CS502-Midterm
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In Quick Sort Constants hidden in T(n log n) are
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Efficient algorithm requires less computational…….
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In which order we can sort?
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Analysis of Selection algorithm ends up with,
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One example of in place but not stable algorithm is
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What is the solution to the recurrence T(n) = T(n/2)+n .
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The number of nodes in a complete binary tree of height h is
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Upper bound requires that there exist positive constants c2 and n0 such that f(n) ____ c2n for all n <= n0(ye question ghalat lag raha hai mujhae
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Which may be a stable sort?
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Sorting is one of the few problems where provable ________ bonds exits on how fast we can sort,
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The array to be sorted is not passed as argument to the merge sort algorithm.
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Divide-and-conquer as breaking the problem into a small number of
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_______________ is a graphical representation of an algorithm
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Consider the following code:
For(j=1; j
For(k=1; k<15;k++)
For(l=5; l
{
Do_something_constant();
}
What is the order of execution for this code.
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In analysis, the Upper Bound means the function grows asymptotically no faster than its largest term.
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Asymptotic growth rate of the function is taken over_________ case running time.
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Counting sort has time complexity:
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Heaps can be stored in arrays without using any pointers; this is due to the ____________ nature of the binary tree,
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What is the total time to heapify?
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The function f(n)= n(logn+1)/2 is asymptotically equivalent to n log n. Here Upper Bound means the function f(n) grows asymptotically ____________ faster than n log n.
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When we call heapify then at each level the comparison performed takes time
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Quick sort is best from the perspective of Locality of reference.
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In addition to passing in the array itself to Merge Sort algorithm, we will pass in _________other arguments which are indices.
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For the sieve technique we solve the problem,
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Which may be stable sort:
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What type of instructions Random Access Machine (RAM) can execute?
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In Sieve Technique we do not know which item is of interest
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We cannot make any significant improvement in the running time which is better than that of brute-force algorithm.
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Cont sort is suitable to sort the elements in range 1 to k
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Random access machine or RAM is a/an
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The running time of quick sort depends heavily on the selection of
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For small values of n, any algorithm is fast enough. Running time does become an issue when n gets large.
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In pseudo code, the level of details depends on intended audience of the algorithm.w
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While solving Selection problem, in Sieve technique we partition input data __________w
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In selection algorithm, because we eliminate a constant fraction of the array with each phase, we get the
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For Chain Matrix Multiplication we can not use divide and conquer approach because,
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Algorithm analysts know for sure about efficient solutions for NP-complete problems.
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The definition of Theta-notation relies on proving ___________asymptotic bound.
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The analysis of Selection algorithm shows the total running time is indeed ________in n,
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The Knapsack problem belongs to the domain of _______________ problems.
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A point p in 2-dimensional space is usually given by its integer coordinate(s)____________
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In the analysis of Selection algorithm, we make a number of passes, in fact it could be as many as,
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The sieve technique is a special case, where the number of sub problems is just
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The time assumed for each basic operation to execute on RAM model of computation is-----
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A (an) _________ is a left-complete binary tree that conforms to the heap order
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The O-notation is used to state only the asymptotic ________bounds.
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A RAM is an idealized machine with ______________ random-access memory.
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For the heap sort we store the tree nodes in
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