Design And Analysis Of Algorithms 
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0/1 Knapsack problem adjacency list adjacency matrix answer node array articulation point asymptotic notation backtracking basic operation biconnected components big oh notation binary search tree Boolean branch and bound Breadth First Search cA(x clrscr complexity compute Consider denotes depth first search divide and conquer dynamic programming Enode efficiency Enter the element equation example getch graph G Greedy method Hamiltonian cycle Hence Initially input Kruskal's algorithm left child left sublist live nodes log2n loop merge sort minimum cost minimum spanning tree Minimum value multistage graph NP complete obtain optimal binary search optimal solution order of growth Output polynomial Prim's algorithm printf("\n Enter Problem Description Q Q Q queen recurrence relation recursive algorithms right child right sublist select next minimum sequence space tree Step shortest path subproblems sum of subset temp total number Total weight tuple size formulation vertex visited worst