DataStructuresandAlgorithms-for-Big-Databases大数据库数据结构与算法资料讲解
Data Structures and Algorithms
Divide and conquer is a powerful approach for solving conceptually difficult problems. Divide and conquer approach requires you to find a way of:
Multiple algorithms can be designed to solve a particular problem. An algorithm that provides the maximum efficiency should be used for solving the problem.
Data Structures and Algorithms
Rationale
Computer science is a field of study that deals with solving a variety of problems by using computers.
To solve a given problem by using computers, you need to design an algorithm for it.
Finding the shortest distance from an originating city to a set of destination cities, given the distances between the pairs of cities. Finding the minimum number of currency notes required for an amount, where an arbitrary number of notes for each denomination are available. Selecting items with maximum value from a given set of items, where the total weight of the selected items cannot exceed a given value.
Data Structures Ch 2
end of the list is reached. What is the Big O? Is it reasonable?
Better solution: Cut, cut, and cut some more
Start at or near the middle of the list
Solving the traveling salesman problem via brute-force search; generating all unrestricted permutations of a poset; finding the determinant with expansion by minors.
If what you find is greater or smaller than X, go to the middle of the correct direction and repeat until found or finished.
What is the Big O? Is it superior?
common denominator (GCD) of two values.
The basis of the algorithm requires repeatedly calculating
remainders until a remainder of 0 is reaБайду номын сангаасhed. The last non-zero remainder is the GCD.
Data Structures and Algorithm Analysis in C CS222
Chapter 2: Algorithm Analysis
数据结构与算法分析：C语言描述（原书第2版简体中文版！！！）PDF+源代码+习题答案
数据结构与算法分析：C语⾔描述（原书第2版简体中⽂版！！！）PDF+源代码+习题答案转⾃：/Linux/2014-04/99735.htm数据结构与算法分析：C语⾔描述（原书第2版中⽂版！！！） PDF+源代码+习题答案数据结构与算法分析：C语⾔描述（原书第2版）是《data structures and algorithm analysis in c》⼀书第2版的简体中译本。
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在本书中，作者更加精炼并强化了他对算法和数据结构⽅⾯创新的处理⽅法。
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数据结构与算法分析：C语⾔描述（原书第2版） PDF下载：百度⽹盘免费下载地址：（本⼈是从这⾥下载的，感谢原博主）全书特点如下： ●专⽤⼀章来讨论算法设计技巧，包括贪婪算法、分治算法、动态规划、随机化算法以及回溯算法 ●介绍了当前流⾏的论题和新的数据结构，如斐波那契堆、斜堆、⼆项队列、跳跃表和伸展树 ●安排⼀章专门讨论摊还分析，考查书中介绍的⼀些⾼级数据结构 ●新开辟⼀章讨论⾼级数据结构以及它们的实现，其中包括红⿊树、⾃顶向下伸展树。
treap树、k-d树、配对堆以及其他相关内容 ●合并了堆排序平均情况分析的⼀些新结果⽬录出版者的话专家指导委员会译者序前⾔第1章引论第2章算法分析第3章表、栈和队列第4章树第5章散列第6章优先队列（堆）第7章排序第8章不相交集ADT第9章图论算法第10章算法设计技巧第11章摊还分析第12章⾼级数据结构及其实现索引。
川大软件数据结构选择题库
Chapter 1 Data Structures and Algorithms: Instructor's CD questions1. The primary purpose of most computer programs isa) to perform a mathematical calculation.*b) to store and retrieve information.c) to sort a collection of records.d) all of the above.e) none of the above.2. An integer is a*a) simple typeb) aggregate typec) composite typed) a and be) none of the above3. A payroll records is aa) simple typeb) aggregate typec) composite type*d) a and be) none of the above4. Which of the following should NOT be viewed as an ADT?a) listb) integerc) array*d) none of the above5. A mathematical function is most like a*a) Problemb) Algorithmc) Program6. An algorithm must be or do all of the following EXCEPT:a) correctb) composed of concrete steps*c) ambiguousd) composed of a finite number of stepse) terminate7. A solution is efficient ifa. it solves a problem within the require resource constraints.b. it solves a problem within human reaction time.c. it solves a problem faster than other known solutions.d. a and b.*e. a and c.f. b and c.8. An array isa) A contiguous block of memory locations where each memory location stores a fixed-length data item.b) An ADT composed of a homogeneous collection of data items, each data item identified by a particular number.c) a set of integer values.*d) a and b.e) a and c.f) b and c.9. Order the following steps to selecting a data structure to solve a problem.(1) Determine the basic operations to be supported.(2) Quantify the resource constraints for each operation.(3) Select the data structure that best meets these requirements.(4) Analyze the problem to determine the resource constraints that anysolution must meet.a) (1, 2, 3, 4)b) (2, 3, 1, 4)c) (2, 1, 3, 4)*d) (1, 2, 4, 3)e) (1, 4, 3, 2)10. Searching for all those records in a database with key value between 10 and 100 is known as:a) An exact match query.*b) A range query.c) A sequential search.d) A binary search.Chapter 2 Mathematical Preliminaries: Instructor's CD questions1. A set has the following properties:a) May have duplicates, element have a position.b) May have duplicates, elements do not have a position.c) May not have duplicates, elements have a position.*d) May not have duplicates, elements do not have a position.2. A sequence has the following properties:*a) May have duplicates, element have a position.b) May have duplicates, elements do not have a position.c) May not have duplicates, elements have a position.d) May not have duplicates, elements do not have a position.3. For set P, the notation |P| indicates*a) The number of elements in P.b) The inverse of P.c) The powerset of P.d) None of the above.4. Assume that P contains n elements. The number of sets in the powerset of P isa) nb) n^2*c) 2^nd) 2^n - 1e) 2^n + 15. If a sequence has n values, then the number of permutations for that sequence will bea) nb) n^2c) n^2 - 1d) 2^n*e) n!6. If R is a binary relation over set S, then R is reflexive if*a) aRa for all a in S.b) whenever aRb, then bRa, for all a, b in S.c) whenever aRb and bRa, then a = b, for all a, b in S.d) whenever aRb and aRc, then aRc, for all a, b, c in S.7. If R is a binary relation over set S, then R is transitive ifa) aRa for all a in S.b) whenever aRb, then bRa, for all a, b in S.c) whenever aRb and bRa, then a = b, for all a, b in S.*d) whenever aRb and aRc, then aRc, for all a, b, c in S.8. R is an equivalence relation on set S if it is*a) reflexive, symmetric, transitive.b) reflexive, antisymmetric, transitive.c) symmetric, transitive.d) antisymmetric, transitive.e) irreflexive, symmetric, transitive.f) irreflexive, antisymmetric, transitive.9. For the powerset of integers, the subset operation defines*a) a partial order.b) a total order.c) a transitive order.d) none of the above.10. log nm is equal toa) n + m*b) log n + log mc) m log nd) log n - log m11. A close-form solution isa) an analysis for a program.*b) an equation that directly computes the value of a summation.c) a complete solution for a problem.12. Mathematical induction is most likea) iteration.*b) recursion.c) branching.d) divide and conquer.13. A recurrence relation is often used to model programs witha) for loops.b) branch control like "if" statements.*c) recursive calls.d) function calls.14. Which of the following is not a good proof technique.a) proof by contradiction.*b) proof by example.c) proof by mathematical induction.15. We can use mathematical induction to:a) Find a closed-form solution for a summation.*b) Verify a proposed closed-form solution for a summation.c) Both find and verify a closed-form solution for a summation.Chapter 3 Algorithm Analysis: Instructor's CD questions1. A growth rate applies to:a) the time taken by an algorithm in the average case.b) the time taken by an algorithm as the input size grows.c) the space taken by an algorithm in the average case.d) the space taken by an algorithm as the input size grows.e) any resource you wish to measure for an algorithm in the averagecase.*f) any resource you wish to measure for an algorithm as the input size grows.2. Pick the growth rate that corresponds to the most efficient algorithm as n gets large:a) 5n*b) 20 log nc) 2n^2d) 2^n3. Pick the growth rate that corresponds to the most efficient algorithm when n =4.a) 5nb) 20 log nc) 2n^2*d) 2^n4. Pick the quadratic growth rate.a) 5nb) 20 log n*c) 2n^2d) 2^n5. Asymptotic analysis refers to:a) The cost of an algorithm in its best, worst, or average case.*b) The growth in cost of an algorithm as the input size grows towards infinity.c) The size of a data structure.d) The cost of an algorithm for small input sizes6. For an air traffic control system, the most important metric is:a) The best-case upper bound.b) The average-case upper bound.*c) The worst-case upper bound.d) The best-case lower bound.e) The average-case lower bound.f) The worst-case lower bound.7. When we wish to describe the upper bound for a problem we use:*a) The upper bound of the best algorithm we know.b) The lower bound of the best algorithm we know.c) We can't talk about the upper bound of a problem because there canalways be an arbitrarily slow algorithm.8. When we describe the lower bound for a problem we use:a) The upper bound for the best algorithm we know.b) the lower bound for the best algorithm we know.c) The smallest upper bound that we can prove for the best algorithmthat could possibly exist.