# Data Structures Interview Questions and Answers

**Ques 11. What is the quickest sorting method to use?**

**Ans.** The answer depends on what you mean by quickest. For most sorting problems, it just doesn't matter how quick the sort is because it is done infrequently or other operations take significantly more time anyway. Even in cases in which sorting speed is of the essence, there is no one answer. It depends on not only the size and nature of the data, but also the likely order. No algorithm is best in all cases. There are three sorting methods in this author's toolbox that are all very fast and that are useful in different situations. Those methods are quick sort, merge sort, and radix sort.

The Quick Sort

The quick sort algorithm is of the divide and conquer type. That means it works by reducing a sorting problem into several easier sorting problems and solving each of them. A dividing value is chosen from the input data, and the data is partitioned into three sets: elements that belong before the dividing value, the value itself, and elements that come after the dividing value. The partitioning is performed by exchanging elements that are in the first set but belong in the third with elements that are in the third set but belong in the first Elements that are equal to the dividing element can be put in any of the three sets the algorithm will still work properly.

The Merge Sort

The merge sort is a divide and conquer sort as well. It works by considering the data to be sorted as a sequence of already-sorted lists (in the worst case, each list is one element long). Adjacent sorted lists are merged into larger sorted lists until there is a single sorted list containing all the elements. The merge sort is good at sorting lists and other data structures that are not in arrays, and it can be used to sort things that don't fit into memory. It also can be implemented as a stable sort.

The Radix Sort

The radix sort takes a list of integers and puts each element on a smaller list, depending on the value of its least significant byte. Then the small lists are concatenated, and the process is repeated for each more significant byte until the list is sorted. The radix sort is simpler to implement on fixed-length data such as ints.

**Ques 12. How can I search for data in a linked list?**

**Ans.**Unfortunately, the only way to search a linked list is with a linear search, because the only way a linked list's members can be accessed is sequentially. Sometimes it is quicker to take the data from a linked list and store it in a different data structure so that searches can be more efficient.

**Ques 13. What is the heap?**

**Ans.**The heap is where malloc(), calloc(), and realloc() get memory.

Getting memory from the heap is much slower than getting it from the stack. On the other hand, the heap is much more flexible than the stack. Memory can be allocated at any time and deallocated in any order. Such memory isn't deallocated automatically; you have to call free().

Recursive data structures are almost always implemented with memory from the heap. Strings often come from there too, especially strings that could be very long at runtime. If you can keep data in a local variable (and allocate it from the stack), your code will run faster than if you put the data on the heap. Sometimes you can use a better algorithm if you use the heap faster, or more robust, or more flexible. Its a tradeoff.

If memory is allocated from the heap, its available until the program ends. That's great if you remember to deallocate it when you're done. If you forget, it's a problem. A �memory leak is some allocated memory that's no longer needed but isn't deallocated. If you have a memory leak inside a loop, you can use up all the memory on the heap and not be able to get any more. (When that happens, the allocation functions return a null pointer.) In some environments, if a program doesn't deallocate everything it allocated, memory stays unavailable even after the program ends.

**Ques 14. What is the easiest sorting method to use?**

**Ans.**The answer is the standard library function qsort(). It's the easiest sort by far for several reasons:

It is already written.

It is already debugged.

It has been optimized as much as possible (usually).

Void qsort(void *buf, size_t num, size_t size, int (*comp)(const void *ele1, const void *ele2));

**Ques 15. What is the bucket size, when the overlapping and collision occur at same time?**

**Ans.**One. If there is only one entry possible in the bucket, when the collision occurs, there is no way to accommodate the colliding value. This results in the overlapping of values.

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