Off-by-one on range boundaries
Wrong move: Loop endpoints miss first/last candidate.
Usually fails on: Fails on minimal arrays and exact-boundary answers.
Fix: Re-derive loops from inclusive/exclusive ranges before coding.
Build confidence with an intuition-first walkthrough focused on core interview patterns fundamentals.
Table: Employees
+-------------+---------+ | Column Name | Type | +-------------+---------+ | employee_id | int | | name | varchar | +-------------+---------+ employee_id is the column with unique values for this table. Each row of this table indicates the name of the employee whose ID is employee_id.
Table: Salaries
+-------------+---------+ | Column Name | Type | +-------------+---------+ | employee_id | int | | salary | int | +-------------+---------+ employee_id is the column with unique values for this table. Each row of this table indicates the salary of the employee whose ID is employee_id.
Write a solution to report the IDs of all the employees with missing information. The information of an employee is missing if:
Return the result table ordered by employee_id in ascending order.
The result format is in the following example.
Example 1:
Input: Employees table: +-------------+----------+ | employee_id | name | +-------------+----------+ | 2 | Crew | | 4 | Haven | | 5 | Kristian | +-------------+----------+ Salaries table: +-------------+--------+ | employee_id | salary | +-------------+--------+ | 5 | 76071 | | 1 | 22517 | | 4 | 63539 | +-------------+--------+ Output: +-------------+ | employee_id | +-------------+ | 1 | | 2 | +-------------+ Explanation: Employees 1, 2, 4, and 5 are working at this company. The name of employee 1 is missing. The salary of employee 2 is missing.
Problem summary: Table: Employees +-------------+---------+ | Column Name | Type | +-------------+---------+ | employee_id | int | | name | varchar | +-------------+---------+ employee_id is the column with unique values for this table. Each row of this table indicates the name of the employee whose ID is employee_id. Table: Salaries +-------------+---------+ | Column Name | Type | +-------------+---------+ | employee_id | int | | salary | int | +-------------+---------+ employee_id is the column with unique values for this table. Each row of this table indicates the salary of the employee whose ID is employee_id. Write a solution to report the IDs of all the employees with missing information. The information of an employee is missing if: The employee's name is missing, or The employee's salary is missing. Return the result table ordered by employee_id in ascending order. The result format is in the
Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.
Pattern signal: General problem-solving
{"headers":{"Employees":["employee_id","name"],"Salaries":["employee_id","salary"]},"rows":{"Employees":[[2,"Crew"],[4,"Haven"],[5,"Kristian"]],"Salaries":[[5,76071],[1,22517],[4,63539]]}}Source-backed implementations are provided below for direct study and interview prep.
// Accepted solution for LeetCode #1965: Employees With Missing Information
// Auto-generated Java example from rust.
class Solution {
public void exampleSolution() {
}
}
// Reference (rust):
// // Accepted solution for LeetCode #1965: Employees With Missing Information
// pub fn sql_example() -> &'static str {
// r#"
// -- Accepted solution for LeetCode #1965: Employees With Missing Information
// # Write your MySQL query statement below
// SELECT employee_id
// FROM Employees
// WHERE employee_id NOT IN (SELECT employee_id FROM Salaries)
// UNION
// SELECT employee_id
// FROM Salaries
// WHERE employee_id NOT IN (SELECT employee_id FROM Employees)
// ORDER BY 1;
// "#
// }
// Accepted solution for LeetCode #1965: Employees With Missing Information
// Auto-generated Go example from rust.
func exampleSolution() {
}
// Reference (rust):
// // Accepted solution for LeetCode #1965: Employees With Missing Information
// pub fn sql_example() -> &'static str {
// r#"
// -- Accepted solution for LeetCode #1965: Employees With Missing Information
// # Write your MySQL query statement below
// SELECT employee_id
// FROM Employees
// WHERE employee_id NOT IN (SELECT employee_id FROM Salaries)
// UNION
// SELECT employee_id
// FROM Salaries
// WHERE employee_id NOT IN (SELECT employee_id FROM Employees)
// ORDER BY 1;
// "#
// }
# Accepted solution for LeetCode #1965: Employees With Missing Information
# Auto-generated Python example from rust.
def example_solution() -> None:
return
# Reference (rust):
# // Accepted solution for LeetCode #1965: Employees With Missing Information
# pub fn sql_example() -> &'static str {
# r#"
# -- Accepted solution for LeetCode #1965: Employees With Missing Information
# # Write your MySQL query statement below
# SELECT employee_id
# FROM Employees
# WHERE employee_id NOT IN (SELECT employee_id FROM Salaries)
# UNION
# SELECT employee_id
# FROM Salaries
# WHERE employee_id NOT IN (SELECT employee_id FROM Employees)
# ORDER BY 1;
# "#
# }
// Accepted solution for LeetCode #1965: Employees With Missing Information
pub fn sql_example() -> &'static str {
r#"
-- Accepted solution for LeetCode #1965: Employees With Missing Information
# Write your MySQL query statement below
SELECT employee_id
FROM Employees
WHERE employee_id NOT IN (SELECT employee_id FROM Salaries)
UNION
SELECT employee_id
FROM Salaries
WHERE employee_id NOT IN (SELECT employee_id FROM Employees)
ORDER BY 1;
"#
}
// Accepted solution for LeetCode #1965: Employees With Missing Information
// Auto-generated TypeScript example from rust.
function exampleSolution(): void {
}
// Reference (rust):
// // Accepted solution for LeetCode #1965: Employees With Missing Information
// pub fn sql_example() -> &'static str {
// r#"
// -- Accepted solution for LeetCode #1965: Employees With Missing Information
// # Write your MySQL query statement below
// SELECT employee_id
// FROM Employees
// WHERE employee_id NOT IN (SELECT employee_id FROM Salaries)
// UNION
// SELECT employee_id
// FROM Salaries
// WHERE employee_id NOT IN (SELECT employee_id FROM Employees)
// ORDER BY 1;
// "#
// }
Use this to step through a reusable interview workflow for this problem.
Two nested loops check every pair or subarray. The outer loop fixes a starting point, the inner loop extends or searches. For n elements this gives up to n²/2 operations. No extra space, but the quadratic time is prohibitive for large inputs.
Most array problems have an O(n²) brute force (nested loops) and an O(n) optimal (single pass with clever state tracking). The key is identifying what information to maintain as you scan: a running max, a prefix sum, a hash map of seen values, or two pointers.
Review these before coding to avoid predictable interview regressions.
Wrong move: Loop endpoints miss first/last candidate.
Usually fails on: Fails on minimal arrays and exact-boundary answers.
Fix: Re-derive loops from inclusive/exclusive ranges before coding.