20 JavaScript Algorithms Interview Questions and Answers

As a JavaScript developer, you may be asked algorithm questions during your job interview. These questions assess your ability to solve problems and think critically. While you may not be expected to have a complete understanding of algorithms, being able to discuss the basics shows that you have the potential to learn and grow in the role. In this article, we review some commonly asked JavaScript algorithm questions and how you can answer them.

JavaScript Algorithms Interview Questions and Answers

Here are 20 commonly asked JavaScript Algorithms interview questions and answers to prepare you for your interview:

1. What is an algorithm?

An algorithm is a set of instructions or a set of rules that can be followed in order to solve a problem.

2. What are the basic characteristics of a good algorithm?

A good algorithm is one that is both efficient and effective. An efficient algorithm is one that runs quickly and uses minimal resources. An effective algorithm is one that produces the desired results.

3. Can you explain how an algorithm can be evaluated?

There are a few different ways to evaluate an algorithm. One common way is to measure the time complexity, which is the amount of time it takes for the algorithm to run. Another way to evaluate an algorithm is to measure the space complexity, which is the amount of memory the algorithm uses.

4. What is your understanding of Big O notation in context with algorithms?

Big O notation is a way of measuring the efficiency of an algorithm. It looks at the worst case scenario for an algorithm in order to determine how well it will perform. The goal is to find an algorithm with the best possible Big O notation, as this will mean that it is the most efficient.

5. Why do we need to know about algorithms and data structures?

Algorithms and data structures are the foundation on which computer programs are built. Without a solid understanding of how to design efficient algorithms and data structures, it would be very difficult to write programs that are both effective and efficient.

6. What does it mean for one algorithm to be better than another?

When we say that one algorithm is better than another, we typically mean that it is more efficient in terms of time or space complexity. In other words, the better algorithm will complete the task in less time or with less memory usage.

7. How can you compare two algorithms based on their time complexity?

The time complexity of an algorithm is the amount of time it takes to run the algorithm as a function of the input size. There are two common ways to compare the time complexity of two algorithms: asymptotic analysis and worst-case analysis. Asymptotic analysis looks at the limiting behavior of the algorithm as the input size goes to infinity. Worst-case analysis looks at the maximum amount of time the algorithm could possibly take for any given input size.

8. Is it possible to write an algorithm that has infinite loops? If yes, then what’s the best way to handle them?

Yes, it is possible to write an algorithm that has infinite loops. The best way to handle them is to use a break statement to exit out of the loop when a certain condition is met.

9. Which sorting technique will work faster if the number of elements to be sorted is very small?

If the number of elements to be sorted is very small, then any sorting technique will work faster. The reason for this is that the overhead associated with most sorting algorithms is much greater than the actual time it takes to sort a small number of elements. For this reason, it is generally recommended to use the simplest sorting algorithm possible when sorting a small number of elements.

10. What is recursion? Can you give me some examples of recursive functions?

Recursion is a function that calls itself. A good example of a recursive function is one that is used to calculate the factorial of a number. The factorial of a number is the product of all the positive integers less than or equal to that number. So, the factorial of 5 would be 5 * 4 * 3 * 2 * 1, or 120. A recursive function to calculate the factorial of a number would look something like this:

function factorial(n) {
if (n === 1) {
return 1;
} else {
return n * factorial(n – 1);
}
}

11. What are the various steps involved in creating a new data structure?

The first step is to identify the purpose of the data structure and the type of data it will store. The second step is to select the appropriate data structure type. The third step is to design the data structure. The fourth step is to implement the data structure in code. The fifth step is to test the data structure.

12. When would you use an array vs a list vs a map?

There is no definitive answer to this question, as it depends on the specific situation and data involved. However, in general, an array is best suited for storing a sequence of data that can be accessed by index, a list is best suited for storing a sequence of data that can be accessed in order, and a map is best suited for storing data that is associated with keys.

13. Where is it most appropriate to use a linked list over an array?

Linked lists are best used when you need to insert or delete elements from the list frequently, as they are much more efficient at doing so than arrays. Arrays are better suited for cases where you need to access elements randomly, as they can be accessed directly by their index.

14. Why might a hash table not be the best choice for storing large amounts of data?

Hash tables are not well suited for storing large amounts of data because they require a lot of memory to store all of the data. Additionally, hash tables can be slow to access large amounts of data.

15. Can you name the worst-case scenarios for binary search and why they occur?

The worst-case scenario for binary search is when the target value is not present in the array, or when the array is not sorted. In either of these cases, the algorithm will have to search through the entire array before it can determine that the target value is not present.

16. Does swapping two variables require a temporary variable or is there a more elegant solution?

There are a few ways to swap two variables without using a temporary variable. One way is to use arithmetic operators:

“`
a = a + b;
b = a – b;
a = a – b;
“`

Another way is to use the bitwise XOR operator:

“`
a = a ^ b;
b = a ^ b;
a = a ^ b;
“`

Both of these methods work because when you add or XOR two numbers, the result is a number that is different from both of the original numbers. So when you store that result in one of the original variables, you are effectively overwriting the original value.

17. How do you go about finding the middle element in a singly linked list without knowing its length?

There are a few different ways to do this. One way would be to keep track of two pointers, one that moves one node at a time and one that moves two nodes at a time. When the latter pointer reaches the end of the list, the former pointer will be pointing to the middle element. Another way to do this would be to keep track of the length of the list as you traverse it. When you reach the end of the list, you can simply divide the length by 2 to find the middle element.

18. Given a list of unsorted numbers, how would you create a separate sorted list from them using no additional storage space?

You could use a sorting algorithm like quicksort or heapsort, but that would require additional storage space. A better solution would be to use a sorting algorithm like selection sort or insertion sort, which don’t require any additional storage space.

19. Can you determine whether two strings are permutations of each other by comparing the number of times each character occurs in both strings? If so, what is your approach?

Yes, you can determine whether two strings are permutations of each other by comparing the number of times each character occurs in both strings. One approach would be to create two arrays, one for each string, and then sort both arrays. Once the arrays are sorted, you can compare the two arrays element by element to see if they are the same. If the arrays are not the same, then the strings are not permutations of each other.

20. Can you tell me which programming languages make it easier to implement algorithms and data structures?

There is no definitive answer to this question, as it depends on the specific algorithm or data structure you are trying to implement. However, some languages that are generally considered to be good for implementing algorithms and data structures include C++, Java, and Python.