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Recent Software Engineer Interview Questions

Review this list of 650 Software Engineer interview questions and answers verified by hiring managers and candidates.
  • Deloitte logoAsked at Deloitte 
    3 answers

    "BETWEEN and HAVING clauses in SQL serve different purposes: 1. BETWEEN Clause Used to filter rows based on a range of values. Works with numeric, date, or text values. Can be used with WHERE or HAVING clauses. The range includes both lower and upper bounds. Example: Filtering employees with salaries between 30,000 and 50,000 `SELECT * FROM Employees WHERE salary BETWEEN 30000 AND 50000;` 2. HAVING Clause Used to filter **groups"

    Meenakshi D. - "BETWEEN and HAVING clauses in SQL serve different purposes: 1. BETWEEN Clause Used to filter rows based on a range of values. Works with numeric, date, or text values. Can be used with WHERE or HAVING clauses. The range includes both lower and upper bounds. Example: Filtering employees with salaries between 30,000 and 50,000 `SELECT * FROM Employees WHERE salary BETWEEN 30000 AND 50000;` 2. HAVING Clause Used to filter **groups"See full answer

    Software Engineer
    Concept
    +4 more
  • Meta logoAsked at Meta 
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    Software Engineer
    Behavioral
    +1 more
  • Add answer
    Software Engineer
    Behavioral
  • "I got it right"

    Rudransh V. - "I got it right"See full answer

    Software Engineer
    Data Structures & Algorithms
    +1 more
  • Amazon logoAsked at Amazon 
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    Software Engineer
    System Design
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  • Amazon logoAsked at Amazon 
    1 answer

    "class Node: def init(self, value): self.value = value self.children = [] def inorder_traversal(root): if not root: return [] result = [] n = len(root.children) for i in range(n): result.extend(inorder_traversal(root.children[i])) if i == n // 2: result.append(root.value) if n == 0: result.append(root.value) return result Example usage: root = Node(1) child1 = Node(2) chil"

    Teddy Y. - "class Node: def init(self, value): self.value = value self.children = [] def inorder_traversal(root): if not root: return [] result = [] n = len(root.children) for i in range(n): result.extend(inorder_traversal(root.children[i])) if i == n // 2: result.append(root.value) if n == 0: result.append(root.value) return result Example usage: root = Node(1) child1 = Node(2) chil"See full answer

    Software Engineer
    Data Structures & Algorithms
    +1 more
  • Apple logoAsked at Apple 
    1 answer

    "public class HashMap { public class Element { T key; V value; Element(T k, V v) { this.key = k; this.value = v; } } private static final int DEFAULT_CAPACITY = 16; private static final float LOAD_FACTOR = 0.75f; private LinkedList[] table = new LinkedList[DEFAULT_CAPACITY]; private int size = 0; private int threshold = (int) (DEFAULTCAPACITY * LOADFACTOR); public void put(T k"

    Md kamrul H. - "public class HashMap { public class Element { T key; V value; Element(T k, V v) { this.key = k; this.value = v; } } private static final int DEFAULT_CAPACITY = 16; private static final float LOAD_FACTOR = 0.75f; private LinkedList[] table = new LinkedList[DEFAULT_CAPACITY]; private int size = 0; private int threshold = (int) (DEFAULTCAPACITY * LOADFACTOR); public void put(T k"See full answer

    Software Engineer
    Data Structures & Algorithms
    +2 more
  • Goldman Sachs logoAsked at Goldman Sachs 
    1 answer

    "standard answer for this."

