Fall 2014 ASSIGNMENT
PROGRAM - Master of Science in
Information Technology (MSc IT)Revised Fall 2011
SEMESTER - 2
SUBJECT CODE & NAME – MIT203-
ANALYSIS AND DESIGN OF ALGORITHMS
CREDIT 4 BK ID B1480 MAX.
MARKS 60
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Q1.
List and explain the properties of Algorithms.
Answer:
Properties of algorithms
An algorithm may have zero or
more inputs externally and it should produce one or more output. Also, an
algorithm must terminate after a finite number of steps. Properties of
algorithm include:
1. Correctness
2. Definiteness
3. Finiteness
4. Effectiveness
5. Generality
Q2.
Write a detail note on sequential search.
Answer:
Definition – Sequential
search is a process for finding a particular value in a list that checks every
element (one at a time) in sequence till the desired element is found.
Sequential search is the simplest
brute force search algorithm. It is also known as linear search.
Q3. What is mean by
Topological sort? And explain with example. 5+5=10
Answer: Topological sort is done using a
directed acyclic graph (DAG), which is a linear ordering of all vertices G= (V,
E) is an ordering of all vertices such that if G contains an edge (u,
4. Explain good-suffix and
bad-character shift in Boyer-Moore algorithm. 5+5=10
Answer:
Good suffix Shift
This shift helps in shifting a matched
part of the pattern, and is denoted by Q. Good suffix shift Q is applied after
0 < k < m characters are matched.
Q5.
Explain Lower – Bound Arguments? What are the methods help to make an algorithm
more efficient?
Answer:
Lower–bound
means calculating the minimum amount of work required to solve the problem.
While obtaining the lower–bound of the algorithm we look for the limits of
efficiency of any algorithm that can solve the problem.
Q6.
Write an approximation Algorithms for NP – Hard Problems.
Answer:
Combinatorial
optimization problems lie within a finite but huge feasible region.
Underlying
principles
An NP-Hard
problem is one for which the algorithm can be translated to one that can solve
any NP-problem (non-deterministic polynomial time). Many optimization problems
do not have an algorithm that can find a solution for all instances. Sometimes,
when trying to find an optimal solution to some problems we realize that it is
NP-Hard. Such problems also do not have any
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