Algorithm
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Getting Started with AlgorithmWhat is an Algorithm?
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Characteristics of Algorithm1 Topic
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Analysis Framework
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Performance Analysis3 Topics
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Mathematical Analysis2 Topics
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Sorting AlgorithmSorting Algorithm10 Topics
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Searching Algorithm6 Topics
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Fundamental of Data StructuresStacks
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Queues
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Graphs
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Trees
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Sets
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Dictionaries
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Divide and ConquerGeneral Method
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Binary Search
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Recurrence Equation for Divide and Conquer
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Finding the Maximum and Minimum
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Merge Sort
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Quick Sort
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Stassen’s Matrix Multiplication
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Advantages and Disadvantages of Divide and Conquer
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Decrease and ConquerInsertion Sort
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Topological Sort
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Greedy MethodGeneral Method
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Coin Change Problem
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Knapsack Problem
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Job Sequencing with Deadlines
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Minimum Cost Spanning Trees2 Topics
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Single Source Shortest Paths1 Topic
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Optimal Tree Problem1 Topic
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Transform and Conquer Approach1 Topic
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Dynamic ProgrammingGeneral Method with Examples
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Multistage Graphs
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Transitive Closure1 Topic
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All Pairs Shortest Paths6 Topics
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BacktrackingGeneral Method
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N-Queens Problem
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Sum of Subsets problem
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Graph Coloring
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Hamiltonian Cycles
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Branch and Bound2 Topics
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0/1 Knapsack problem2 Topics
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NP-Complete and NP-Hard Problems1 Topic
Participants2253
Space Complexity
The space complexity of an algorithm is the amount of memory it needs to run to completion.

The space needed by each of these algorithms is seen to be the sum of the following components:


1.A fixed part that is independent of the characteristics(e.g.,number, size)of the inputs and outputs. This part typically includes the instruction space(i.e., space for the code), space for simple variables and fixed-size component variables(also called aggregate), space for constants,and soon.
2.A variable part that consists of the space needed by component variables whose size is dependent on the particular problem instance being solved, the space needed by referenced variables(to the extent that this depends on instance characteristics), and the recursion stack space (in-so far as this space depends on the instance characteristics).
The space requirement S(P) of any algorithm P may therefore be written as S(P)= c+Sp(instance characteristics), where c is a constant.