    Shar N. - "standard answer for this."See full answer

    Software Engineer
    Data Structures & Algorithms
    +1 more
  • Adobe logoAsked at Adobe 
    1 answer

    "create a queue push all cells with 0 into queue Mark all 1s as unvisited (-1 or large value) Run BFS for each cell, explore 4 directions If neighbor is unvisited:distance = current + 1 push into queue "

    Areeba M. - "create a queue push all cells with 0 into queue Mark all 1s as unvisited (-1 or large value) Run BFS for each cell, explore 4 directions If neighbor is unvisited:distance = current + 1 push into queue "See full answer

    Software Engineer
    Data Structures & Algorithms
    +2 more
  • LinkedIn logoAsked at LinkedIn 
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    Software Engineer
    Data Structures & Algorithms
    +2 more
  • Oracle logoAsked at Oracle 
    2 answers

    " At low level: I would use two stacks: one for forward history and other for backward history. i go to tryexponent.com => this url will be stored in backward history stack. i go to google => again this url will be stored in backward history stack. i press back => data from backward history will be popped and put in to forward history stack. I press forward => data from forward history stack will be popped and put in to backward history tab. Also, whenever i go to any url,"

    Anubhav S. - " At low level: I would use two stacks: one for forward history and other for backward history. i go to tryexponent.com => this url will be stored in backward history stack. i go to google => again this url will be stored in backward history stack. i press back => data from backward history will be popped and put in to forward history stack. I press forward => data from forward history stack will be popped and put in to backward history tab. Also, whenever i go to any url,"See full answer

    Software Engineer
    System Design
    +1 more
  • Adobe logoAsked at Adobe 
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    Software Engineer
    Data Structures & Algorithms
    +4 more
  • Capital One logoAsked at Capital One 
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    Software Engineer
    Data Structures & Algorithms
    +2 more
  • JP Morgan Chase logoAsked at JP Morgan Chase 
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    Software Engineer
    Data Structures & Algorithms
    +1 more
  • Adobe logoAsked at Adobe 
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    Software Engineer
    Data Structures & Algorithms
    +4 more
  • Adobe logoAsked at Adobe 
    1 answer

    "Use a representative of each, e.g. sort the string and add it to the value of a hashmap> where we put all the words that belong to the same anagram together."

    Gaston B. - "Use a representative of each, e.g. sort the string and add it to the value of a hashmap> where we put all the words that belong to the same anagram together."See full answer

    Software Engineer
    Data Structures & Algorithms
    +4 more
  • Walmart Labs logoAsked at Walmart Labs 
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    Software Engineer
    Behavioral
    +5 more
  • Meta logoAsked at Meta 
    1 answer

    "I first clarified what he needed for the leaderboard meaning did he need a gaming leaderboard system, a stock market leaderboard system where the trades placed would be ranked in terms of values or a coding platform leaderboard where the users are ranked as per the points earned by solving the problem? He answered that he wanted a multipurpose leaderboard system He was specifically interested in the design of the api part Explained him that assuming we had a flask api there would be a get re"

    GalacticInterviewer - "I first clarified what he needed for the leaderboard meaning did he need a gaming leaderboard system, a stock market leaderboard system where the trades placed would be ranked in terms of values or a coding platform leaderboard where the users are ranked as per the points earned by solving the problem? He answered that he wanted a multipurpose leaderboard system He was specifically interested in the design of the api part Explained him that assuming we had a flask api there would be a get re"See full answer

    Software Engineer
    System Design
  • Meta logoAsked at Meta 
    4 answers
    +1

    "Approach 1: Use sorting and return the kth largest element from the sorted list. Time complexity: O(nlogn) Approach 2: Use max heap and then select the kth largest element. time complexity: O(n+logn) Approach 3: Quickselect. Time complexity O(n) I explained my interviewer the 3 approaches. He told me to solve in a naive manner. Used Approach 1 had some time left so coded approach 3 also The average time complexity of Quickselect is O(n), making it very efficient for its purpose. However, in"

    GalacticInterviewer - "Approach 1: Use sorting and return the kth largest element from the sorted list. Time complexity: O(nlogn) Approach 2: Use max heap and then select the kth largest element. time complexity: O(n+logn) Approach 3: Quickselect. Time complexity O(n) I explained my interviewer the 3 approaches. He told me to solve in a naive manner. Used Approach 1 had some time left so coded approach 3 also The average time complexity of Quickselect is O(n), making it very efficient for its purpose. However, in"See full answer

    Software Engineer
    Data Structures & Algorithms
    +2 more
  • Discord logoAsked at Discord 
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    Software Engineer
    Behavioral
    +4 more
Showing 221-240 of 650