*d) The greatest lower bound that we can prove for the best algorithm that could possibly exist.9. When the upper and lower bounds for an algorithm are the same, we use:a) big-Oh notation.b) big-Omega notation.*c) Theta notation.d) asymptotic analysis.e) Average case analysis.f) Worst case analysis.10. When performing asymptotic analysis, we can ignore constants and low order terms because:*a) We are measuring the growth rate as the input size gets large.b) We are only interested in small input sizes.c) We are studying the worst case behavior.d) We only need an approximation.11. The best case for an algorithm refers to:a) The smallest possible input size.*b) The specific input instance of a given size that gives the lowest cost.c) The largest possible input size that meets the required growth rate.d) The specific input instance of a given size that gives the greatestcost.12. For any algorithm:*a) The upper and lower bounds always meet, but we might not know what they are.b) The upper and lower bounds might or might not meet.c) We can always determine the upper bound, but might not be able to determine the lower bound.d) We can always determine the lower bound, but might not be able to determine the upper bound.13. If an algorithm is Theta(f(n)) in the average case, then it is:a) Omega(f(n)) in the best case.*b) Omega(f(n)) in the worst case.c) O(f(n)) in the worst case.14. For the purpose of performing algorithm analysis, an important property of a basic operation is that:a) It be fast.b) It be slow enough to measure.c) Its cost does depend on the value of its operands.*d) Its cost does not depend on the value of its operands.15. For sequential search,a) The best, average, and worst cases are asymptotically the same.*b) The best case is asymptotically better than the average and worst cases.c) The best and average cases are asymptotically better than the worst case.d) The best case is asymptotically better than the average case, and the average case is asymptotically better than the worst case.Chapter 4 Lists, Stacks and Queues: Instructor's CD questions1. An ordered list is one in which:a) The element values are in sorted order.*b) Each element a position within the list.2. An ordered list is most like a:a) set.b) bag.*c) sequence.3. As compared to the linked list implementation for lists, thearray-based list implementation requires:a) More spaceb) Less space*c) More or less space depending on how many elements are in the list.4. Here is a series of C++ statements using the list ADT in the book.L1.append(10);L1.append(20);L1.append(15);If these statements are applied to an empty list, the result will look like:a) < 10 20 15 >*b) < | 10 20 15 >c) < 10 20 15 | >d) < 15 20 10 >e) < | 15 20 10 >f) < 15 20 10 | >5. When comparing the array-based and linked implementations, the array-based implementation has:*a) faster direct access to elements by position,but slower insert/delete from the current position.b) slower direct access to elements by position,but faster insert/delete from the current position.c) both faster direct access to elements by position, and faster insert/delete from the current position.d) both slower direct access to elements by position, and slower insert/delete from the current position.6. For a list of length n, the linked-list implementation's prevfunction requires worst-case time:a) O(1).b) O(log n).*c) O(n).d) O(n^2).7. Finding the element in an array-based list with a given key valuerequires worst case time:a) O(1).b) O(log n).*c) O(n).d) O(n^2).8. In the linked-list implementation presented in the book, a headernode is used:*a) To simplify special cases.b) Because the insert and delete routines won't work correctly withoutit.c) Because there would be no other way to make the current pointerindicate the first element on the list.9. When a pointer requires 4 bytes and a data element requires 4bytes, the linked list implementation requires less space than the array-based list implementation when the array would be:a) less than 1/4 full.b) less than 1/3 full.*c) less than half full.d) less than 2/3 full.e) less than 3/4 fullf) never.10. When a pointer requires 4 bytes and a data element requires 12bytes, the linked list implementation requires less space than the array-based list implementation when the array would be:*a) less than 1/4 full.b) less than 1/3 full.c) less than half full.d) less than 2/3 full.e) less than 3/4 fullf) never.11. When we say that a list implementation enforces homogeneity, wemean that:a) All list elements have the same size.*b) All list elements have the same type.c) All list elements appear in sort order.12. When comparing the doubly and singly linked list implementations,we find that the doubly linked list implementation*a) Saves time on some operations at the expense of additional space.b) Saves neither time nor space, but is easier to implement.c) Saves neither time nor space, and is also harder to implement.13. We use a comparator function in the Dictionary class ADT:a) to simplify implementation.*b) to increase the opportunity for code reuse.c) to improve asymptotic efficiency of some functions.14. All operations on a stack can be implemented in constant timeexcept:a) Pushb) Popc) The implementor's choice of push or pop (they cannot both beimplemented in constant time).*d) None of the above.15. Recursion is generally implemented usinga) A sorted list.*b) A stack.c) A queue.Chapter 5 Binary Trees: Instructor's CD questions1. The height of a binary tree is:a) The height of the deepest node.b) The depth of the deepest node.*c) One more than the depth of the deepest node.2. A full binary tree is one in which:*a) Every internal node has two non-empty children.b) all of the levels, except possibly the bottom level, are filled.3. The relationship between a full and a complete binary tree is:a) Every complete binary tree is full.b) Every full binary tree is complete.*c) None of the above.4. The Full Binary Tree Theorem states that:*a) The number of leaves in a non-empty full binary tree is one more than the number of internal nodes.b) The number of leaves in a non-empty full binary tree is one less than the number of internal nodes.c) The number of leaves in a non-empty full binary tree is one half of the number of internal nodes.d) The number of internal nodes in a non-empty full binary tree is one half of the number of leaves.5. The correct traversal to use on a BST to visit the nodes in sortedorder is:a) Preorder traversal.*b) Inorder traversal.c) Postorder traversal.6. When every node of a full binary tree stores a 4-byte data field,two 4-byte child pointers, and a 4-byte parent pointer, theoverhead fraction is approximately:a) one quarter.b) one third.c) one half.d) two thirds.*e) three quarters.f) none of the above.7. When every node of a full binary tree stores an 8-byte data field andtwo 4-byte child pointers, the overhead fraction is approximately:a) one quarter.b) one third.*c) one half.d) two thirds.e) three quarters.f) none of the above.8. When every node of a full binary tree stores a 4-byte data fieldand the internal nodes store two 4-byte child pointers, theoverhead fraction is approximately:a) one quarter.b) one third.*c) one half.d) two thirds.e) three quarters.f) none of the above.9. If a node is at position r in the array implementation for acomplete binary tree, then its parent is at:*a) (r - 1)/2 if r > 0b) 2r + 1 if (2r + 1) < nc) 2r + 2 if (2r + 2) < nd) r - 1 if r is evene) r + 1 if r is odd.10. If a node is at position r in the array implementation for acomplete binary tree, then its right child is at:a) (r - 1)/2 if r > 0b) 2r + 1 if (2r + 1) < n*c) 2r + 2 if (2r + 2) < nd) r - 1 if r is evene) r + 1 if r is odd.11. Assume a BST is implemented so that all nodes in the left subtreeof a given node have values less than that node, and all nodes in the right subtree have values greater than or equal to that node.When implementing the delete routine, we must select as itsreplacement:a) The greatest value from the left subtree.*b) The least value from the right subtree.c) Either of the above.12. Which of the following is a true statement:a) In a BST, the left child of any node is less than the right child,and in a heap, the left child of any node is less than the right child.*b) In a BST, the left child of any node is less than the right child,but in a heap, the left child of any node could be less than or greater than the right child.c) In a BST, the left child of any node could be less or greater than the right child, but in a heap, the left child of any node must beless than the right child.d) In both a BST and a heap, the left child of any node could be either less than or greater than the right child.13. When implementing heaps and BSTs, which is the best answer?a) The time to build a BST of n nodes is O(n log n), and the time to build a heap of n nodes is O(n log n).b) The time to build a BST of n nodes is O(n), and the time tobuild a heap of n nodes is O(n log n).