IKIO Lighting Interview Questions and Answers

Implement Merge Sort algorithm to sort a sequence of numbers in non-descending order.

• Divide the input array into two halves recursively until each part has a size of '1'.

• Merge the sorted arrays to return one fully sorted array.

• Time complexity of Merge Sort is O(n log n).

Count nodes within K-distance from marked nodes in a connected, undirected, acyclic graph.

• Create an adjacency list to represent the graph.

• Use BFS to traverse the graph and calculate distances from marked nodes.

• Keep track of visited nodes and distances to avoid revisiting nodes.

• Return the count of nodes with distances less than 'K' from all marked nodes.

• Handle edge cases like empty graph or marked nodes.

Given coin denominations and a target value, find the total number of ways to make change.

• Use dynamic programming to keep track of the number of ways to make change for each value up to the target value.

• Iterate through each denomination and update the number of ways to make change for each value.

• Handle base cases such as making change for 0 value.

• Consider all possible combinations of denominations to make change for the target value.

Count occurrences of a given integer in a sorted array.

• Use binary search to find the first and last occurrence of X in the array.

• Calculate the count by subtracting the indices of the last and first occurrences.

• Handle cases where X is not present in the array.

Implement a Stack data structure using a Singly Linked List with operations in O(1) time.

• Create a class named Stack with getSize, isEmpty, push, pop, and getTop methods.

• Use a Singly Linked List to store the elements of the stack.

• Ensure each operation runs in O(1) time complexity.

• Handle edge cases like empty stack appropriately.

• Example: For input '5 3 10 5 1 2 4', the output should be '10 1 false'.

Pillars of OOPs are Inheritance, Encapsulation, Polymorphism, and Abstraction. Data science involves analyzing and interpreting complex data. ACID stands for Atomicity, Consistency, Isolation, Durability.

• Pillars of OOPs: Inheritance, Encapsulation, Polymorphism, Abstraction

• Data science: Analyzing and interpreting complex data to gain insights

• ACID: Atomicity, Consistency, Isolation, Durability