Data Structure and Algorithm

The App Data Structure and Algorithm is designed for quick learning, revisions, references at the time of exams and interviews. This App has 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. This app cover most of related topics and Detailed explanation with all the basics 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 This app will useful for quick reference. The revision of all concepts can be finished within Several hour using this app. Algorithms is part of computer science & software engineering education courses and information technology degree programs of various universities. Instead of giving us a lower rating, please mail us your queries, issues and give us valuable Rating And Suggestion So we can consider it for Future Updates. We will be happy to solve them for you.