set of join attributes in the result relation can be removed without any loss of information. Certainly, ...

... are identical in all re spects. Thus, one set of join attributes in the result relation can be removed without any loss of information. Certainly, ...

2-7 The Mathematics Models and an Actual Proof Experiment

... of FPR by this system. The rate of false detection due to “a” or “b” can be calculated in the same manner as in the ICMP method. 3.1.3 HASH method (1) Overview of evaluated system’s processing procedure As a HASH method, we evaluated an SPIE system described in a different paper［3］. In this system, ...

... of FPR by this system. The rate of false detection due to “a” or “b” can be calculated in the same manner as in the ICMP method. 3.1.3 HASH method (1) Overview of evaluated system’s processing procedure As a HASH method, we evaluated an SPIE system described in a different paper［3］. In this system, ...

Fundamental Data Structures - University of North Florida

... Functional ADT definitions Another way to define an ADT, closer to the spirit of functional programming, is to consider each state of the structure as a separate entity. In this view, any operation that modifies the ADT is modeled as a mathematical function that takes the old state as an argument, a ...

... Functional ADT definitions Another way to define an ADT, closer to the spirit of functional programming, is to consider each state of the structure as a separate entity. In this view, any operation that modifies the ADT is modeled as a mathematical function that takes the old state as an argument, a ...

Functional Programming

... ▫ List the syntax mappings between Lisp and C (or any other languages that you are familiar with) as many as possible ▫ Illustrate what happened while removing the root node (5) of the tree in page 25 by the algorithm introduced in our class. If the resulting tree is wrong (not a BST), explain why ▫ ...

... ▫ List the syntax mappings between Lisp and C (or any other languages that you are familiar with) as many as possible ▫ Illustrate what happened while removing the root node (5) of the tree in page 25 by the algorithm introduced in our class. If the resulting tree is wrong (not a BST), explain why ▫ ...

Fast Local Searches and Updates in Bounded Universes

... to that element’s successor. This pointer is then used to insert the element into the skip list. We then insert the appropriate prefixes of the element into the hash tables and the corresponding y-fast tries. The y-fast tries may need to be restructured as the buckets increase in size. The key obser ...

... to that element’s successor. This pointer is then used to insert the element into the skip list. We then insert the appropriate prefixes of the element into the hash tables and the corresponding y-fast tries. The y-fast tries may need to be restructured as the buckets increase in size. The key obser ...

Abstract Efficient Data Structures for Tamper-Evident Logging

... event syslog trace at 1,750 events per second using a single CPU core. Performance improves to 10,500 events per second if cryptographic signatures are offloaded, corresponding to 1.1 TB of logging throughput per week. ...

... event syslog trace at 1,750 events per second using a single CPU core. Performance improves to 10,500 events per second if cryptographic signatures are offloaded, corresponding to 1.1 TB of logging throughput per week. ...

Fast Local Searches and Updates in Bounded Universes

... primary reason this is difficult is that each hash table must maintain the appropriate prefixes of the elements in the subtrees rooted at that level. In order to overcome this, we will use an indirection trick similar to that used by y-fast tries, but instead maintain a single skip list [10]. This s ...

... primary reason this is difficult is that each hash table must maintain the appropriate prefixes of the elements in the subtrees rooted at that level. In order to overcome this, we will use an indirection trick similar to that used by y-fast tries, but instead maintain a single skip list [10]. This s ...

Fundamental Data Structures

... How it works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...

... How it works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...

Chapter 4 Index Structures

... Until this point we have supposed that the search key, upon which the index is based, was also a key of the relation, so there could be at most one recoid with any key value. However, indexes are often used for nonkey attributes, so it is possible that more than one record has a given key value. If ...

... Until this point we have supposed that the search key, upon which the index is based, was also a key of the relation, so there could be at most one recoid with any key value. However, indexes are often used for nonkey attributes, so it is possible that more than one record has a given key value. If ...

Optimal Shortest Path Queries in a Simple Polygon

... problem specifies the object to be moved, a set of obstacles, and a pair of locations. A solution to the problem is a minimum-length path for the object that connects the two locations and avoids the obstacles. There are many possible versions of the problem; this paper focusses on what is perhaps t ...

... problem specifies the object to be moved, a set of obstacles, and a pair of locations. A solution to the problem is a minimum-length path for the object that connects the two locations and avoids the obstacles. There are many possible versions of the problem; this paper focusses on what is perhaps t ...

# 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.