Test Series - Data Structure

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Test Number 78/115

Q: What is the use of the bin data structure?
A. to have efficient insertion
B. to have efficient deletion
C. to have efficient region query
D. to have efficient traversal
Solution: Bin data structure allows us to have efficient region queries. A frequency of bin is increased by one each time a data point falls into a bin.
Q:  What is the worst case time complexity of query operation(n is the no. of candidates)?
A. O(1)
B. O(n)
C. O(log n)
D. O(n log n)
Solution: The worst case in a bin query occurs when all the candidates are concentrated in one bin. So in this case the time complexity is O(n).
Q:  What is the worst case time complexity of delete operation(n is the no. of candidates)?
A. O(1)
B. O(n)
C. O(log n)
D. O(n log n)
Solution: The worst case in a bin delete operation occurs when all the candidates are concentrated in one bin. So in this case the time complexity is O(n).
Q: What is the worst case time complexity of insertion operation(n =no. of candidates)?
A. O(1)
B. O(n)
C. O(log n)
D. O(n log n)
Solution: The worst case in a bin insert operation occurs when all the candidates are concentrated in one bin. So in this case the time complexity is O(1).
Q: What is computational geometry?
A. study of geometry using a computer
B. study of geometry
C. study of algorithms
D. study of algorithms related to geometry
Solution: Computational geometry deals with the study of algorithms which can be expressed in terms of geometry. Bin data structure is an example of it.
Q: What will be the time complexity of query operation if all the candidates are evenly spaced so that each bin has constant no. of candidates? (k = number of bins query rectangle intersects)
A. O(1)
B. O(k)
C. O(k2)
D. O(log k)
Solution:  The process of query becomes faster in a case when the number of candidates are equally distributed among the bins. In such a case the query operation becomes O(k).
Q: What will be the time complexity of delete operation if all the candidates are evenly spaced so that each bin has constant no. of candidates? (m = number of bins intersecting candidate intersects)
A. O(1)
B. O(m)
C. O(m2)
D. O(log m)
Solution: The process of deletion becomes faster in a case when the number of candidates are equally distributed among the bins. In such a case the query operation becomes O(m). It is practically slower than insertion in this case.
Q: What will be the time complexity of insertion operation if all the candidates are evenly spaced so that each bin has constant no. of candidates? (m = number of bins intersecting candidate intersects)
A. O(1)
B. O(m)
C. O(m2)
D. O(log m)
Solution: The process of insertion becomes faster in the case when the number of candidates are equally distributed among the bins. In such a case the query operation becomes O(m). It is practically faster than deletion in this case.
Q: Efficiency of bin depends upon ___________
A. size of query and candidates
B. location of query and candidates
C. location and size of query and candidates
D. depends on the input
Solution: Efficiency of bin depends upon the location and size of query and candidates. It is similar to that of a hash table.
Q: Bigger the query rectangle the better is the query efficiency.
A. true
B. false
C. none
D. ...
Solution: Efficiency of bin depends upon the location and size of query and candidates. Also, the smaller is the query rectangle the better is the query efficiency.

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