```python
def find_duplicates(nums):
duplicates = []
seen = set()
for num in nums:
if num in seen:
duplicates.append(num)
else:
seen.add(num)
return duplicates

print(find_duplicates([1, 2, 3, 4, 5, 6, 6, 7, 8, 9]))
```

Question

```python
def find_duplicates(nums):
    duplicates = []
    seen = set()
    for num in nums:
        if num in seen:
            duplicates.append(num)
        else:
            seen.add(num)
    return duplicates

print(find_duplicates([1, 2, 3, 4, 5, 6, 6, 7, 8, 9]))
```

Accepted Answer

### 1. Problem Analysis
The problem involves finding duplicates in a given list of numbers by iterating through the list and keeping track of numbers that have been seen before.

### 2. Data Structure Selection
For efficiently finding duplicates while iterating over the list, a **Hash Set** data structure is suitable. This allows constant time complexity for membership tests, improving the performance of duplicate detection.

### 3. Template Generation
#### Hash Set Data Structure Template
```pseudocode
hash_set <- empty set
duplicates <- empty list

for num in nums:
    if num is in hash_set:
        add num to duplicates
    else:
        add num to hash_set

return duplicates
```

### 4. Description and Documentation
- **Hash Set**: 
    - **Description**: A hash set is a data structure that stores a collection of unique elements where each element is hashed to a unique value. It provides constant time complexity for insertion, deletion, and membership tests.
    - **Rationale**: Hash sets are ideal for efficiently checking for duplicates in a collection of elements due to their constant-time complexity for membership tests.
- **Code Template Explanation**:
    - The template initializes an empty hash set to store seen numbers and an empty list for duplicates.
    - It then iterates through the input list, checking if each number is already in the hash set. If it is, the number is added to the duplicates list; otherwise, the number is added to the hash set.
    - Finally, the list of duplicates is returned.

By using a hash set, the implementation ensures efficient duplicate detection in linear time complexity while processing the list of numbers. The provided template can be easily adapted to different programming languages and environments, making it versatile for various data management scenarios.

Data Structure Designer | Python

Efficient Duplicate Detection Using Hash Set

Prompt

Answer

1. Problem Analysis

2. Data Structure Selection

3. Template Generation

Hash Set Data Structure Template

4. Description and Documentation

Description

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