COS 226 Final Exam Review Fall 2015 Ananda
... – Since 15 and 25 can be represented using 5 bits, we need only 10 bits to represent a total of 15+25 = 40 bits. A compression ratio of 10/40 = 25% Under what circumstances would you use this algorithm? – A great algorithm when sending FAX, lots of white spaces (0’s) leading to long patterns of 0 If ...
... – Since 15 and 25 can be represented using 5 bits, we need only 10 bits to represent a total of 15+25 = 40 bits. A compression ratio of 10/40 = 25% Under what circumstances would you use this algorithm? – A great algorithm when sending FAX, lots of white spaces (0’s) leading to long patterns of 0 If ...
A Comparison and Selection on Basic Type of Searching Algorithm
... 2. For I=0 to length[A] //scan on element start to end 3. If (SE = =A [I]) //check on searching element 4. L=L+1 // increment on location variable 5. Return A[I] //print on finding element 6. END If 7. END For LOOP 8. If L=0 then return “not find out element” 9.Exit ...
... 2. For I=0 to length[A] //scan on element start to end 3. If (SE = =A [I]) //check on searching element 4. L=L+1 // increment on location variable 5. Return A[I] //print on finding element 6. END If 7. END For LOOP 8. If L=0 then return “not find out element” 9.Exit ...
relational databases SQL example: create, describe, insert, select
... • a table can be thought of as a spreadsheet, where the fields are columns in the spreadsheet, and the records are rows • records can have “unique” fields, which are called keys • if a record does not have a value for a particular field, then a NULL value is entered • “relational” databases consist ...
... • a table can be thought of as a spreadsheet, where the fields are columns in the spreadsheet, and the records are rows • records can have “unique” fields, which are called keys • if a record does not have a value for a particular field, then a NULL value is entered • “relational” databases consist ...
Lists, sets and iterators
... efficient random access to any part of the array (accessing the thousandth element in an array is as efficient as accessing the first) whereas lists are designed for serial access (accessing the first element is the most efficient operation, whereas to access the thousandth element in a list we must ...
... efficient random access to any part of the array (accessing the thousandth element in an array is as efficient as accessing the first) whereas lists are designed for serial access (accessing the first element is the most efficient operation, whereas to access the thousandth element in a list we must ...
Streaming Algorithms - Computer Science, Stony Brook University
... Given: ■ |S| keys to filter; will be mapped to |B| bits ■ hashes = h1, h2, …, hk independent hash functions Algorithm ■ Set all B to 0 For each i in hashes, for each s in S: Set B[hi (s)] = 1 … #usually embedded in other code ■ while key x arrives next in stream ● if B[hi (s)] == 1 all i in hashes: ...
... Given: ■ |S| keys to filter; will be mapped to |B| bits ■ hashes = h1, h2, …, hk independent hash functions Algorithm ■ Set all B to 0 For each i in hashes, for each s in S: Set B[hi (s)] = 1 … #usually embedded in other code ■ while key x arrives next in stream ● if B[hi (s)] == 1 all i in hashes: ...
chap09
... • Definition: A comparison-based search algorithm performs its search by repeatedly comparing the target element to the list elements. • Theorem: Let L be a list of size n > 1. Suppose that the elements of L are sorted. If SRH(n) denotes the minimum number of comparisons needed, in the worst case, b ...
... • Definition: A comparison-based search algorithm performs its search by repeatedly comparing the target element to the list elements. • Theorem: Let L be a list of size n > 1. Suppose that the elements of L are sorted. If SRH(n) denotes the minimum number of comparisons needed, in the worst case, b ...
MAT 114 Distributions Worksheet Key 1. A machine is used to put
... This time we need to first read from the table to get the z- score. The scores do not fall exactly on values on the tables, so it requires a little guesswork. Answers may therefore be different to mine; but they should be close. To convert from z-score to actual value, reverse the process used in pa ...