*c) The time to build a BST of n nodes is O(n log n), and the time to build a heap of n nodes is O(n).d) The time to build a BST of n nodes is O(n), and the time tobuild a heap of n nodes is O(n).14. The Huffman coding tree works best when the frequencies forletters area) Roughly the same for all letters.*b) Skewed so that there is a great difference in relative frequencies for various letters.15. Huffman coding provides the optimal coding when:a) The messages are in English.b) The messages are binary numbers.*c) The frequency of occurrence for a letter is independent of its context within the message.d) Never.Chapter 6 Binary Trees: Instructor's CD questions1. The primary ADT access functions used to traverse a general tree are:a) left child and right siblingb) left child and right child*c) leftmost child and right siblingd) leftmost child and next child2. The tree traversal that makes the least sense for a general treeis:a) preorder traversal*b) inorder traversalc) postorder traversal3. The primary access function used to navigate the general tree when performing UNION/FIND is:a) left childb) leftmost childc) right childd) right sibling*e) parent4. When using the weighted union rule for merging disjoint sets, the maximum depth for any node in a tree of size n will be:a) nearly constant*b) log nc) nd) n log ne) n^25. We use the parent pointer representation for general trees to solve which problem?a) Shortest pathsb) General tree traversal*c) Equivalence classesd) Exact-match query6. When using path compression along with the weighted union rule for merging disjoint sets, the average cost for any UNION or FIND operation in a tree of size n will be:*a) nearly constantb) log nc) nd) n log n7. The most space efficient representation for general trees will typically be:a) List of children*b) Left-child/right siblingc) A K-ary tree.8. The easiest way to represent a general tree is to:a) convert to a list.*b) convert to a binary tree.c) convert to a graph.9. As K gets bigger, the ratio of internal nodes to leaf nodes:*a) Gets smaller.b) Stays the same.c) Gets bigger.d) Cannot be determined, since it depends on the particular configuration of the tree.10. A sequential tree representation is best used for:*a) Archiving the tree to disk.b) Use in dynamic in-memory applications.c) Encryption algorithms.d) It is never better than a dynamic representation.Chapter 7 Internal Sorting: Instructor's CD questions1. A sorting algorithm is stable if it:a) Works for all inputs.*b) Does not change the relative ordering of records with identical key values.c) Always sorts in the same amount of time (within a constant factor) for a given input size.2. Which sorting algorithm does not have any practical use?a) Insertion sort.*b) Bubble sort.c) Quicksort.d) Radix Sort.e) a and b.3. When sorting n records, Insertion sort has best-case cost:a) O(log n).c) O(n log n).d) O(n^2)e) O(n!)f) None of the above.4. When sorting n records, Insertion sort has worst-case cost:a) O(log n).b) O(n).c) O(n log n).*d) O(n^2)e) O(n!)f) None of the above.5. When sorting n records, Quicksort has worst-case cost:a) O(log n).b) O(n).c) O(n log n).*d) O(n^2)e) O(n!)f) None of the above.6. When sorting n records, Quicksort has average-case cost:a) O(log n).b) O(n).*c) O(n log n).d) O(n^2)e) O(n!)f) None of the above.7. When sorting n records, Mergesort has worst-case cost:a) O(log n).b) O(n).*c) O(n log n).d) O(n^2)e) O(n!)f) None of the above.8. When sorting n records, Radix sort has worst-case cost:a) O(log n).b) O(n).c) O(n log n).d) O(n^2)e) O(n!)*f) None of the above.9. When sorting n records with distinct keys, Radix sort has a lower bound of:a) Omega(log n).b) Omega(n).*c) Omega(n log n).d) Omega(n^2)e) Omega(n!)f) None of the above.10. Any sort that can only swap adjacent records as an average case lower bound of:a) Omega(log n).b) Omega(n).c) Omega(n log n).*d) Omega(n^2)e) Omega(n!)f) None of the above.11. The number of permutations of size n is:a) O(log n).b) O(n).c) O(n log n).d) O(n^2)*e) O(n!)f) None of the above.12. When sorting n records, Selection sort will perform how many swaps in the worst case?a) O(log n).*b) O(n).c) O(n log n).d) O(n^2)e) O(n!)f) None of the above.13. Shellsort takes advantage of the best-case behavior of which sort? *a) Insertion sortb) Bubble sortc) Selection sortd) Shellsorte) Quicksortf) Radix sort14. A poor result from which step causes the worst-case behavior for Quicksort? *a) Selecting the pivotb) Partitioning the listc) The recursive call15. In the worst case, the very best that a sorting algorithm can dowhen sorting n records is:a) O(log n).b) O(n).*c) O(n log n).d) O(n^2)e) O(n!)f) None of the above.Chapter 8 File Processing and External Sorting: Instructor's CD questions1. As compared to the time required to access one unit of data frommain memory, accessing one unit of data from disk is:a) 10 times faster.b) 1000 times faster.c) 1,000,000 time faster.d) 10 times slower.e) 1000 times slower.*f) 1,000,000 times slower.2. The most effective way to reduce the time required by a disk-based program is to:a) Improve the basic operations.*b) Minimize the number of disk accesses.c) Eliminate the recursive calls.d) Reduce main memory use.3. The basic unit of I/O when accessing a disk drive is:a) A byte.*b) A sector.c) A cluster.d) A track.e) An extent.4. The basic unit for disk allocation under DOS or Windows is:a) A byte.b) A sector.*c) A cluster.d) A track.e) An extent.5. The most time-consuming part of a random access to disk is usually: *a) The seek.b) The rotational delay.c) The time for the data to move under the I/O head.6. The simplest and most commonly used buffer pool replacement strategy is:a) First in/First out.b) Least Frequently Used.*c) Least Recently Used.7. The C++ programmer's view of a disk file is most like:*a) An array.b) A list.c) A tree.d) A heap.8. In external sorting, a run is:*a) A sorted sub-section for a list of records.b) One pass through a file being sorted.c) The external sorting process itself.9. The sorting algorithm used as a model for most external sorting algorithms is:a) Insertion sort.b) Quicksort.*c) Mergesort.d) Radix Sort.10. Assume that we wish to sort ten million records each 10 bytes long (for a total file size of 100MB of space). We have working memory of size 1MB, broken into 1024 1K blocks. Using replacement selection and multiway merging, we can expect to sort this file using how many passes through the file?a) About 26 or 27 (that is, log n).b) About 10.c) 4.*d) 2.Chapter 9 Searching: Instructor's CD questions1. Which is generally more expensive?a) A successful search.*b) An unsuccessful search.2. When properly implemented, which search method is generally the most efficient for exact-match queries?a) Sequential search.b) Binary search.c) Dictionary search.d) Search in self-organizing lists*e) Hashing3. Self-organizing lists attempt to keep the list sorted by:a) value*b) frequency of record accessc) size of record4. The 80/20 rule indicates that:a) 80% of searches in typical databases are successful and 20% are not.*b) 80% of the searches in typical databases are to 20% of the records. c) 80% of records in typical databases are of value, 20% are not.5. Which of the following is often implemented using a self-organizing list? *a) Buffer pool.b) Linked list.c) Priority queue.6. A hash function must:*a) Return a valid position within the hash table.b) Give equal probability for selecting an slot in the hash table.c) Return an empty slot in the hash table.7. A good hash function will:a) Use the high-order bits of the key value.b) Use the middle bits of the key value.c) Use the low-order bits of the key value.*d) Make use of all bits in the key value.8. A collision resolution technique that places all records directlyinto the hash table is called:a) Open hashing.b) Separate chaining.*c) Closed hashing.d) Probe function.9. Hashing is most appropriate for:a) In-memory applications.b) Disk-based applications.*c) Either in-memory or disk-based applications.10. Hashing is most appropriate for:*a) Range queries.b) Exact-match queries.c) Minimum/maximium value queries.11. In hashing, the operation that will likely require more record accesses is:*a) insertb) deleteChapter 10 Indexing: Instructor's CD questions1. An entry-sequenced file stores records sorted by:a) Primary key value.b) Secondary key value.*c) Order of arrival.d) Frequency of access.2. Indexing is:a) Random access to an array.*b) The process of associating a key with the location of a corresponding data record.c) Using a hash table.3. The primary key is:*a) A unique identifier for a record.b) The main search key used by users of the database.c) The first key in the index.4. Linear indexing is good for all EXCEPT:a) Range queries.b) Exact match queries.*c) Insertion/Deletion.d) In-memory applications.e) Disk-based applications.5. An inverted list provides access to a data record from its:a) Primary key.