Engineering a Sorted List Data Structure for 32 Bit Keys
... Our Stree is fastest over the entire range of inputs. For small n, it is much faster than comparison based structures up to a factor of 4.1. For random inputs of this size, locate mostly accesses the root-top data structure which fits in cache and hence is very fast. It even gets faster with increas ...
... Our Stree is fastest over the entire range of inputs. For small n, it is much faster than comparison based structures up to a factor of 4.1. For random inputs of this size, locate mostly accesses the root-top data structure which fits in cache and hence is very fast. It even gets faster with increas ...
The Pigeonhole Principle and Hashing
... Hashing and Association Tables (Maps, Dictionaries) A dictionary (or map or association table) is a collection of keyvalue pairs. In general, the objects in a table have no fixed order and each object is accessed by using the associated key. For example, we could have a table of motor vehicle drive ...
... Hashing and Association Tables (Maps, Dictionaries) A dictionary (or map or association table) is a collection of keyvalue pairs. In general, the objects in a table have no fixed order and each object is accessed by using the associated key. For example, we could have a table of motor vehicle drive ...
Data Structures 1
... • Performance: O(n) => slow Would it be better to keep the nodes sorted by key? ...
... • Performance: O(n) => slow Would it be better to keep the nodes sorted by key? ...
Midterm Solutions
... the largest key less than or equal to a given key in logarithmic time. This is the floor function. I. Design a priority queue implementation that performs insert, 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 viola ...
... the largest key less than or equal to a given key in logarithmic time. This is the floor function. I. Design a priority queue implementation that performs insert, 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 viola ...
Programming for GCSE - Teaching London Computing
... Data Structures? “I will, in fact, claim that the difference between a bad programmer and a good one is whether he considers his code or his data structures more important. Bad programmers worry about the code. Good programmers worry about data structures and their relationships.” Linus Torvalds, 2 ...
... Data Structures? “I will, in fact, claim that the difference between a bad programmer and a good one is whether he considers his code or his data structures more important. Bad programmers worry about the code. Good programmers worry about data structures and their relationships.” Linus Torvalds, 2 ...
Data Structures
... Data Structures Used by Collections How data is stored affects how efficiently it is accessed and modified. Where many items of data are related to each other it is usually most efficient to store them together in some form of structure. Different data structures have different characteristics; whic ...
... Data Structures Used by Collections How data is stored affects how efficiently it is accessed and modified. Where many items of data are related to each other it is usually most efficient to store them together in some form of structure. Different data structures have different characteristics; whic ...
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 ...
MapADT_HashTables
... Hashing involves transforming data to produce an integer in a fixed range (0..TABLE_SIZE-1) The function that transforms the key into an array index is known as the hash function When two data values produce the same hash value, you get a collision—it happens! Collision resolution may be don ...
... Hashing involves transforming data to produce an integer in a fixed range (0..TABLE_SIZE-1) The function that transforms the key into an array index is known as the hash function When two data values produce the same hash value, you get a collision—it happens! Collision resolution may be don ...
HashTables - University of Arizona
... to store the table as an array of linked lists and to keep at each array index the list of values that yield that hash value known as separate chaining Most often the data stored in a hash table includes both a key field and a data field (e.g., social security number and student information). Th ...
... to store the table as an array of linked lists and to keep at each array index the list of values that yield that hash value known as separate chaining Most often the data stored in a hash table includes both a key field and a data field (e.g., social security number and student information). Th ...
Lecture Note 10
... – Find record/empty slot starting at index = h(key) (use resolution policy if necessary) ...
... – Find record/empty slot starting at index = h(key) (use resolution policy if necessary) ...
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... (b) Must partition only 7 times total. Each partition takes linear time. 5. Heaps and Priority Queues. a. – V J R E J G F F B F E A E B D b. Heapification is linear time. Best algorithm is to use ‘bottom up heapifi ...
... (b) Must partition only 7 times total. Each partition takes linear time. 5. Heaps and Priority Queues. a. – V J R E J G F F B F E A E B D b. Heapification is linear time. Best algorithm is to use ‘bottom up heapifi ...
Hashing / Hash tables
... • Goal: To eliminate the primary clustering problem of linear probing • Strategy: by examining certain cells away from the original probe point when a collision occurs using F(i) = i2 Let H = h(k). If H is occupied and not equal to k, search H+1, H+22, H+32, …, until found or all possible locations ...
... • Goal: To eliminate the primary clustering problem of linear probing • Strategy: by examining certain cells away from the original probe point when a collision occurs using F(i) = i2 Let H = h(k). If H is occupied and not equal to k, search H+1, H+22, H+32, …, until found or all possible locations ...
Lecture 20 - Ece.umd.edu
... equipment called programmers is needed to carry out the programming of a PLD. ...
... equipment called programmers is needed to carry out the programming of a PLD. ...
D amortized analysis binomial heaps Fibonacci heaps
... Abstract. A powerful technique in the complexity analysis of data structures is amortization, or averaging over time. Amortized running time is a realistic but robust complexity measure for which we can obtain surprisingly tight upper and lower bounds on a variety of algorithms. By following the pri ...
... Abstract. A powerful technique in the complexity analysis of data structures is amortization, or averaging over time. Amortized running time is a realistic but robust complexity measure for which we can obtain surprisingly tight upper and lower bounds on a variety of algorithms. By following the pri ...
LanguageProcessor
... • Search data structures are used during language processing to maintain attribute information concerning different entities in the source program. • Key field is symbol field containing the name of an entity. • Entry format: Set of fields Common for entry. Entry format types: 1. Fixed length entrie ...
... • Search data structures are used during language processing to maintain attribute information concerning different entities in the source program. • Key field is symbol field containing the name of an entity. • Entry format: Set of fields Common for entry. Entry format types: 1. Fixed length entrie ...
Modular interprocedural pointer analysis using access paths
... a measure of correctness for getting the required information from pointer analysis. for pointer analysis, the required information is: whether two pointers are aliases or non-aliases. dynamic analysis is precise with respect to that execution. ...
... a measure of correctness for getting the required information from pointer analysis. for pointer analysis, the required information is: whether two pointers are aliases or non-aliases. dynamic analysis is precise with respect to that execution. ...
Control table
Control tables are tables that control the control flow or play a major part in program control. There are no rigid rules about the structure or content of a control table—its qualifying attribute is its ability to direct control flow in some way through ""execution"" by a processor or interpreter. The design of such tables is sometimes referred to as table-driven design (although this typically refers to generating code automatically from external tables rather than direct run-time tables). In some cases, control tables can be specific implementations of finite-state-machine-based automata-based programming. If there are several hierarchical levels of control table they may behave in a manner equivalent to UML state machinesControl tables often have the equivalent of conditional expressions or function references embedded in them, usually implied by their relative column position in the association list. Control tables reduce the need for programming similar structures or program statements over and over again. The two-dimensional nature of most tables makes them easier to view and update than the one-dimensional nature of program code. In some cases, non-programmers can be assigned to maintain the control tables.