Sorting Stability and When to Use Which Sort in DSA Javascript - Practice Problems & Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this stable sort on objects?

Consider the array of objects sorted by the 'value' key using a stable sort. What is the output after sorting?

DSA Javascript

const arr = [
  {id: 1, value: 3},
  {id: 2, value: 1},
  {id: 3, value: 3},
  {id: 4, value: 2}
];

const sorted = arr.slice().sort((a, b) => a.value - b.value);
console.log(sorted.map(o => o.id));

A [1, 3, 4, 2]

B [2, 4, 3, 1]

C [2, 4, 1, 3]

D [4, 2, 1, 3]

💡 Hint

Stable sort keeps the original order of equal elements.

The sort is stable, so elements with the same 'value' keep their original order. Both objects with value 3 (id 1 and 3) remain in the order they appeared.

🧠 Conceptual

intermediate

Which sorting algorithm is stable by default?

Among the following sorting algorithms, which one is stable by default?

A Quick Sort

B Merge Sort

C Heap Sort

D Selection Sort

💡 Hint

Think about which algorithm merges sorted sublists without changing order of equal elements.

Merge Sort is stable because it merges sorted sublists by comparing elements and preserving their order when equal.

❓ Predict Output

advanced

What error or output does this unstable sort produce?

Given this array of objects sorted by an unstable algorithm, what is the output of the ids after sorting by 'value'?

DSA Javascript

const arr = [
  {id: 'a', value: 5},
  {id: 'b', value: 3},
  {id: 'c', value: 5},
  {id: 'd', value: 3}
];

// Simulate unstable sort by swapping equal elements
function unstableSort(array) {
  array.sort((x, y) => x.value - y.value);
  // Swap equal elements to simulate instability
  for (let i = 0; i < array.length - 1; i++) {
    if (array[i].value === array[i + 1].value) {
      [array[i], array[i + 1]] = [array[i + 1], array[i]];
      i++;
    }
  }
  return array;
}

const sorted = unstableSort(arr);
console.log(sorted.map(o => o.id));

A ['d', 'b', 'c', 'a']

B ['b', 'd', 'a', 'c']

C ['b', 'd', 'c', 'a']

D ['a', 'c', 'b', 'd']

💡 Hint

The unstable sort swaps equal elements, changing their original order.

The unstable sort swaps adjacent equal elements, so the original order of equal 'value' elements is reversed in pairs.

🚀 Application

advanced

When should you prefer a stable sort over an unstable sort?

Choose the best scenario where using a stable sort is important.

A Sorting a list of employees first by department, then by joining date

B Sorting numbers where duplicates do not matter

C Sorting a list of unique IDs in any order

D Sorting a small array where speed is the only concern

💡 Hint

Stable sort preserves order of equal keys, useful for multi-level sorting.

When sorting by multiple criteria, stable sort preserves the order of previous sorts, important for sorting employees by department then joining date.

🧠 Conceptual

expert

Which sorting algorithm is NOT stable and why?

Among the following, which sorting algorithm is NOT stable and what is the main reason?

A Merge Sort - because it merges sorted sublists

B Bubble Sort - because it compares and swaps adjacent elements

C Insertion Sort - because it swaps adjacent elements only

D Heap Sort - because it rearranges elements using a heap structure

💡 Hint

Think about which algorithm changes relative order by moving elements far apart.

Heap Sort is not stable because it builds a heap and swaps elements that can be far apart, changing the relative order of equal elements.

Practice

1. What does it mean when a sorting algorithm is stable?

easy

A. It keeps the original order of equal elements after sorting

B. It sorts elements faster than unstable algorithms

C. It uses less memory than unstable algorithms

D. It always sorts in ascending order

Solution

1. Step 1: Understand stability in sorting

   A stable sort keeps the relative order of items with equal keys unchanged.

2. Step 2: Compare with other options

   Speed, memory use, or sorting order do not define stability.

3. Final Answer:

   It keeps the original order of equal elements after sorting -> Option A

4. Quick Check:

   Stable sort = keeps equal elements order [OK]

Hint: Stable means equal items keep their original order [OK]

Common Mistakes:

• Confusing stability with speed
• Thinking stability means sorting ascending only
• Assuming stable sorts use less memory

2. Which of the following is the correct way to call JavaScript's built-in sort method to sort numbers in ascending order?

easy

A. arr.sort()

B. arr.sort((a, b) => a + b)

C. arr.sort((a, b) => b - a)

D. arr.sort((a, b) => a - b)

Solution

1. Step 1: Understand JavaScript's default sort

   By default, arr.sort() sorts elements as strings, not numbers.

