Sureti Insurance Marketing Interview Questions and Answers

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Q1. Given a Linked List Arrange it into Positive and Negative Alternatively

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Arrange a Linked List into Positive and Negative Nodes Alternately

Traverse the Linked List and separate positive and negative nodes into two separate lists
Merge the two lists alternately to form the final arrangement
Ensure to handle cases where one list is longer than the other

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Currently using a tech stack consisting of Java, Spring Boot, React, and PostgreSQL.

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Tech debt should be managed by prioritizing, tracking, and addressing it regularly.

Prioritize tech debt based on impact on product, codebase, and team productivity.
Track tech debt using tools like Jira or Trello to ensure visibility and accountability.
Address tech debt incrementally by allocating time in sprints or dedicated tech debt cleanup sprints.
Involve the team in identifying and addressing tech debt to foster a culture of continuous improvement.

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DB indexing is a technique used to improve the performance of database queries by creating data structures that allow for faster data retrieval.

Indexes are created on specific columns in a database table to speed up data retrieval.
When a query is executed, the database engine uses the index to quickly locate the rows that match the query criteria.
Types of indexes include clustered, non-clustered, unique, and composite indexes.
Regularly updating statistics and maintaining inde...read more

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I have 5 years of experience leading technical teams, handling team dynamics, delegating tasks, and resolving conflicts.

Led a team of 10 developers in a software development project, ensuring timely delivery and quality output
Managed team members with diverse skill sets, assigning tasks based on individual strengths and weaknesses
Resolved conflicts within the team by facilitating open communication and finding mutually agreeable solutions

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LRU Cache is a data structure that stores the most recently used items, discarding the least recently used items when full.

Use a combination of a doubly linked list and a hashmap to implement LRU Cache efficiently.
Keep track of the most recently used item by moving it to the front of the linked list.
When the cache is full, remove the least recently used item from the end of the linked list and the hashmap.
Ensure constant time complexity for both get and put operations.