Are you a coder, software developer, or programmer looking for a new job? There is a slight chance that you might be interviewed using Codility, a web-based platform companies use to determine the coding and programming abilities of different job applicants. Our article will help you prepare for your upcoming interview by looking at some of the questions to expect in a Codility Interview. Feel free to use our responses to find the correct answers for your upcoming interview and increase your chances of landing the job. Let’s get started!
1. Explain Dynamic Programming And Recursion
Dynamic programming is a popular method used to find solutions to different technical problems by breaking them down into smaller units and solving each unit once, then storing the solutions in an array or table to facilitate later lookup. It is generally used when subproblems overlap to avoid redundant computations. On the other hand, recursion is a programming technique used to solve problems by allowing functions to call themselves. Even though it can also be used to solve breakable problems, it doesn’t work if the subproblems are solved severally.
2. What Is The Difference Between Dynamic Programming And Recursion?
Even though dynamic programming and recursion both offer a way of dealing with problems that can be broken down into subproblems, the former stores reusable solutions to its subproblems while the latter independently solve subproblems with the possibility of repeating computations.
3. Can You Tell The Difference Between A Stack And A Queue?
Coders and computer programmers use stacks and queues to store and retrieve data. However, a queue is a first-in-first-out (FIFO) data structure where the first items added to the queue are removed first, while a stack is a last-in-first-out (LIFO) data structure where the last added item is the first to be eliminated. The main difference, therefore, exists in the first items to be removed.
4. When Would You Use A Stack And A Queue?
Given that these two data structures differ in the first items to be removed, I would use a queue to process items in their receipt order, for example, in a job queue or messaging system, given that it follows a FIFO approach. In contrast, I would use a stack when there is a need to track function calls or operations order, for example, in a web browser’s history or recursive algorithm, given its LIFO approach.
5. Explain The Time Complexity Of A Binary Search Algorithm. Can You Tell Its Working Mechanisms?
To understand the working mechanism of the time complexity of a binary search algorithm, it’s crucial first to mention that it is O(log)n, where n refers to the number of elements found in the sorted array. Whenever a binary search runs, the array is repeatedly divided in half. The system also checks whether the target element is in the left or right half. The process is then repeated depending on the side the target element is located until the target element is found or determined not to be in the array. This search algorithm works perfectly when dealing with a sorted array, given that half of the remaining elements at each step are eliminated. The time complexity will quickly degrade to O(n) if the array is not sorted.
6. Differentiate Between A Breadth-First Search And A Depth-First Search
Popularly known as BFS and DFS, these two searches are popularly used to traverse trees and graphs. They differ depending on the order in which they visit nodes, i.e., DFS uses the Depth-First order to visit nodes, completing one branch first before going back to other branches, while BFS uses the breadth-first order which requires visiting the nodes at the same level first before going to the next level and so on. BFS comes in handy when finding the shortest path between two nodes, while DFS is mainly used to explore all paths in a given graph. The former is also used to visit all nodes at a given depth before proceeding to the next one, while the latter comes in handy when it’s necessary to find a path meeting given criteria.
7. Define A Binary Tree. What’s The Difference Between A Binary Tree And A Binary Search Tree?
The binary tree is one of the most common data structures. It is a tree data structure where the nodes are given not more than two children, i.e., the left and right child. On the other hand, a binary search tree is a unique binary tree where each node has a value greater than or equal to that on the left subtree and less than or equal to that on the right subtree. This property allows efficient sorting and searching of elements in the binary search tree.
8. Define An Abstract Data Type And Give An Example
An abstract data type, commonly referred to as an ADT, is a special data type defined by its operations or behaviors and not its implementation. It normally sums up operations and data into a single unit for modular or reusable usage. Common examples include stacks, queues, lists, trees, and trees. A stack supports two operations: push and pop. The first operation, push, add elements from the top, while pop, the second supported operation, removes elements from the data structure.
9. Define Memorization And How It Works
Memorization is a common, important technique in programming. It caches the results of previous computations to speed up recursive algorithms. The previous function calls results are stored in an array or table that must be checked before computing a new result, eliminating redundant computations. It, therefore, helps improve the efficiency of recursive algorithms.
10. Do You Know How Abstract Classes Differ From Interfaces In Java?
An abstract class can have instances, constructors, and variables, which lack in the interface. It can also carry abstract and concrete methods and cannot be instantiated. On the other hand, an interface is a group of abstract methods that a class can implement. Abstract classes are normally used to create a base class to offer a few implementations for subclasses, while interfaces come in handy to define a set of methods to be implemented by the class if one doesn’t want to offer any implementations.
11. Differentiate Between A Static Method And An Instance Method
Static methods belong to the class and are usually called without creating a class instance, while instance methods are owned by the objects and can only be called by the class instance. Due to these differing capabilities, static methods can only access other static methods and static variables, not instance methods or variables. An operation that does not depend on a particular class instance or modify an instance’s state requires a static method, while an instance method works for the opposite.
12. Differentiate Between A Linked List And Array
Linked lists and arrays are common data structures, like stacks and queues, used to store and retrieve data. The array stores fixed-size element collections, given that it is a continuous memory block, while linked lists are made up of nodes, each referring to the next node in a given list. Every linked list also contains a value.
13. When Would You Use A Linked List And An Array?
Given their constant time complexity, I would use an array when accessing elements by their indexes or iterating over the elements in a given collection that promotes elements access via index. It comes in handy since the insertion and deletion of elements can be expensive, owing to the need to shift every element after the deletion and insertion points. On the other hand, I would use a linked list to insert or delete elements frequently or when unsure of the collection size. It helps when accessing elements by indexes is not viable since iterating over a list till one reaches the desired index can be expensive.