... This time we need to first read from the table to get the z- score. The scores do not fall exactly on values on the tables, so it requires a little guesswork. Answers may therefore be different to mine; but they should be close. To convert from z-score to actual value, reverse the process used in pa ...
ADT Dictionaries and Hashing
... Double Hashing (1) Use one hash function to determine the first slot. (2) Use a second hash function to determine the increment for the probe sequence: h(k,i) = (h1(k) + i h2(k) ) mod m, i=0,1,... • Initial probe: h1(k) • Second probe is offset by h2(k) mod m, so on ... • Advantage: handles cluster ...
... Double Hashing (1) Use one hash function to determine the first slot. (2) Use a second hash function to determine the increment for the probe sequence: h(k,i) = (h1(k) + i h2(k) ) mod m, i=0,1,... • Initial probe: h1(k) • Second probe is offset by h2(k) mod m, so on ... • Advantage: handles cluster ...
Ecient Index Maintenance Under Dynamic Genome
... the data structure. A link directly to this element may bubble up to higher levels in the skip list with some probability (we set this to be 0.5 at each level). The nodes in the bottom level of the skip list store the location of the edit with respect to the initial reference, and are ordered by th ...
... the data structure. A link directly to this element may bubble up to higher levels in the skip list with some probability (we set this to be 0.5 at each level). The nodes in the bottom level of the skip list store the location of the edit with respect to the initial reference, and are ordered by th ...
IP puzzles probabilistic networking and other projects at
... Finer control of difficulty Support O(210+211) difficulty? One 11-bit hash = too easy One 12-bit hash = too hard One 10-bit hash and one 11-bit hash = just right ...
... Finer control of difficulty Support O(210+211) difficulty? One 11-bit hash = too easy One 12-bit hash = too hard One 10-bit hash and one 11-bit hash = just right ...
Review handout
... of these pre-existing methods in a super class, JAVA won't know which method to execute. However, Java does allow a class to implement more than one interface. Why don't interfaces have the same problem with method ambiguity that classes do? Questions on recursion Q1. Give a recursive algorithm for ...
... of these pre-existing methods in a super class, JAVA won't know which method to execute. However, Java does allow a class to implement more than one interface. Why don't interfaces have the same problem with method ambiguity that classes do? Questions on recursion Q1. Give a recursive algorithm for ...
Algorithms for Nearest Neighbor Search
... Variants of nearest neighbor • Near neighbor (range search): find one/all points in P within distance r from q • Spatial join: given two sets P,Q, find all pairs p in P, q in Q, such that p is within distance r from q • Approximate near neighbor: find one/all points p’ in P, whose distance to q is ...
... Variants of nearest neighbor • Near neighbor (range search): find one/all points in P within distance r from q • Spatial join: given two sets P,Q, find all pairs p in P, q in Q, such that p is within distance r from q • Approximate near neighbor: find one/all points p’ in P, whose distance to q is ...
Advanced Data Structure
... Suppose we need to store values between 0 and 99, but only have an array with 10 cells We can map the values [0,99] to [0,9] by taking modulo 10. The result is the “Hash Value” Adding, finding and removing an element are O(1) It is even possible to map the strings to integers, e.g. “ATE” to (1*26*26 ...
... Suppose we need to store values between 0 and 99, but only have an array with 10 cells We can map the values [0,99] to [0,9] by taking modulo 10. The result is the “Hash Value” Adding, finding and removing an element are O(1) It is even possible to map the strings to integers, e.g. “ATE” to (1*26*26 ...
B - Simon Fraser University
... Can manage growing number of buckets without wasting too much space. Assume that directory fits into main memory. Never need to access more than one data block (as long as there are no overflow chains) for a query. Doubling the directory is a very expensive operation. Interrupts other operations and ...
... Can manage growing number of buckets without wasting too much space. Assume that directory fits into main memory. Never need to access more than one data block (as long as there are no overflow chains) for a query. Doubling the directory is a very expensive operation. Interrupts other operations and ...