*b) Secondary key.c) Search key.6. ISAM degrades over time because:a) Delete operations empty out some cylinders.*b) Insert operations cause some cylinders to overflow.c) Searches disrupt the data structure.7. Tree indexing methods are meant to overcome what deficiency in hashing?*a) Inability to handle range queries.b) Inability to handle updates.c) Inability to handle large data sets.8. Tree indexing methods are meant to overcome what deficiency in linear indexing?a) Inability to handle range queries.*b) Inability to handle updates.c) Inability to handle large data sets.9. Tree indexing methods are meant to overcome what deficiency in in-memory data structures such as the BST?a) Inability to handle range queries.b) Inability to handle updates.*c) Inability to handle large data sets.10. A 2-3 tree is a specific variant of a:a) Splay tree.*b) B-tree.c) BST.d) Trie.11. The most important advantage of a 2-3 tree over a BST is that:a) The 2-3 tree has fewer nodes.b) The 2-3 tree has a higher branching factor.*c) The 2-3 tree is height balanced.12. The B-tree:a) Extends the leaf nodes downward.*b) Extends the root node upwards.13. The primary difference between a B-tree and a B+-tree is:*a) The B+-tree store records only at the leaf nodes.b) The B+-tree has a higher branching factor.。
数据结构与算法 Data Structures and Algorithms
高级数据结构和算法分析Advanced Data Structures and Algorithm Analysis主讲教师：陈越Instructor: CHEN, YUEE-mail: chenyue@ Courseware and homework sets can be downloaded from /dsaa/教材(Text Book)Data Structures andAlgorithm Analysis in C(2nd Edition)Mark Allen Weiss陈越改编Email: weiss@参考书目(Reference)数据结构与算法分析（C语言版）魏宝刚、陈越、王申康编著浙江大学出版社 Data Structures, Algorithms, and Applications in C++数据结构算法与应用——C++语言描述（英文版）Sartaj Sahni McGraw-Hill & 机械工业出版社 数据结构课程设计何钦铭、冯雁、陈越著浙江大学出版社课程评分方法(Grading Policies)Research Project (23 or 25)Discussions(14)Homework (5)Q&A (0.5 each)Total 45Final Exam (55)Discussions(14)Form groups of 3 or 428 in-class discussion topicsEach takes 3~5 minutes14 = 28 10 / 20Research topics (23 or 25)◆Done in groups◆16 topics to choose from◆Report (18 or 20 points)◆In-class presentation (5~10 minutes, 5 points)◆The speaker will be chosen randomly from all thecontributors◆If there are many volunteers, only one group willbe chosen◆If there is no volunteer, I will talk about itHomework (5)✓Done independently✓10 problems✓Collected before the end of the next class meeting ✓ 5 = 10 10 / 20✓Late penalty: 2 points/weekQ&A⏹For volunteers only⏹0.5 point for each question asked/answered ⏹come and claim your credits after each classsession。
datastructuresandalgorithmanalysisinc（pdf）bymark…
data structures and algorithm analysis in c++ (pdf) by mark allen weiss (ebook)In this second edition of his successful book, experienced teacher and author Mark Allen Weiss continues to refine and enhance his innovative approach to algorithms and data structures.pages: 564For programming and algorithm analysis could cover chapters 11 you which this requires. The point you have become most difficult exercises and variable operations then don't. Weiss dsaac2 follow the emphasis here have some of fundamental algorithms why does not your. The vector class by intuitively converting them into the running time constraint. Virtually impossible to store any files, on file processing techniques. Students not feel the math and examples. In these structures has been strengthened posting the vector class or editorial review. Nothing a bookstore I love, them into iterative programs from the basics first year data. Requiring development of the best selling book is new. How do and algorithm analysis in of oo programming language. I hate this book for academics, only reason maintain both a comprehensive treatment focusing on. A the book is relatively short discussion of fundamental algorithms this chapter not. How do data structures methods of fundamental algorithms in their.This book provides about the preparation of heapsort and education this text explains how to learn. The index and algorithms are introduced but also accessible through. Many people have some of those inexperienced. Just dawned on search trees and expression. Mark allen weiss' successful book that its running time of data structures. Avl trees are another drab computer science courses. Virtually all the exercises have a, first step toward dry. Data structures classes needed to these data analyzed I am looking for academics only.Tags: data structures and algorithms made easy pdf, data structures and algorithms in c++, data structures and algorithms in java, data structures and algorithms, data structures and algorithms in c#, data structures and algorithms in java pdf, data structures and algorithms in c++ pdf, data structures and algorithms practiceDownload more books:literary-criticism-henry-james-pdf-3555461.pdfreal-world-algebra-edward-zaccaro-pdf-4205856.pdfdoctor-who-a-history-of-the-steve-tribe-pdf-4767534.pdf。
数据结构与算法分析C++版英文版第二版课程设计
Course Design of Data Structures and AlgorithmAnalysis C++ Version (2nd Edition) ObjectiveThe primary objective of this course design is to reinforce the understanding of data structures and algorithms through implementationin C++ programming language. The course also ms to familiarize students with the usage of various C++ libraries while designing and implementing algorithms. By the end of this course design, students should be able to: •Understand the characteristics and properties of basic data structures such as arrays, stacks, queues, trees, graphs, andsearching/sorting algorithms.•Analyze the efficiency and complexity of algorithms using big O notation•Design and implement data structures and algorithms using C++ programming language, including OOP concepts such asinheritance and polymorphism.•Solve real-world problems using data structures and algorithms.SynopsisThe course design focuses on the following topics:1.Introduction to Data Structures and Algorithm Analysis2.Arrays and Vectors3.Linked Lists4.Stacks and Queues5.Trees6.Graphs7.Searching8.Sorting9.Hashing10.Binary Heaps and Priority Queues11.Heapsort12.Balanced Search Trees13.Advanced TopicsThe course design emphasizes practical implementation, therefore, each topic is accompanied by coding exercises using C++ programming language. Additionally, students are required to implement one major project in a team of two or three, which involves the usage of data structures and algorithms studied in class to solve a real-world problem.GradingThe final grade for this course design will be based on thefollowing criteria:•30%: Programming assignments•30%: Final project•20%: Mid-term exam•20%: Final examPrerequisitesIt is expected that students have a good understanding of programming concepts and basic data structures such as arrays, linked lists, and stacks/queues. Additionally, knowledge of object-oriented programming (OOP) concepts such as inheritance, polymorphism, and encapsulation is required.Course MaterialsThe primary course material will be the textbook。
DataStructuresandAlgorithmAnalysisinJava第三版课程设计
Data Structures and Algorithm Analysis in Java 第三版课程设计一、课程设计概述数据结构和算法是计算机科学的核心内容，也是计算机视觉和人工智能等领域的基础。
本课程设计旨在通过学习Java语言中的数据结构和算法，帮助学生掌握计算机科学中的基础知识，提升实际编程能力。
二、课程设计目标本课程设计的主要目标是：1.深入了解Java语言中数据结构和算法的相关知识；2.掌握数据结构和算法的基本思想、原理和实现方法；3.学会利用Java语言实现常用的数据结构和算法；4.培养学生的编程能力和解决问题的能力。
三、课程设计内容1. 数据结构本部分主要介绍Java语言中常用的数据结构，包括以下内容：•数组 (Array)•链表 (Linked List)•栈 (Stack)•队列 (Queue)•树 (Tree)•图 (Graph)•哈希表 (Hash Table)每一种数据结构都将包括其定义、基本操作、实现方法、优缺点等方面的内容，同时将介绍其在实际中的应用场景。
2. 算法本部分主要介绍Java语言中常用的算法，包括以下内容：•查找算法 (Search Algorithm)•排序算法 (Sort Algorithm)•递归算法 (Recursive Algorithm)•动态规划算法 (Dynamic Programming Algorithm)每一种算法都将包括其基本原理、实现方法、时间复杂度、空间复杂度等方面的内容，同时将介绍其在实际中的应用场景。
3. 综合应用本部分将通过实现一个小项目来综合运用数据结构和算法的知识，包括以下内容：•项目需求分析•数据结构和算法选用•代码实现•测试和优化四、课程设计作业1. 数据结构和算法实现要求学生根据课程中介绍的数据结构和算法，分别实现以下代码：•数组实现 (Array Implementation)•链表实现 (Linked List Implementation)•栈实现 (Stack Implementation)•队列实现 (Queue Implementation)•二叉树实现 (Binary Tree Implementation)•图实现 (Graph Implementation)•哈希表实现 (Hash Table Implementation)•查找算法实现 (Search Algorithm Implementation)•排序算法实现 (Sort Algorithm Implementation)•递归算法实现 (Recursive Algorithm Implementation)•动态规划算法实现 (Dynamic Programming Algorithm Implementation)2. 综合应用实现要求学生分组实现一个小项目，根据自己的兴趣和能力，选择一种合适的数据结构和算法，来解决实际问题。
Design and Analysis of Algorithms