2. Step 2: Use compare function for numeric ascending

   The compare function (a, b) => a - b sorts numbers ascending correctly.

3. Final Answer:

   arr.sort((a, b) => a - b) -> Option D

4. Quick Check:

   Numeric ascending sort uses (a, b) => a - b [OK]

Hint: Use (a, b) => a - b for ascending numeric sort [OK]

Common Mistakes:

• Using arr.sort() alone for numbers
• Using (a, b) => b - a for ascending order
• Using (a, b) => a + b which is invalid

3. Consider the array of objects:

const items = [
  {name: 'apple', price: 50},
  {name: 'banana', price: 20},
  {name: 'cherry', price: 50},
  {name: 'date', price: 20}
];
items.sort((a, b) => a.price - b.price);

What will be the order of items after sorting?

medium

A. [{banana,20}, {date,20}, {cherry,50}, {apple,50}]

B. [{date,20}, {banana,20}, {cherry,50}, {apple,50}]

C. [{banana,20}, {date,20}, {apple,50}, {cherry,50}]

D. [{date,20}, {banana,20}, {apple,50}, {cherry,50}]

Solution

1. Step 1: Understand the sort comparator

   The comparator sorts by price ascending: 20 then 50.

2. Step 2: Check stability of JavaScript sort

   JavaScript's sort is stable in modern engines, so equal price items keep original order.

3. Step 3: Apply stability to equal price items

   For price 20, original order is banana then date; for 50, apple then cherry.

4. Final Answer:

   [{banana,20}, {date,20}, {apple,50}, {cherry,50}] -> Option C

5. Quick Check:

   Stable sort keeps equal price order [OK]

Hint: Stable sort keeps original order of equal keys [OK]

Common Mistakes:

• Assuming unstable sort changes order of equal items
• Mixing up banana and date order
• Ignoring stability of JavaScript sort

4. The following code tries to sort an array of strings by length, which may not keep the original order of equal length strings:

const arr = ['bat', 'cat', 'apple', 'dog'];
arr.sort((a, b) => a.length - b.length);

What is the main reason the original order of equal length strings might not be preserved?

medium

A. Strings cannot be sorted by length

B. JavaScript's sort is unstable in some engines

C. The comparator function is incorrect

D. The array contains duplicates

Solution

1. Step 1: Check comparator correctness

   The comparator (a, b) => a.length - b.length correctly compares string lengths.

2. Step 2: Understand JavaScript sort stability

   JavaScript's sort is stable in modern engines but may be unstable in older engines, causing order change.

3. Final Answer:

   JavaScript's sort is unstable in some engines -> Option B

4. Quick Check:

   Unstable sort breaks equal element order [OK]

Hint: Old JS engines have unstable sort, losing order [OK]

Common Mistakes:

• Blaming comparator function
• Thinking strings can't be sorted by length
• Assuming duplicates cause instability

5. You have a list of student records with name and score. You want to sort by score ascending but keep the original order for students with the same score. Which sorting algorithm should you choose and why?

hard

A. MergeSort, because it is stable and sorts efficiently

B. QuickSort, because it is fast but unstable

C. HeapSort, because it uses less memory

D. BubbleSort, because it is simple and stable

Solution

1. Step 1: Identify need for stability

   We want to keep original order for equal scores, so stability is required.

2. Step 2: Choose algorithm with stability and efficiency

   MergeSort is stable and efficient (O(n log n)), suitable for this task.

3. Step 3: Compare other options

   QuickSort is fast but unstable; HeapSort is unstable; BubbleSort is stable but inefficient.

4. Final Answer:

   MergeSort, because it is stable and sorts efficiently -> Option A

5. Quick Check:

   Stable + efficient = MergeSort [OK]

Hint: Stable and efficient sort for equal keys: MergeSort [OK]

Common Mistakes:

• Choosing QuickSort ignoring instability
• Picking BubbleSort despite inefficiency
• Confusing HeapSort as stable