Dictionary Data Structures
... In Dijkstra’s original implementation, the Open list is a plain array of nodes together with a bitvector indicating if elements are currently open or not. The minimum is found through a complete scan, yielding quadratic execution time in the number of nodes. More refined data structures have been de ...
... In Dijkstra’s original implementation, the Open list is a plain array of nodes together with a bitvector indicating if elements are currently open or not. The minimum is found through a complete scan, yielding quadratic execution time in the number of nodes. More refined data structures have been de ...
2013S
... a) Show by a suitable example, how constructors are called in a multilevel inheritance. b) Why do we require pure virtual function? Explain giving a suitable example. (8M+8M) ...
... a) Show by a suitable example, how constructors are called in a multilevel inheritance. b) Why do we require pure virtual function? Explain giving a suitable example. (8M+8M) ...
Fact table - WordPress.com
... de-normalized into dimension and fact tables which are typical to a data warehouse database design. The differences in the database architectures are caused by different purposes of their existence. In a typical OLTP system the database performance is crucial, as end-user interface responsiveness is ...
... de-normalized into dimension and fact tables which are typical to a data warehouse database design. The differences in the database architectures are caused by different purposes of their existence. In a typical OLTP system the database performance is crucial, as end-user interface responsiveness is ...
Database Systems: Design, Implementation, and
... variable length column with a fixed length. If the length of the data is less than the maximum length of the field, then the field is not padded with spaces. • maximum length of the column = 2000. e.g: a customer’s first name - VARCHAR2(35) since name length is variable. ...
... variable length column with a fixed length. If the length of the data is less than the maximum length of the field, then the field is not padded with spaces. • maximum length of the column = 2000. e.g: a customer’s first name - VARCHAR2(35) since name length is variable. ...
Crawling the Web Web Crawling
... – not flood servers • expect many pages to visit on one server ...
... – not flood servers • expect many pages to visit on one server ...
Midterm Solutions
... max, and delete-max in ∼ 31 lg N compares per operation, where N is the number of comparable keys in the data structure. This would violate the ∼ N lg N lower bound for sorting because you can sort an array by inserting N keys into a maximumoriented priority queue and deleting the maximum N times. P ...
... max, and delete-max in ∼ 31 lg N compares per operation, where N is the number of comparable keys in the data structure. This would violate the ∼ N lg N lower bound for sorting because you can sort an array by inserting N keys into a maximumoriented priority queue and deleting the maximum N times. P ...
Midterm1Spring07Key
... a. Data structures differ mainly in the amount of storage required b. A queue is a restricted version of a list c. Elements are removed from a stack in reverse order of insertion d. Sets may contain duplicate elements e. Maps may contain more keys than values f. A key may be used to retrieve multipl ...
... a. Data structures differ mainly in the amount of storage required b. A queue is a restricted version of a list c. Elements are removed from a stack in reverse order of insertion d. Sets may contain duplicate elements e. Maps may contain more keys than values f. A key may be used to retrieve multipl ...
Algoritmos y Programacion II
... — an expensive operation, one that may not even be possible if memory is fragmented. Similarly, an array from which many elements are removed may have to be resized in order to avoid wasting too much space. On the other hand, dynamic arrays (as well as fixed-size array data structures) allow constan ...
... — an expensive operation, one that may not even be possible if memory is fragmented. Similarly, an array from which many elements are removed may have to be resized in order to avoid wasting too much space. On the other hand, dynamic arrays (as well as fixed-size array data structures) allow constan ...
Lecture 12 : Identity and Equality I
... of computer science. A hash table is a representation for a mapping: an abstract data type that maps keys to values. Hash tables offer constant time lookup, so they tend to perform better than trees or lists. Keys don’t have to be ordered, or have any particular property, except for offering equals an ...
... of computer science. A hash table is a representation for a mapping: an abstract data type that maps keys to values. Hash tables offer constant time lookup, so they tend to perform better than trees or lists. Keys don’t have to be ordered, or have any particular property, except for offering equals an ...
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.