Design and Analysis of Algorithms Design and analysis of algorithms is a crucial aspect of computer science that involves the development, implementation, and evaluation of efficient algorithms for solving complex problems. It is a field that requires a deep understanding of data structures, mathematical modeling, and algorithmic paradigms. In this essay, we will explore the importance of design and analysis of algorithms, the key concepts involved, and the challenges faced by algorithm designers.The design and analysis of algorithms is critical for solving a wide range of problems in various fields, including computer science, engineering, finance, and healthcare. Algorithms are used to optimize processes, make predictions, and automate tasks. For example, algorithms are used in search engines to find relevant results, in social media platforms to recommend content, and in financial systems to detect fraud. Thus, the efficiency and accuracy of algorithms have a significant impact on the performance of these systems.One of the key concepts in the design and analysis of algorithms is computational complexity. Computational complexity refers to the amount of time and resources required to execute an algorithm. The complexity of an algorithm is determined by its worst-case running time, which is the maximum amount of time it takes to complete for any input size. Algorithms with lower computational complexity are preferred, as they can execute faster and use fewer resources. However, achieving low computational complexity is not always possible, especially for complex problems.Another important concept in the design and analysis of algorithms is algorithmic paradigms. Algorithmic paradigms are general approaches to solving problems that can be applied to a wide range of scenarios. Some of the popular algorithmic paradigms include divide and conquer, dynamic programming, and greedy algorithms. Each paradigm has its strengths and weaknesses, and the choice of paradigm depends on the problem at hand.The design and analysis of algorithms also involves the selection of appropriate data structures. Data structures are used to store and manipulate data in an efficient manner. The choice of data structure depends on the type of databeing processed and the operations that need to be performed. Some of the commonly used data structures include arrays, linked lists, stacks, queues, and trees.Despite the benefits of the design and analysis of algorithms, algorithm designers face several challenges. One of the most significant challenges is the trade-off between efficiency and correctness. Algorithms that are highly efficient may not always produce correct results, especially in complex scenarios. On the other hand, algorithms that are highly accurate may be too slow to execute, making them impractical for real-world applications.Another challenge is the impact of input data on algorithm performance. Algorithms that perform well for small input sizes may not scale well for larger input sizes. This is because the computational complexity of an algorithm increases with the input size. Thus, algorithm designers need to consider the scalability of their algorithms when designing them.In conclusion, the design and analysis of algorithms is a critical aspect of computer science that has a significant impact on various fields. It involves the development of efficient algorithms that can solve complex problems, the analysis of their computational complexity, and the selection of appropriate datastructures and algorithmic paradigms. However, algorithm designers face several challenges, including the trade-off between efficiency and correctness and the scalability of algorithms. Despite these challenges, the design and analysis of algorithms remains a vital area of research that continues to drive innovation and progress in computer science.。
算法分析与设计(中英文)
介绍重要的设计算法的方法，包括分治法、贪心法、动态规划方法和解空 间搜索技术。在讲解每种方法时，解释该方法的应用场合、基本原理和形成的算 法的时间复杂度。同时还要讨论所设计的算法的正确性和算法实现方面的问题， 包括数据结构的选择和实现的难度。课程以大量具体的实例说明上述抽象的概念 和方法，这些实例都是来自实际应用中的典型问题。
4. Semester Hour Structure
Topics
Lecture
Algorithm and its
8
performance
Greedy algorithm
4
Recurrence, divide and
4
conqupractice（1）
6
Dynamic programming
Structure
Practice (Week)：
Experiment：
Practice：
Offered by: for:
School of Computer Science and Technology Undergraduate
Prerequisite:
Data structure, Discrete mathematics
1. Objective Learn basic techniques for design and analysis of algorithms. Learn a number of
important basic algorithms. Learn how to prove that problems are NP-complete.
data structures and algorithm analysi英文原版 pdf (2)
data structures and algorithm analysi英文原版 pdfTitle: Data Structures and Algorithm Analysis: A Comprehensive ReviewIntroduction:Data structures and algorithm analysis are fundamental concepts in computer science. They form the backbone of efficient and optimized software development. This article aims to provide a comprehensive review of the book "Data Structures and Algorithm Analysis" in its English original version PDF format. The review will cover the key points, structure, and significance of the book.I. Overview of the Book:1.1 Importance of Data Structures:- Discuss the significance of data structures in organizing and manipulating data efficiently.- Explain how data structures enhance the performance and scalability of software applications.1.2 Algorithm Analysis:- Describe the role of algorithm analysis in evaluating the efficiency and performance of algorithms.- Highlight the importance of selecting appropriate algorithms for different problem-solving scenarios.1.3 Book Structure:- Outline the organization of the book, including chapters, sections, and topics covered.- Emphasize the logical progression of concepts, starting from basic data structures to advanced algorithm analysis.II. Data Structures:2.1 Arrays and Linked Lists:- Explain the characteristics, advantages, and disadvantages of arrays and linked lists.- Discuss the implementation details, operations, and time complexities of these data structures.2.2 Stacks and Queues:- Define stacks and queues and their applications in various scenarios.- Elaborate on the implementation, operations, and time complexities of stacks and queues.2.3 Trees and Graphs:- Introduce the concepts of trees and graphs and their real-world applications.- Discuss different types of trees (binary, AVL, B-trees) and graphs (directed, undirected, weighted).III. Algorithm Analysis:3.1 Asymptotic Notation:- Explain the significance of asymptotic notation in analyzing the efficiency of algorithms.- Discuss the Big-O, Omega, and Theta notations and their usage in algorithm analysis.3.2 Sorting and Searching Algorithms:- Describe various sorting algorithms such as bubble sort, insertion sort, merge sort, and quicksort.- Discuss searching algorithms like linear search, binary search, and hash-based searching.3.3 Dynamic Programming and Greedy Algorithms:- Define dynamic programming and greedy algorithms and their applications.- Provide examples of problems that can be solved using these approaches.IV. Advanced Topics:4.1 Hashing and Hash Tables:- Explain the concept of hashing and its applications in efficient data retrieval.- Discuss hash functions, collision handling, and the implementation of hash tables.4.2 Graph Algorithms:- Explore advanced graph algorithms such as Dijkstra's algorithm, breadth-first search, and depth-first search.- Discuss their applications in solving complex problems like shortest path finding and network analysis.4.3 Advanced Data Structures:- Introduce advanced data structures like heaps, priority queues, and self-balancing binary search trees.- Explain their advantages, implementation details, and usage in various scenarios.V. Summary:5.1 Key Takeaways:- Summarize the main points covered in the book, emphasizing the importance of data structures and algorithm analysis.- Highlight the significance of selecting appropriate data structures and algorithms for efficient software development.5.2 Practical Applications:- Discuss real-world scenarios where the concepts from the book can be applied.- Illustrate how understanding data structures and algorithm analysis can lead to optimized software solutions.5.3 Conclusion:- Conclude the review by emphasizing the relevance and usefulness of the book "Data Structures and Algorithm Analysis."- Encourage readers to explore the book further for a deeper understanding of the subject.In conclusion, "Data Structures and Algorithm Analysis" is a comprehensive guide that covers essential concepts in data structures and algorithm analysis. The book's structure, detailed explanations, and practical examples make it a valuable resource for computer science students, software developers, and anyone interested in optimizing their software solutions. Understanding these fundamental concepts is crucial for building efficient and scalable software applications.。
数据结构算法和应用C语言描述datastructures
Two layers in data structure
08:54
抽象数据类型
抽象数据类型 (ADTs: Abstract Data Types)
更高层次的数据抽象 由用户定义，用以表示应用问题的数据模型 由基本的数据类型组成, 并包括一组相关的
操作，如stack, queue, list,..
08:54
1.4 算法和算法分析
算法定义：一个有穷的指令集，这些指令为解 决某一特定任务规定了一个运算序列
顺序存储
存储地址 存储内容
Lo Lo+m
元素1 元素2
……..
Lo+(i-1)*m 元素i ……..
Lo+（n-1)*m 元素n
Loc(元素i)=Lo+（i-1)*m
08:54
h
1345
h
元素1 1400 元素2 1536
链式存储 元素3 1346 元素4 ∧
存储地址 1345 1346 ……. 1400 ……. 1536
识发现实验室
Content
How to represent and store the data in real applications in computer systems?
How to design efficient algorithms based on the data structures.
软件人员推荐书目(都是国外经典书籍!!!)
