CS502-Midterm
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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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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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Counting sort has time complexity:
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Analysis of Selection algorithm ends up with,
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Quick sort is
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Quick sort is based on divide and conquer paradigm; we divide the problem on base of pivot element and:
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Which sorting algorithm is faster
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In which order we can sort?
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The sieve technique works where we have to find _________ item(s) from a large input.
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Which may be a stable sort?
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In Quick Sort Constants hidden in T(n log n) are
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The O-notation is used to state only the asymptotic ________bounds.
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In analysis, the Lower Bound means the function grows asymptotically at least as fast as its largest term.
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A point p in 2-dimensional space is usually given by its integer coordinate(s)____________
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When we call heapify then at each level the comparison performed takes time
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For Chain Matrix Multiplication we can not use divide and conquer approach because,
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In Quick sort, we don’t have the control over the sizes of recursive calls
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Algorithm is concerned with.......issues.
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Cont sort is suitable to sort the elements in range 1 to k
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For the sieve technique we solve the problem,
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The Knapsack problem belongs to the domain of _______________ problems.
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In Heap Sort algorithm, we build _______ for ascending sort.
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Asymptotic growth rate of the function is taken over_________ case running time.
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The time assumed for each basic operation to execute on RAM model of computation is-----
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Is it possible to sort without making comparisons?
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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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An in place sorting algorithm is one that uses ___ arrays for storage
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How many elements do we eliminate in each time for the Analysis of Selection algorithm?
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In the analysis of Selection algorithm, we eliminate a constant fraction of the array with each phase; we get the convergent _______________ series in the analysis,
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A (an) _________ is a left-complete binary tree that conforms to the heap order
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The reason for introducing Sieve Technique algorithm is that it illustrates a very important special case of,
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In ____________ we have to find rank of an element from given input.
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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 number of nodes in a complete binary tree of height h is
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In Sieve Technique we do not know which item is of interest
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The ancient Roman politicians understood an important principle of good algorithm design that is plan-sweep algorithm.
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The function f(n)=n(logn+1)/2 is asymptotically equivalent to nlog n. Here Lower Bound means function f(n) grows asymptotically at ____________ as fast as nlog n.
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One Example of in place but not stable sort is
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In plane sweep approach, a vertical line is swept across the 2d-plane and _______structure is used for holding the maximal points lying to the left of the sweep line.
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The definition of Theta-notation relies on proving ___________asymptotic bound.
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F (n) and g (n) are asymptotically equivalent. This means that they have essentially the same __________ for large n.
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The array to be sorted is not passed as argument to the merge sort algorithm.
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For the Sieve Technique we take time
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One example of in place but not stable algorithm is
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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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The sieve technique works in ___________ as follows
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What is the total time to heapify?
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