14. Differentiate Between A Binary Search Tree And A Heap
Binary search trees and heaps are unique data structures that store and retrieve data. In a heap, the parent mode is greater than or of the same value as its children or smaller than and equal to its children, making it a complete binary tree. On the other hand, a binary search tree has nodes with keys greater than all the keys in the left subtree and smaller than the keys in the right subtree.
15. When Is The Right Time To Use A Heap And A Binary Search Tree?
Heaps and search trees are used on different occasions. Thanks to their logarithmic time complexity, I would use a binary search tree to quickly insert, search and delete elements in a collection that supports the insertion, deletion, and search of elements. On the other hand, I would use a heap to quickly figure out the maximum or minimum element in a given collection or maintain a partially ordered collection owing to its logarithmic time complexity supporting the identification of minimum or maximum element and a constant time complexity for element insertion or deletion.
16. Differentiate Between A Pessimistic And Optimistic Locking Strategy As Used In Data Management Systems
Optimistic and pessimistic locking strategies control data access. The locking strategy prevents simultaneous access to the same data by two transactions capable of causing errors and inconsistencies, while optimistic locking permits several transactions to simultaneously read and write the same data by assuming that conflicts between them are rare. However, before committing changes, it checks for conflicts, while a pessimistic locking strategy locks data exclusively to only one transaction by assuming the commonness of the transactions. Other transactions can’t access data in the latter unless the lock is lifted.
17. Define A Deadlock In Multi-Threaded Programming And Explain How It Can Be Avoided
Deadlock can be a common occurrence in Multi-Threaded programming. It happens following the blockage of two or more threads as they await a source release, meaning they can’t proceed. It is the main reason why programs hang or crash since it’s difficult to debug too. Luckily, deadlocks can be avoided in the following ways:
- Deadlock detection and recovery- Deadlock detection and recovery is a technique that uses algorithms to detect the occurrence of a deadlock and allow the system to recover from it by aborting one or more transactions.
- Consistently acquiring locks- Consistently acquiring locks can prevent circular wait when several threads are involved.
- Timeouts- One can limit the time a thread takes to wait for a lock before releasing the lock and trying once more.
- Lock-free or wait-free algorithms- These are algorithms that do not need locks and equally guarantee progress in the event that certain threads are blocked.
18. What’s The Difference Between A Synchronous And An Asynchronous Programming Model?
A program waits for one task to end before moving to the next in a synchronous model while a program executes even as the task runs in a synchronous programming model. A notification is usually given upon the completion of the task.
19. When Would You Use A Synchronous And Asynchronous Programming Model?
Synchronous and asynchronous programming models should be used on different occasions. The former comes in handy for short tasks incapable of blocking the program for a longer period or when a program is free as the task runs. On the other hand, asynchronous programming models are advisable for longer tasks capable of blocking the programs for a longer duration. It also comes in handy for programs that remain occupied as the task runs. The use cases explain why asynchronous programming can be more complex than synchronous programming.
20. Explain What A Database Index Is And How It Works
A database index is a database structure that speeds up a database table’s data retrieval operations. Once the index is created in one or more table columns, it stores a sorted data copy pointing to the original data in the columns. The database can use the index to quickly locate the matching rows when a query involving the indexed columns is executed, saving it from scanning the whole table. Indexes are generally used to sort, search, or group using the index columns or whenever there is a need to enforce a select column or constraint. However, its use is limited when the table is small, or the data is static. Also, it can slow down operations such as insert, delete, and update.
21. Differentiate Between A Static And A Dynamic Library
A static library comprises object files linked into a program at compile time. The compiled code for functions a given program uses is normally stored in the object files and merged into the program executable. On the other hand, a dynamic or shared library exists as a separate file with compiled codes for functions. It is normally loaded into memory and linked to the program as it runs.
22. Explain The Use Cases Of Static And Dynamic Libraries.
Static libraries are normally used to ensure that the codes required by the program are available at runtime and to avoid the costs associated with loading and linking shared databases. On the other hand, dynamic libraries allow code sharing between several programs. They also allow code updates without recompiling the programs dependent on it.
23. What Do You Understand By An Inner And Outer Join?
Inner and outer joins are common features in SQL that combine rows from at least two tables sharing a column. They only differ in the rows returned. The inner join returns the rows with matching values in both tables, while the outer one returns the rows from a table and matching rows from the others. It goes ahead to offer a NULL response if there is no match. Inner joins are used to retrieve data found in both tables without including the non-matching data, while the outer join is used to retrieve data from one table even if the other table lacks matching rows.
24. Define A Hash Table And How It Works
Hash tables are common data structures used in programs. They use hash functions to map indices keys, facilitating the storage of several elements in arrays. The key is recognized as an input, and the hash function creates an index at the element’s storage location. Thanks to the hash table, elements are stored in the array at the computed index. In the event of a collision which happens when two elements have a similar hash value, the elements are stored in a linked list.
25. Define A Priority Queue And Define How It Works
A priority queue stores several elements. Each element collection has a priority, with the elements inserted in the priority queue in no particular order. However, they are removed from the priority queue in order of their priority, meaning the element with the highest priority gets eliminated first. Priority queues are generally implemented using a heap, the binary whose parent node’s value is higher than or equal to the children’s values.
Above are some of the most common interview questions in Codility Interviews. Ensure that you take some time to brainstorm the perfect answers to increase your chances of landing your upcoming programming or coding interviews. We wish you all the best in your upcoming interview and remember to work on your first impression too.