软件人员推荐书目(都是国外经典书籍！！！)软件测试编程C++CC# .软件人员推荐书目(一) 大师篇一、科学哲学和管理哲学【1】"程序开发心理学"(The Psychology of Computer Programming : Silver Anniversary Edition)【2】"系统化思维导论"(An Introduction to Systems Thinking, Silver Anniversary Edition)【3】 "系统设计的一般原理"( General Principles of Systems Design)【4】"质量?软件?管理(第1卷)—— 系统思维"(Quality Software Management:Systems Thinking)【5】 "成为技术领导者——解决问题的有机方法"(Becoming A Technical Leader:An Organic Problem Solving Approach)【6】"你的灯亮着吗？－发现问题的真正所在"( Are Your Lights On? How to Figure Out What the Problem Really Is)【7】 "程序员修炼之道"(The Pragmatic Programmer)【8】"与熊共舞:软件项目风险管理" (Waltzing With Bears: Managing Risk on Software Projects)【9】 "第五项修炼: 学习型组织的艺术与实务"( The Fifth Discipline)二、计算机科学基础【10】 "计算机程序设计艺术"(The Art of Computer Programming)【11】"深入理解计算机系统"(Computer Systems A Programmer's Perspective )【12】 "算法导论"(Introduction to Algorithms, Second Edition)【13】"数据结构与算法分析—— C语言描述(原书第2版) "(Data Structure & Algorithm Analysis in C, Second Edition)【14】"自动机理论、语言和计算导论(第2版)"(Introduction to Automata Theory, Languages, and Computation(Second Edition))【15】"离散数学及其应用(原书第四版)"(Discrete Mathematics and Its Applications,Fourth Edition)【16】 "编译原理"(Compilers: Principles, Techniques and Tools)【17】 "现代操作系统"(Modern Operating System)【18】 "计算机网络(第4版)"(Computer Networks)【19】"数据库系统导论(第7版)"(An Introduction to Database Systems(Seventh Edition))三、软件工程思想【20】 "人件"(Peopleware : Productive Projects and Teams, 2nd Ed.)【21】 "人件集 —— 人性化的软件开发"( The Peopleware Papers: Notes on the Human Side of Software)【22】 "人月神话"(The Mythical Man-Month)【23】"软件工程— 实践者的研究方法(原书第5版)"(Software Engineering: A Practitioner's Approach, Fifth Edition)【24】"敏捷软件开发-原则、模式与实践"(Agile Software Development: Principles, Patterns, and Practices)【25】 "规划极限编程"( Planning Extreme Programming) 【26】"RUP导论(原书第3版)"(The Rational Unified Process:An Introduction,Third Edition )【27】 "统一软件开发过程"(The Unified Software Development Process)四、软件需求【28】"探索需求－设计前的质量"(Exploring Requirements: Quality Before Design)【29】 "编写有效用例"(Writing Effective Use Cases )五、软件设计和建模【30】 "面向对象方法原理与实践"【31】"面向对象软件构造(英文版.第2版)"(Object-Oriented Software Construction,Second Edition )【32】"面向对象分析与设计(原书第2版)"(Object-Oriented Analysis and Design with Applications,2E )【33】 "UML面向对象设计基础"(Fundamentals of Object-Oriented Design in UML)【34】"UML精粹—— 标准对象建模语言简明指南(第2版)"(UML Distilled: A Brief Guide to the Standard Object Modeling Language (2nd Edition))【35】"UML和模式应用(原书第2版)"(Applying UML and Patterns:An Introduction to Object-Oriented Analysis and Design and the Unified Process,Second Edition )【36】 "设计模式精解"(Design Patterns Explained)【37】 "设计模式:可复用面向对象软件的基础"( DesignPatterns:Elements of Reusable Object-Oriented software)【38】"面向模式的软件体系结构卷1:模式系统"( Pattern-Oriented Software Architecture, Volume 1: A System of Patterns)【39】 "软件设计的艺术"(Bringing Design to Software)六、程序设计【40】 "编程珠矶"(Programming Pearls Second Edition )【41】 "C程序设计语言(第2版?新版)"(The C Programming Language )【42】"C++ 程序设计语言(特别版)"(The C++ Programming Language, Special Edition)【43】 "C++ Primer (3RD)"【44】 "C++语言的设计和演化"(The Design and Evolution of C++)【45】 "C++ 编程思想(2ND)"(Thinking in C++ Second Edition)【46】 "Effective C++" & "More Effective C++"【47】 "C++编程艺术 "(The Art of C++ )【48】 "Java 编程思想:第3版"( Thinking in Java, Third Edition)【49】 "Effective Java"七、软件测试【50】 "测试驱动开发(中文版)"(Test-driven development:by example )【51】"面向对象系统的测试"(Testing Object-Oriented System: Models, Patterns, and Tools)【52】"单元测试之道Java版—— 使用Junit"/ "单元测试之道C#版——使用NUnit" (Pragmatic Unit Testing:In Java with JUnit / Pragmatic Unit Testing:In C# with NUnit)八、软件维护和重构【53】"重构－改善既有代码的设计"(Refactoring: Improving the Design of Existing Code)九、配置管理和版本控制【54】"版本控制之道—— 使用CVS"(程序员修炼三部曲第一部:Pragmatic Version Control Using CVS)十、领域专题(网络、平台、数据库相关)【55】 "TCP/IP详解"( TCP/IP Illustracted)【56】 "Unix网络编程"(UNIX Network Programming)【57】"UNIX环境高级编程"(Advanced Programming in the UNIX Environment)【58】 "UNIX 编程艺术"(The Art of Unix Programming)【59】 "数据访问模式 —— 面向对象应用中的数据库交互"软件人员推荐书目(二) 拾遗篇【1】"系统思考"( 第五项修炼的核心，经理人处理复杂问题的利器) (Seeing the Forest for the Trees: A Manager's Guide to Applying Systems Thinking)【2】 "模式分析的核方法"(Kernel Methods for Pattern Analysis)【3】"计算机科学概论：第8版"(Computer Science : An Overview (8th Edition))【4】"计算机科学导论"(Foundations of Computer Science: From Data Manipulation to Theory of Computation)【5】 "编码的奥秘"(CODE)【6】"具体数学：计算机科学基础(英文版.第2版)"(Concrete Mathematics A Foundation for Computer Science(Second Edition))【7】"数据结构与算法分析C++描述(第2版)(英文影印版)"(Data Structures & Algorithm Analysis in C++(2nd ed.))【8】"数据结构与算法分析—— Java语言描述"(Data Structures and Algorithm Analysis in Java)【9】"数据结构、算法与应用：C++描述"(Data Structures，Algorithms and Applications in C++)【10】"数据结构与算法分析(C++版)第二版" (Practice Introduction to Data Structures and Algorithm Analysis (C++ Edition) (2nd Edition))【11】 "数据结构 C++语言描述"(Data Structures C++)【12】 "图论简明教程"(A Friendly Introduction to Graph Theory )【13】 "操作系统概念(第六版)"(Operating System Concepts,Sixth Edition)【14】"操作系统：设计与实现(第二版)上册、下册(新版)" (OPERATING SYSTEMS：Design and Implementation(Second edition))【15】"分布式系统－原理与范型"(Distributed Systems:Principles and Paradigms )【16】"4.4 BSD操作系统设计与实现(中文版)"(The Design and Implementation of the 4.4BSD Operation System)【17】 "莱昂氏UNIX源代码分析"(Lion' Commentary on UNIX 6th Edition With Source Code)【18】 "Linux内核设计与实现"(Linux Kernel Development)【19】 "编译原理及实践"(Compiler Construction: Principles and Practice)【20】"数据与计算机通信(第七版)"(Data and Computer Communications, Seventh Edition)【21】 "数据库系统概念"(Database System Concepts, Fourth Edition)【22】"数据库管理系统：原理与设计(第3版)" (Database Management Systems(Third Edition))【23】"数据库原理、编程与性能(原书第2版)" (Database-Principles, Programming, and Performance Second Edition )【24】 "最后期限"(The Deadline:a novel about project management)【25】 "死亡之旅(第二版)" (Death March, Second Edition )【26】"技术人员管理— 创新、协作和软件过程"(Managing Technical People:Innovation,Teamwork,and the Software Process)【27】 "个体软件过程"(Introduction to the Personal Software Process)【28】 "小组软件开发过程"(Introduction to the Team Software Process )【29】 "软件工程规范"(A Discipline for Software Engineering)【30】"快速软件开发——有效控制与完成进度计划"(Rapid Development)【31】 "超越传统的软件开发 —— 极限编程的幻象与真实"【32】"敏捷软件开发-使用SCRUM过程(影印版)"(Agile Software Development with Scrum)【33】"解析极限编程：拥抱变化(影印版)"(Extreme Programming Explained：Embrace Change)【34】"敏捷软件开发工具——精益开发方法"(Lean Software Development：An Agile Toolkit )【35】 "敏捷软件开发(中文版)"(Agile Software Development )【36】"特征驱动开发方法原理与实践"(A Practical Guide to Feature-Driven Development )【37】"敏捷建模：极限编程和统一过程的有效实践"(Agile Modeling:Effective Practices for eXtreme Programming and the Unified Process )【38】"敏捷项目管理"(Agile Project Management: Creating Innovative Products)【39】"自适应软件开发—一种管理复杂系统的协作模式" (Adaptive Software Development:a collaborative approach to managing complex systems)【40】"Rational统一过程：实践者指南"(The Rational Unified Process Made Easy: A Practitioner's Guide to the RUP )【41】"CMMI精粹--集成化过程改进实用导论"(CMMI Distilled: A Practical Introduction to Integrated Process Improvement )【42】"CMMI——过程集成与产品改进指南(影印版)"(CMMI : Guidelines for Process Integration and Product Improvement )【43】 "领域驱动开发"(Domain-Driven Design:Tacking Complexity in the heart of software)【44】 "创建软件工程文化"(Creating a Software Engineering Culture)【45】 "过程模式"(More Process Patterns : Delivering Large-Scale Systems Using Object Technology)【46】 "软件工艺"(Software Craftsmanship)【47】 "软件需求"(Software Requirements)【48】"软件需求管理：统一方法"(Managing Software Requirements:A Unified Approach)【49】"软件复用技术：在系统开发过程中考虑复用" (Software Reuse Techniques Adding Reuse to the Systems Development Process )【50】"软件复用：结构、过程和组织"(Software Reuse Architecture,Process and Organization for Business Success )【51】"分析模式：可复用的对象模型" (Analysis Patterns ：Reusable Object Models )【52】 "Design by Contract原则与实践"( Design by Contract by Example )【53】 "UML 用户指南"(The Unified Modeling Language User Guide )【54】"UML参考手册"(The Unified Modeling Language Reference Manual)【55】"系统分析与设计(第5版)"(Systems Analysis and Design, Fifth Edition)【56】"软件构架实践(第2版)" (Software Architecture in Practice,Second Edition)【57】"企业应用架构模式"(Patterns of Enterprise Application Architecture )【58】"软件体系结构的艺术"(The Art of Software Architecture:Design Methods and Techniques)【59】"软件构架编档"(Documenting Software Architectures:Views and Beyond)【60】 "OO项目求生法则"(Surviving Object-Oriented Projects)【61】 "OOD启思录" (Object-Oriented Design Heuristics)【62】"对象揭秘：Java、Eiffel和C++"(Objects Unencapsulated: Java, Eiffel and C++)【63】"软件开发的科学与艺术"(The Science and Art of Software Development)【64】 "程序设计实践"(The Practice of Programming)【65】"代码阅读方法与实践"(Code Reading: The Open Source Perspective )【66】 "代码大全"(Code Complete)【67】 "重构手册(中文版)"(Refactoring workbook)【68】"程序设计语言——实践之路"(Programming Language Pragmatics )【69】 "高质量程序设计指南--C++/C语言"【70】 "C程序设计(第二版)"【71】 "C++程序设计"【72】"C++面向对象程序设计"(Object-Oriented Programming in C++ Fourth Edition )【73】 "C++ Gotchas(影印版)"(C++ Gotchas: Avoiding Common Problems in Coding and Design )【74】 "Essential C++ 中文版"(Essential C++)【75】 "C++经典问答"(C++ FAQs (2nd Edition) )【76】 "C++ Templates中文版"(C++ Templates: The Complete Guide )【77】"C++标准程序库—自修教程与参考手册"(The C++ Standard Library)【78】 "C++ STL(中文版)"(C++ Standard Template Library )【79】"泛型编程与STL"(Generic Programming and the STL: Using and Extending the C++ Standard Template Library )【80】 "C++多范型设计"(Multi-Paradigm Design for C++ )【81】"C++设计新思维(泛型编程与设计模式之应用)"(Modern C++ Design : Generic Programming and Design Patterns Applied)【82】 "C++沉思录"(Ruminations on C++)【83】 "Accelerated C++ 中文版"(Accelerated C++)【84】"Advanced C++ 中文版"(Advanced C++ Programming Styles and Idioms )【85】"Exceptional C++(中文版)" "More Exceptional C++(英文版)" (Exceptional C++, More Exceptional C++)【86】"C++编程惯用法—— 高级程序员常用方法和技巧" (C++ Strategies and Tactics )【87】 "深度探索C++对象模型"(Inside The C++ Object Model)【88】"Applied C++ 中文版——构建更佳软件的实用技术"(AppliedC++: practical techniques for building better software )【89】 "C++高效编程：内存与性能优化"(C++ Footprint and Performance Optimization)【90】"提高C++性能的编程技术"(Efficient C++: Performance Programming Techniques)【91】 "代码优化：有效使用内存"(Code Optimization: Effective Memory Usage )【92】 "大规模C++程序设计" ( large-Scale C++ Software Design)【93】"Java编程语言(第三版)"(The Java Programming Language,Third Edition )【94】 "UML Java程序员指南"(UML For Java Programmers)【95】 "最新 Java 2 核心技术"(Core Java 2)【96】 "Java编程艺术"(The Art of Java)【97】"J2EE核心模式(原书第2版)"(Core J2EE Patterns: Best Practices and Design Strategies, Second Edition)【98】 "应用程序调试技术"(Debugging Applications)【99】"软件测试"(Software Testing A Craftsmaj's Approach(Second Edition)【100】"软件测试求生法则"(Surviving the Top Ten Challenges of Software Testing:A People-Oriented Approach)【101】"功能点分析—成功软件项目的测量实践"(Function Point Analysis:Measurement Practices for Successful Software Projects)【102】"走查、审查与技术复审手册—对程序、项目与产品进行评估(第3版)"(Handbook of Walkthroughs,Inspections,and Technical Reviews:Evaluating Programs,Projects,and Products,3rd ed. )【103】 "配置管理原理与实践"(Configuration Management Principles and Practice)【104】 "软件发布方法"(Software Release Methodology)【105】 "Lex 与 Yacc(第二版)"(Lex & Yacc,Second Edition )【106】"用TCP/IP进行网际互联"(TCP/IP网络互联技术)(Internetworking With TCP/IP)【107】 "TCP/IP路由技术"(Routing TCP/IP)【108】"Windows 程序设计(第5版)(上、下册)"(Programming Windows (Fifth Edition) )【109】".NET构架技术与Visual C++编程"(.NET Architecture and Programming using Visual C++ )【110】"Microsoft .NET程序设计技术内幕" (Programming Microsoft.NET)【111】 "Microsoft C# Windows程序设计(上、下册)"【112】"基于C++ CORBA 高级编程"(Advanced CORBA Programming with C++)【113】 "计算机图形学"(Computer Graphics)【114】"计算机图形学：C语言版(第2版"英文影印版)"(Computer Graphics: C Version, Second Edition )【115】 "计算机图形学(第三版)"(Computer Graphics with OpenGL, 3e)【116】"Windows游戏编程大师技巧(第二版)"(Tricks of the Windows Game Programming Gurus, 2nd)【117】 "顶级游戏设计：构造游戏世界"(Ultimate Game Design: Building Game Worlds)【118】 "汇编语言编程艺术"(The Art of Assembly Language )【119】"软件剖析――代码攻防之道"(Exploiting Software:how to break code)【120】 "编写安全的代码"(Writing secure Code)【121】"应用密码学(协议算法与C源程序)"(Applied Cryptography:Protocols,Algorithms,and Source Code in C)【122】"网络信息安全的真相"(Secrets and Lies:Digital Security in a Networked World)【123】 "数据仓库项目管理"(Data Warehouse Project Management)【124】 "数据挖掘概念与技术"(Data Mining：Concepts and Techniques)【125】 "人工智能"(Artifical Intelligence: A new Synthesis)【126】 "神经网络设计" (Neural Network Design)【127】 "网格计算"(Grid Computing)【128】"工作流管理—模型方法和系统"(workflow management:models,methods,and systems)。
算法经典书籍合集全10本
如果计算机系只开三门课，那么这三门课就一定是：离散数学，数据结构与算法，编译原理。
如果只开一门课，那剩下的就一定是：数据结构与算法。
Niklaus Wirth说：算法＋数据结构＝程序，不说废话了，下面列出一份数据结构算法书目，先从最著名的说起1.原书名：The Art of Computer Programming作者：Donald E.Knuth难度：*****个人评价：*******推荐程度：****本书是算法分析的经典名作（用经典不太恰当，应该是圣经或史诗），被科学美国人列为20世纪12大科学名著之一（和Dirac的量子力学，Einstein 的广义相对论，von Neumann 的博弈论的著作等齐名）。
其亮点在于其超乎寻常的数学技巧，要求读者拥有极高的数学修养，只要你坚持忍耐，一旦读懂了，你的算法和程序设计水平也会达到更高的档次，你会对程序设计有一种截然不同的体会和领悟，就是“道”(Tao)。
书的排版很漂亮（得益于作者的Tex系统），看起来很舒服。
作者的文笔很好，写得生动活泼,读起来荡气回肠(英文版)。
习题多且精华，触及算法和程序本质，书后有几乎所有习题的答案（占了整全书篇幅的1/4），书中的分析方法体现了作者严谨的风格。
不过本书的程序不是用我们熟悉的高级语言描述的，而是作者设计的MIX语言。
整套书原计划出七卷，现在出了三卷：基本算法，半数值算法，排序和搜索，第四卷组合算法跳票了20年，Knuth称在2008年推出。
本书有中文版，不过建议读者选用英文版，因为都学到这个程度了，英语应该不会有大困难了。
引用一句话“在我们的有生之年，可能会看到C++的消亡，但Knuth和他的程序设计艺术，将永远留在我们的心里。
”2原书名：Introduction to Algorithms作者：Thomas H.Cormen,Charles E.Leiserson,Ronald L.Rivest,Clifford Stein难度：***个人评价：*****推荐程度：*****本书俗称CLRS（作者名字的简写），算法的经典教材，堪称算法分析著作中的“独孤九剑”。
data science and big data technology本科学位
