Design and analysis of algorithms
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- What is the time complexity of linear search?
- Define algorithm
- What is Fast Fourier Transform (FFT)?
- Explain divide and conquer technique
- Give the recurrence relation for the time complexity of merge sort algorithm.
- Differentiate between exponential versus polynomial running time.
- State the principle of optimality used in dynamic programming.
- How is the accuracy of approximation algorithm measured?
- Algorithm A performs 10n 2 basic operations, and algorithm B performs 300 logn basic operations. For what value of n does algorithm B start to show its better performance?
- What do you mean by NP-complete?
- What do you mean by Amortized Analysis?
- What is Big ‘Oh’ notation?
- Define direct recursive and indirect recursive algorithms.
- What do you mean by time complexity and space complexity of an algorithm?
- Define control abstraction
- What are the features of dynamic programming?
- Define explicit constraint
- Define Branch-and-Bound method
- What are the factors that influence the efficiency of the backtracking algorithm?
- What is NP hard problem?
- Show that for any real constants a and b, where b > 0, (n + a)b = θ(nb)
- What is the time complexity of conventional matrix multiplication method and Strassen's matrix multiplication method?
- What-is the advantage of using merge-sort algorithm over quick-sort algorithm?
- What are NP-complete problems? Give examples.
- What are the applications of BFS and DFS algorithms?
- What are the basic steps in divide-and-conquer strategy of algorithm design? Out of these basic steps which step is not always required even if problem instance is big?
- What are the time complexities of pre-processing stage and matching stage of KnuthMorris-Pratt string matching algorithm?
- What do you mean by polynomial time reduction?
- What would be the running time of radix sort on an array of n integers in the range 0 ... n5 -1 when base-10 representation is used?
- Define convex hull.