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In this unit, we described about the data structure Queue. It had two ends. One is front from where the elements can be removed and the other is rear where the elements can be inserted. A queue can be implemented via Arrays or Linked lists. Each illustration is having it's own advantages & disadvantages. The problems along arrays are that they are restricted in space. Therefore, the queue is having a restricted capacity. If queues are implemented via linked lists, then this problem is solved. Now, there is no restriction on the capacity of the queue. The only overhead is the memory occupied though the pointers.
There are a number of variants of the queues. Queues normally mean circular queues. In spite of linear queues, we also discussed circular queues in this unit. A particular type of queue called Dequeue was also discussed in this unit. Dequeues allows elements to be inserted or deleted at either of the rear or front. We also discussed the array & linked list implementations of Dequeue.
In order to analyze an algorithm is to find out the amount of resources (like time & storage) that are utilized to execute. Mostly algorithms are designed to work along with inputs
Q. Explain various graph traversal schemes and write their advantages and disadvantages. A n s . Graph Traversal Scheme is explained below In many troubles we wish
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Sequential files are most frequently utilized in commercial batch oriented data processing where there is the concept of a master file on which details are inserted periodically. F
Q. Calculate that how many key comparisons and assignments an insertion sort makes in its worst case? Ans: The worst case performance occurs in insertion
What are the conditions under which sequential search of a list is preferred over binary search? Sequential Search is a preferred over binary search when the list is unordered
Q. Describe the adjacency matrix and make the same for the given undirected graph. Ans: The representation of Adjacency Matrix: This representation consists of
What do you mean by complexity of an algorithm? The complexity of an algorithm M is the function f(n) which gives the running time and/or storage space need of the algorithm i
Complexity classes All decision problems fall in sets of comparable complexity, called as complexity classes. The complexity class P is the set of decision problems which ca
write an algorithm to search a particular node in linked list which returns " FOUND" or "NOT FOUND" as outcome.
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