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Searching, Sorting, Hashing, Asymptotic worst case time and Space complexity, Algorithm design techniques: Greedy, Dynamic programming, and Divide‐and‐conquer, Graph search, Minimum spanning trees, Shortest paths.

$$\scriptsize{\overset{{\large{\textbf{Mark Distribution in Previous GATE}}}}{\begin{array}{|c|c|c|c|c|c|c|c|}\hline
\textbf{Year}&\textbf{2024-1} & \textbf{2024-2} & \textbf{2023} & \textbf{2022} & \textbf{2021-1}&\textbf{2021-2}&\textbf{Minimum}&\textbf{Average}&\textbf{Maximum}
\\\hline\textbf{1 Mark Count} & 1&2&2& 2 &3&2&1&2&3
\\\hline\textbf{2 Marks Count} &4&2&2& 2 &3&4&2&2.83&4
\\\hline\textbf{Total Marks} &9&6&6& 6 &9&10&\bf{6} & \bf{7.67}&\bf{10}\\\hline
\end{array}}}$$

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Hot questions in Algorithms

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3641
questions
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3642
Made Easy
what will be the change in time when quick sort is used over the heap sort to sort the edges in order to find the MST using kruskal algorithm...no of edges = 16
what will be the change in time when quick sort is used over the heap sort to sort the edges in order to find the MST using kruskal algorithm...no of edges = 16
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1 votes
1 answer
3643
Algorithm Doubt
Assume we are given that f(n) = Οg(n), then which of the following can be stated true 2f(n) = Ο(2g(n)) log f(n) = Ο(log (g(n)) g(n) ≠ Ω f(n) None of these
Assume we are given that f(n) = Οg(n), then which of the following can be stated true2f(n) = Ο(2g(n)) log f(n) = Ο(log (g(n))g(n) ≠ Ω f(n)None of these
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3644
self doubta
please explain these few point: how is longest path between any pair of vertices different from diameter of a agraph.? in dijkstra algorithm,each edge is relaxed eaxtly one time..is it true or false?
please explain these few point:how is longest path between any pair of vertices different from diameter of a agraph.?in dijkstra algorithm,each edge is relaxed eaxtly one...
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2 answers
3645
ADA Testbook
What is the time complexity to count the number of leaf nodes in a tree? I am getting O(nlogn) but answer is O(n) please anybody explain in detail
What is the time complexity to count the number of leaf nodes in a tree? I am getting O(nlogn) but answer is O(n) please anybody explain in detail
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1 votes
2 answers
3646
worst case lower bound
What is the meaning of upper bound and worst case lower bound here?
What is the meaning of upper bound and worst case lower bound here?
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1 answer
3647
Time complexity
Let A =[a1, a2, …, an] be a one-dimensional array of integers define a MEGA-PEAK in A to be an element ai belongs A such that ai >= aj for all aj with | j – i | <= 2. What is the time complexity to find MEGA-PEAK?
Let A =[a1, a2, …, an] be a one-dimensional array of integers define a MEGA-PEAK in A to be an element ai belongs A such that ai >= aj for all aj with | j – i | <= 2....
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4 votes
1 answer
3650
GATE Overflow | Algorithms | Test 1 | Question: 13
You are given a 1 billion numbers. The time require in seconds to sort them provided sorting thousand numbers takes 100 microseconds will be _______ 10,000 512 300 65536
You are given a 1 billion numbers. The time require in seconds to sort them provided sorting thousand numbers takes 100 microseconds will be _______10,00051230065536
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2 votes
1 answer
3654
quick sort
Is quick sort in-place algorithm?
Is quick sort in-place algorithm?
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2 votes
1 answer
3657
Which of the following sorting methods will be the best if number of swapping
Which of the following sorting methods will be the best if number of swapping done is the only measure of efficiency I am getting Bubble sort , is it right ?
Which of the following sorting methods will be the best if number of swapping done is the only measure of efficiencyI am getting Bubble sort , is it right ?
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3658
Algo rec
What is the tightest upper bound to $T(n) = T(n-1) + 2^n$? $O(n2^n)$ $O(2^n)$ $O(2^{2n})$ None
What is the tightest upper bound to $T(n) = T(n-1) + 2^n$?$O(n2^n)$$O(2^n)$$O(2^{2n})$None
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3659
How many levels are present for this algorithm assuming merge can be accomplished in O(n log(k)) time.
in an effort to make MERGE-SORT faster, you decide to divide the array into k equal sized, disjoint subarrays, where k 2. This means that you have to merge k lists. How ...
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