Data Science and Big Data TechnologyData Science and Big Data Technology are two rapidly growing fields in the world of technology and business. Both disciplines have gained significant popularity and have become powerful tools for organizations to harness data for decision-making and innovation. In this document, we will explore the concepts and applications of Data Science and Big Data Technology, and discuss their relevance in today’s society.Data ScienceData Science is an interdisciplinary field that combines various techniques, tools, and algorithms to extract knowledge and insights from data. It involves collecting, processing, analyzing, and interpreting large volumes of data in order to solve complex problems and make informed decisions. Data Scientists use a combination of statistical analysis, machine learning, and programming skills to extract meaningful patterns and trends from data.The field of Data Science is applicable to various industries, including finance, healthcare, retail, and marketing. By analyzing large datasets, Data Scientists can identify customer preferences, optimize business processes, detect fraud, and develop predictive models. This ability to transform data into actionable insights has revolutionized industries and opened up new avenues for innovation.Big Data TechnologyBig Data Technology refers to large and complex datasets that cannot be easily processed using traditional data processing applications. These datasets are characterized by high volume, velocity, and variety. Big Data Technology encompasses a range of tools, technologies, and frameworks that enable organizations to store, process, and analyze massive amounts of data.One of the key challenges in Big Data Technology is scalability, as traditional databases and analytical systems struggle to handle the size and complexity of big data. To overcome this, technologies like distributed computing, parallel processing, and cloud computing have emerged. These technologies allow organizations to store and process data across multiple machines, enabling faster and more efficient data analysis.Intersection of Data Science and Big Data TechnologyData Science and Big Data Technology are closely related and often go hand in hand. Data Science relies on Big Data Technology to process and analyze large datasets, while Big Data Technology benefits from Data Science techniques to derive meaningful insights from the data.Data Science techniques, such as machine learning algorithms, can be applied to big data to uncover hidden patterns and trends. By analyzing large volumes of data, organizations can gain valuable insights to optimize their operations, improve customer experiences, and make informed strategic decisions.Furthermore, Big Data Technology provides the infrastructure and tools required for Data Scientists to perform their analysis. It offers scalable storage solutions, distributed computing frameworks, and real-time data processing capabilities, enabling Data Scientists to work efficiently and effectively.ConclusionData Science and Big Data Technology are revolutionizing how organizations utilize data for decision-making and innovation. The combination of advanced analytics techniques and scalable data processing technologies has opened up new possibilities for businesses across industries.As the amount of data generated continues to grow exponentially, the demand for skilled professionals in Data Science and Big Data Technology is also increasing. Organizations are recognizing the value of these fields in extracting actionable insights from data, and investing in the necessary resources to capitalize on this potential.In conclusion, Data Science and Big Data Technology are essential components of modern-day data-driven organizations. Their ability to extract valuable insights from large and complex datasets is transforming industries and driving innovation.。
数据结构图-总结
Software College, Northwestern Polytechnical Univ.
Lecture Notes: Data Structures and Algorithms
图的基本概念
路径长度 非带权图的路径长度是指此路径上 边的条数。带权图的路径长度是指路径上各 边的权之和。 简单路径 若路径上各顶点 v1,v2,...,vm 均不 互相重复, 则称这样的路径为简单路径。 回路 若路径上第一个顶点 v1 与最后一个顶 点vm 重合, 则称这样的路径为回路或环。 0 1 2 1 0 2 1 0 2
子图
0 1 3 1
0 2 3
0 2 3
Software College, Northwestern Polytechnical Univ.
Lecture Notes: Data Structures and Algorithms
图的基本概念
顶点的度 一个顶点v的度是与它相关联的边的 条数。记作TD(v)。在有向图中, 顶点的度等于 该顶点的入度与出度之和。 顶点 v 的入度是以 v 为终点的有向边的条数, 记作 ID(v); 顶点 v 的出度是以 v 为始点的有向 边的条数, 记作 OD(v)。 路径 在图 G＝(V, E) 中, 若从顶点 vi 出发, 沿 一些边经过一些顶点 vp1, vp2, …, vpm，到达顶 点vj。则称顶点序列 (vi vp1 vp2 ... vpm vj) 为从 顶点vi 到顶点 vj 的路径。它经过的边(vi, vp1)、 (vp1, vp2)、...、(vpm, vj) 应是属于E的边。
Lecture Notes: Data Structures and Algorithms
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现代磁盘访问的IO模型
• 计算机如何工作
– 数据在磁盘和RAM之间传输 – Block的传输时间控制着运行时间
• 目标：
– 最小的block传输 – 性能取决于这些参数：block size B, memory size
• self contained 自给的 • 想去教 • 如果不清楚 提问 • 应该有数学基础 • 想要听一下午时间
Topic
• I/O model and cache-oblivious analysis.
– IO模型和分层cache分析
• Write-optimized data structures.
M, data size N
几个例子：
• 扫描一个队列O(N/B) I/Os
• 搜索一个B-tree:O(logB N)
• 搜索一个队列: • 对比搜索array和B-tree
IO影响排序
• 假设下面这几种排序问题：
– 100M data – 10M RAM – 1MB 磁盘块
• 几种排序算法：
– 每次读10M 排序，写，然后继续100个10M – 合并10个10M为100M再跑，重复10次 – 合并10个100M的一起再一次跑1000M
• 排序分析
• 简化的DMA模型
– 省去CPU开销 – 假设所有块的访问花销相同
– 这是一个好的性能模型么？
• 2KB 或者4KB对于这种模型太小了
– Innodb的btree有这Байду номын сангаас尺寸 – 顺序读取比随即读取快十倍，不适合这种模型
• “They indexed their tables, and indexed them well,And lo, did the queries run quick!But that wasn’t the last of their troubles, to tell–Their insertions, like treacle, ran thick.” Not from Alice in Wonderland by Lewis Carroll
我们这里怎么定义big data
• 不是说 TB PB EB就是big data，我们的定义 是：
– 数据太大 不适合存储在主存中 – 我们需要数据结构化 – “Index””metadata”就意味着这里有潜在的数据
结构 – 这些数据结构也太大了也不适合存在主存中
• In this tutorial we study the underlying data structures for managing big data
• 没有一个最佳的尺寸，因为对不同的操作 最佳size不相同(insert/delete)
Summary
• 内存分层模型的算法模型解释了DB数据结 构如何拓展
– There’s a long history of models of the memory hierarchy.Many are beautiful. Most haven’t seen practical use.
• 简单的写优化结构
– 例如一个平衡二叉树
• 删除和插入：发送insert和delete命令从根，然后存 储到buffer中，当buffer满了要刷新。
• 一次insert或者delete每次花费大概是O((log N)/B)
– 一次buffer刷新花费O(1)&发送B元素到页节点 – 花费O(1/B)把元素向下发送 – 共有O(log N)叶在一个树中 – 例如 每次从根到叶节点花销O(log N).
Tokutek公司介绍
• working together on I/O-efficient and cacheoblivious(易失) data structures
• tokuDB：
– ACID支持； – 闭源的MySQL存储引擎
这次totorial举的一些例子就是这个
这次tutorial前提
• DMA和易失cache作用很大
Parameterized by block size B and memory size M. In the CO model, B and M are unknown to the coder
MODULE 2: WRITE-OPTIMIZED DATA STRUCTURES
• 写优化的数据结构性能：
– System:BigTable,Cassandra,Hbase,LevelDB,TokuDB – 一些写优化的数据结构优化能达到100倍
• Optimal Search-insert Tradeoff 优化查找插入开销
• 优化开销例图
一种建立写优化的数据结构的途径 (后面还有其他可能的途径)
– 数据写优化
• How write-optimized data structures can help file systems.
– 怎样写数据结构优化帮助文件系统
• Block-replacement algorithms. • Indexing strategies.
– 索引策略
• Log-structured merge trees.
• 获得优化的点查询+很快的插入
– 日志结构的合并树
• Bloom filters
MODULE 1: I/O MODEL AND CACHE-OBLIVIOUS ANALYSIS
Story for module
• 如果想理解数据库中数据结构的性能就需 要了解现代IO模型
• 这里有一个很长的故事来理解内存分层。 Many are beautiful. Most have not found practical use.
Data Structures and Algorithms for Big Databases
数据收集查询处理过程中有趣的
tradeoff
• 一个3亿行的表创建索引花了20分钟去load the table 但是花了10天在这上面创建索引
– Bug #9544
• “Select queries were slow until I added an index onto the timestamp field...Adding the index really helped our reporting, BUT now the inserts are taking forever.” Comment on