This free App on Data Structure covers most important topics with full Description using Easy example and Diagrams
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 w
ith 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 Algorithms2. Efficiency of algorithm3. Analysis of insertion sort4. Insertion sort5. The divide-and-conquer approach6. Analyzing divide-and-conquer algorithms7. Asymptotic notation8. Asymptotic notation in equations and inequalities9. Standard notations and common functions10. The hiring problem11. Indicator random variables12. Balls and bins13. Probabilistic analysis and further uses of indicator random variables14. Streaks15. The on-line hiring problem16. Overview of Recurrences17. The substitution method for recurrences18. The recursion-tree method19. The master method20. Proof of the master theorem21. The proof for exact powers22. Floors and ceilings23. Randomized algorithms24. Heaps25. Maintaining the heap property26. Building a heap27. The heapsort algorithm28. Priority queues29. Description of quicksort30. Performance of quicksort31. A randomized version of quicksort32. Analysis of quicksort33. Lower bounds for sorting34. Counting sort35. Radix sort36. Minimum and maximum37. Selection in expected linear time38. Bucket sort39. Selection in worst-case linear time40. Stacks and queues41. Linked lists42. Implementing pointers and objects43. Representing rooted trees44. Direct-address tables45. Hash tables46. Hash functions47. Open addressing48. Perfect hashing49. introduction to binary search tree50. Querying a binary search tree51. Insertion and deletion52. Randomly built binary search trees53. Red-Black Trees54. Rotations of red black tree55. Insertion in red black tree56. Deletion in red black tree57. Dynamic order statistics58. Augmenting a Data Structure59. Interval Trees60. Overview of Dynamic Programming61. Assembly-line scheduling62. Matrix-chain multiplication63. Elements of dynamic programming64. Longest common subsequence65. Optimal binary search trees66. Greedy Algorithms67. Elements of the greedy strategy68. Huffman codes69. Theoretical foundations for greedy methods70. A task-scheduling problem71. Aggregate analysis72. The accounting method73. The potential method74. Dynamic tables75. B-Trees76. Definition of B-trees77. Basic operations on B-trees78. Deleting a key from a B-tree79. Binomial Heaps80. Operations on binomial heaps81. Fibonacci Heaps82. Mergeable-heap operations83. Decreasing a key and deleting a node84. Bounding the maximum degree85. Data Structures for Disjoint Sets86. Linked-list representation of disjoint sets87. Disjoint-set forests88. Analysis of union by rank with path compression89. Representations of graphs90. Breadth-first search91. Depth-first search92. Topological sort93. Strongly connected components94. Minimum Spanning Trees95. Growing a minimum spanning tree96. The algorithms of Kruskal and Prim97. Single-Source Shortest Paths98. The Bellman-Ford algorithm99. Single-source shortest paths in directed acyclic graphs100. Dijkstra's algorithm101. Difference constraints and shortest paths102. Shortest paths and matrix multiplication103. The Floyd-Warshall algorithmAlgorithms is part of computer science & software engineering education courses and information technology degree programs of various universities.
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