Data structures are a very important part of software development. In the interview process, data structure questions might be asked as part of an assessment that is done to filter out those with less experience from those more experienced.

A data structure is a way that an application stores and organizes its information, which can be anything from numerical values to arrays of details on a user. There are many ways in getting through these questions, but there are some common ones found in software engineer interviews.

The interview process for a software developer can be a stressful experience if you don't know the right questions to ask. This article reviews some common data structure questions to help you prepare for your next interview!

**1. What is a Stack?**

A stack is a data structure in Computer Science where data are stored on the top of the stack by pushing it to the top, and off the top by popping it off.

A stack is a Last In, First Out (LIFO) data structure. It consists of a collection of data elements "stacked" on top of each other.

What makes a stack special is that it does not incur the space of repeated overwriting. It is also easier to access items in the stack since they are physically located at one address instead of complex memory addresses

**2. What is a Queue?**

Queue is a data structure in a computer science term. It's a simple in-memory list in which either new or old items can be added at one end and removed from the other.

Queue can be defined as a class of data structures comprising those structures that are used for implementing a wait-free algorithm or a data flow network. The queue is also called first in first out (FIFO).

**3. What is a Linked List?**

A linked list is a data structure that consists of a series of items that are linked together by pointers. This linked list can be seen as a sequence.

It is composed of nodes where the nodes contain the data and children which contain pointers to the following node. This allows linked lists to grow dynamically.

A linked list is a type of data structure that stores an ordered collection of data elements. An element can be a value, item, or record.

**4. What is an Array?**

Arrays are the most common data structure used in programming. An array is a list of variables, which allows you to store multiple values in a single line.

An array is like a list but has some features that make it better. An array is declared without specifying the size of the items in the array, meaning they can be finite or infinite.

Arrays can be accessed using their index positions, which range from 0 to one less than the size of the array minus 1.

**5. What is searching?**

A searching algorithm is a technique used in computer algorithms to find an item of interest. For example, searching can be used recursively to show the descendants of the letter "a". Searching algorithms are also used for data structures such as lists or trees that have items of interest.

**6. List out different Searching Algorithms?**

- Linear Search
- Binary Search

**7. What is Binary Search?**

Binary search compares the target value to the middle element of the array. If they are not equal, the half in which the target cannot lie is eliminated and the search continues on the remaining half until one is reached where their values are equal. If the search ends with the remaining half being empty, the target is not in the array.

**8. What is Sorting?**

Sorting is a way of arranging data in ascending or descending order. Sorting is a process that decides which records in an ordered collection should be placed into the smallest or largest container.

Sorting can be performed on any data set, such as an array of numbers, text strings, records in a database table, and so on. A sorting algorithm is used to determine which of the items in a group should be placed in what order.

**9. List out different Sorting Algorithms**

- Bubble Sort
- Quick Sort
- Insertion Sort
- Selection Sort
- Merge Sort

**10. What is a Tree Data Structure?**

In computer science, a tree structure is a data structure that encapsulates parent-child relations as a tree. The branches of the tree can have data internally and externally, similar to how a tree branches out into smaller trees.

A tree data structure is a structure that contains many different data elements, ordered in levels with nodes. A node in trees can contain other nodes, so trees are also called hierarchical data structures. Historically, trees were developed by analyzing the disk block address lines of hard disks or datasets stored on tape drives.

**11. What is a hashmap?**

A hashmap is a very efficient data structure that uses an elaborately worked out technique to store key/value pairs efficiently. It can be extended to provide faster lookup operations so it is often the default choice if the developer doesn't need quicksort, binary search, or another expensive but useful data structure.

Hashing is a dynamic data structure where a key is associated with a certain value. Hashmaps are often used in programming to map keys to values.

They are often used in combination with hashing algorithms, which make it possible for hashmaps to be very fast when it comes to searching, adding, or updating elements. When keys are stored on a disk or memory, they can reference structures of any length.

**12. What is a Binary Search Tree?**

A Binary search tree is a data structure that consists of nodes where the value of each node is less than or equal to the values of its two child nodes. A binary search tree uses a sorted list to help locate items, and it saves time with comparisons.

**13. List out different types of Queue?**

- Simple Queue
- Circle Queue
- Double Ended Queue
- Circular Queue

**14. Explain about Greedy Algorithms**

Greedy algorithms are a class of algorithms that evaluate subsets of the search space in order to find the best match. For example, suppose you want to travel from one place to another and you don't know how far away the closest spot is. At every one of these locations, there may be a closer spot, according to your set criteria such as traffic intensity and walking/driving time, etc. With greedy algorithms, we find these closest spots before leaving any unvisited location.

**15. What is dynamic programming?**

Dynamic programming is the process of constructing code that executes both before and after its events. Dynamic programming is a process of searching for the optimal solution to a problem, which involves calculating a succession of changes to a given set of cumulative costs and evaluating their effects on the goal.

Dynamic programming is a process where variables known as states are calculated. For example, if you wanted to know what time it is in another city based on the current date and the current day, then state one would be 12 AM, state two would be 1 AM, state three would be 2 AM, etc.