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Data Structure and Algorithm Pro - APK Download

Data Structure and Algorithm Pro

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Run this app named Data Structure and Algorithm Pro or download it using ApkOnline. You can do it using our Android online emulator.

This 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.\tIntroduction to Algorithms
2.\tEfficiency of algorithm
3.\tAnalysis of insertion sort
4.\tInsertion sort
5.\tThe divide-and-conquer approach
6.\tAnalyzing divide-and-conquer algorithms
7.\tAsymptotic notation
8.\tAsymptotic notation in equations and inequalities
9.\tStandard notations and common functions
10.\tThe hiring problem
11.\tIndicator random variables
12.\tBalls and bins
13.\tProbabilistic analysis and further uses of indicator random variables
14.\tStreaks
15.\tThe on-line hiring problem
16.\tOverview of Recurrences
17.\tThe substitution method for recurrences
18.\tThe recursion-tree method
19.\tThe master method
20.\tProof of the master theorem
21.\tThe proof for exact powers
22.\tFloors and ceilings
23.\tRandomized algorithms
24.\tHeaps
25.\tMaintaining the heap property
26.\tBuilding a heap
27.\tThe heapsort algorithm
28.\tPriority queues
29.\tDescription of quicksort
30.\tPerformance of quicksort
31.\tA randomized version of quicksort
32.\tAnalysis of quicksort
33.\tLower bounds for sorting
34.\tCounting sort
35.\tRadix sort
36.\tMinimum and maximum
37.\tSelection in expected linear time
38.\tBucket sort
39.\tSelection in worst-case linear time
40.\tStacks and queues
41.\tLinked lists
42.\tImplementing pointers and objects
43.\tRepresenting rooted trees
44.\tDirect-address tables
45.\tHash tables
46.\tHash functions
47.\tOpen addressing
48.\tPerfect hashing
49.\tintroduction to binary search tree
50.\tQuerying a binary search tree
51.\tInsertion and deletion
52.\tRandomly built binary search trees
53.\tRed-Black Trees
54.\tRotations of red black tree
55.\tInsertion in red black tree
56.\tDeletion in red black tree
57.\tDynamic order statistics
58.\tAugmenting a Data Structure
59.\tInterval Trees
60.\tOverview of Dynamic Programming
61.\tAssembly-line scheduling
62.\tMatrix-chain multiplication
63.\tElements of dynamic programming
64.\tLongest common subsequence
65.\tOptimal binary search trees
66.\tGreedy Algorithms
67.\tElements of the greedy strategy
68.\tHuffman codes
69.\tTheoretical foundations for greedy methods
70.\tA task-scheduling problem
71.\tAggregate analysis
72.\tThe accounting method
73.\tThe potential method
74.\tDynamic tables
75.\tB-Trees
76.\tDefinition of B-trees
77.\tBasic operations on B-trees
78.\tDeleting a key from a B-tree
79.\tBinomial Heaps
80.\tOperations on binomial heaps
81.\tFibonacci Heaps
82.\tMergeable-heap operations
83.\tDecreasing a key and deleting a node
84.\tBounding the maximum degree
85.\tData Structures for Disjoint Sets
86.\tLinked-list representation of disjoint sets
87.\tDisjoint-set forests
88.\tAnalysis of union by rank with path compression
89.\tRepresentations of graphs
90.\tBreadth-first search
91.\tDepth-first search
92.\tTopological sort
93.\tStrongly connected components
94.\tMinimum Spanning Trees
95.\tGrowing a minimum spanning tree
96.\tThe algorithms of Kruskal and Prim
97.\tSingle-Source Shortest Paths
98.\tThe Bellman-Ford algorithm
99.\tSingle-source shortest paths in directed acyclic graphs
100.\tDijkstra's algorithm
101.\tDifference constraints and shortest paths
102.\tShortest paths and matrix multiplication
103.\tThe Floyd-Warshall algorithm

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



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