Data Structure and Algorithm

This free App on Data Structure covers most important topics with full Description using Easy example and Diagrams. this Subject is very Helpful in Exam, Viva, Gate. All Chapter are Related to each other so after keeping it in mind all Content are Arranged with Step by Step.

The best app for Exam, college and in programs. If you are a student It will help to learn a lot.

This useful App lists 130 topics in 5 chapters, totally based on practical as well as a strong base of theoretical knowledge with notes written in very simple and understandable English.

Consider this App as a quick note guide which professors use in a classroom. The App will help in faster learning and quick revisions of all the topics.

Some of the topics Covered in the app are:

1. Introduction to Algorithms

2. Efficiency of algorithm

3. Analysis of insertion sort

4. Insertion sort

5. The divide-and-conquer approach

6. Analyzing divide-and-conquer algorithms

7. Asymptotic notation

8. Asymptotic notation in equations and inequalities

9. Standard notations and common functions

10. The hiring problem

11. Indicator random variables

12. Balls and bins

13. Probabilistic analysis and further uses of indicator random variables

14. Streaks

15. The on-line hiring problem

16. Overview of Recurrences

17. The substitution method for recurrences

18. The recursion-tree method

19. The master method

20. Proof of the master theorem

21. The proof for exact powers

22. Floors and ceilings

23. Randomized algorithms

24. Heaps

25. Maintaining the heap property

26. Building a heap

27. The heapsort algorithm

28. Priority queues

29. Description of quicksort

30. Performance of quicksort

31. A randomized version of quicksort

32. Analysis of quicksort

33. Lower bounds for sorting

34. Counting sort

35. Radix sort

36. Minimum and maximum

37. Selection in expected linear time

38. Bucket sort

39. Selection in worst-case linear time

40. Stacks and queues

41. Linked lists

42. Implementing pointers and objects

43. Representing rooted trees

44. Direct-address tables

45. Hash tables

46. Hash functions

47. Open addressing

48. Perfect hashing

49. introduction to binary search tree

50. Querying a binary search tree

51. Insertion and deletion

52. Randomly built binary search trees

53. Red-Black Trees

54. Rotations of red black tree

55. Insertion in red black tree

56. Deletion in red black tree

57. Dynamic order statistics

58. Augmenting a Data Structure

59. Interval Trees

60. Overview of Dynamic Programming

61. Assembly-line scheduling

62. Matrix-chain multiplication

63. Elements of dynamic programming

64. Longest common subsequence

65. Optimal binary search trees

66. Greedy Algorithms

67. Elements of the greedy strategy

68. Huffman codes

69. Theoretical foundations for greedy methods

70. A task-scheduling problem

71. Aggregate analysis

72. The accounting method

73. The potential method

74. Dynamic tables

75. B-Trees

76. Definition of B-trees

77. Basic operations on B-trees

78. Deleting a key from a B-tree

79. Binomial Heaps

80. Operations on binomial heaps

81. Fibonacci Heaps

82. Mergeable-heap operations

83. Decreasing a key and deleting a node

84. Bounding the maximum degree

85. Data Structures for Disjoint Sets

86. Linked-list representation of disjoint sets

87. Disjoint-set forests

88. Analysis of union by rank with path compression

89. Representations of graphs

90. Breadth-first search

91. Depth-first search

92. Topological sort

93. Strongly connected components

94. Minimum Spanning Trees

95. Growing a minimum spanning tree

96. The algorithms of Kruskal and Prim

97. Single-Source Shortest Paths

98. The Bellman-Ford algorithm

99. Single-source shortest paths in directed acyclic graphs

100. Dijkstra's algorithm

101. Difference constraints and shortest paths

102. Shortest paths and matrix multiplication

103. The Floyd-Warshall algorithm

Algorithms is part of computer science & software engineering education courses and information technology degree programs of various universities.

这个免费的应用程序对数据结构包括使用简单的例子，并用图表充分说明最重要的主题。该主题在考试非常有帮助，万岁，门。所有章节都与彼此保持它考虑到了所有的内容后，与分步安排。

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这个有用的应用程序列出了5章130个主题，完全根据实际和理论知识与写的非常简单易懂的英语笔记强碱。

考虑这个应用程序作为教授在课堂上使用的快速音符引导。该应用程序将帮助更快的学习和所有题目快速修订。

一些在应用程序讨论的主题有：

1.算法导论

2.算法的效率

3.插入排序分析

4.插入排序

5.分而治之的方法

6.分析分而治之算法

7.渐近记法

8.在等式和不等式渐近符号

9.标准符号和常用功能

10.聘用问题

11.指示器随机变量

12.球和箱

指示器随机变量的概率13.分析和进一步使用

14.条纹

15.上线雇用问题

16.概述的复发

17.一种用于复发的替代方法

18.递归树方法

19.主方法

20.证明主定理的

21.确切权力的证明

22.地板和天花板

23.随机算法

24.堆

25.维护堆属性

26.建立一个堆

27.堆排序算法

28.优先级队列

29.快速排序的说明

30.业绩的快速排序

31.快速排序的随机版

快速排序32.分析

33.一种用于分选下界

34.计数排序

35.基数排序

36.最小和最大

37.选择在预期的线性时间

38.桶排序

39.选择在最坏情况下的线性时间

40.栈和队列

41.链表

42.实施指针和对象

43.代表根的树

44.直接地址表

45.哈希表

46.哈希函数

47.打开解决

48.完美的混编

49.介绍二叉搜索树

50.查询二叉搜索树

51.插入和删除

52.随机内置二叉搜索树

53.红黑树

红黑树的54轮作

55.插入在红黑树

56.删除在红黑树

57.动态顺序统计

58.增广的数据结构

59.间隔树

60.概述动态规划

61.装配线调度

62.矩阵链乘法

动态规划的63要素

64.最长公共子

65.最佳二叉搜索树

66.贪婪算法

贪婪战略的67要素

68.霍夫曼码

69.一种用于贪婪方法理论基础

70.任务调度问题

71.综合分析

72.会计方法

73.潜在的方法

74.动态表

75. B-树

B树76定义

77. B树基本操作

78.删除从B树的关键

79.二项堆

80.操作上的二项堆

81.斐波那契堆

82.可合并堆操作

83.降低一个键和删除节点

84.边界范围，最大程度

85.不相交集合数据结构

不相交的集合86.链接的列表表示

87.不相交集森林

通过与路径压缩排名88.分析联盟

图89.交涉

90.广度优先搜索

91.深度优先搜索

92.拓扑排序

93.强连通分量

94.最小生成树

95.成长的最小生成树

96.秩和的Prim的算法

97.单源最短路径

98. Bellman-Ford算法

99.在向无环图的单源最短路径

100. Dijkstra算法

101.差异约束和最短路径

102.最短路径和矩阵乘法

103. Floyd-Warshall算法

算法是计算机科学和软件工程教育课程和各大学的信息技术学位课程的一部分。