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Insertion Sort vs. Selection Sort: What's the Difference?

Edited by Aimie Carlson || By Janet White || Published on February 2, 2024
Insertion sort builds a sorted array one item at a time, while selection sort repeatedly finds the minimum element and moves it to the sorted portion.

Key Differences

Insertion sort works by dividing the array into a sorted and an unsorted region. It iteratively takes an element from the unsorted part and inserts it into its correct position in the sorted part. On the other hand, selection sort divides the array similarly but works by repeatedly finding the smallest (or largest) element from the unsorted portion and moving it to the end of the sorted portion. Each iteration selects an item and puts it in its final position.
In insertion sort, the sorted section grows one element at a time, and elements are moved only within this section to accommodate the new element. This process is akin to the way one might sort a hand of playing cards. Conversely, selection sort does not guarantee that the sorted section remains sorted after each iteration, as it always looks for the smallest element in the unsorted section regardless of the current order.
Insertion sort is adaptive; it can perform well on a partially sorted array, often requiring fewer steps. It is efficient for small datasets and can be more efficient than selection sort in certain scenarios. However, selection sort performs the same number of comparisons regardless of the initial order of the elements. It's not adaptive and has a consistent performance, but it generally performs less efficiently than insertion sort.
The complexity of insertion sort in the worst case is O(n^2), where n is the number of elements. However, its average and best-case performance is better, especially for partially sorted arrays. Selection sort also has a complexity of O(n^2) for all cases, as it always performs n(n-1)/2 comparisons and n swaps in total, making it generally slower and less efficient than insertion sort for larger arrays.
Insertion sort is more efficient and faster for smaller lists, where the overhead of more complex algorithms doesn’t justify their use. It also works well for data sets that are already mostly sorted. Selection sort, while simple and easy to understand, does not have these adaptive characteristics, making it less suitable for large datasets or ones that are already partially sorted.

Comparison Chart

Sorting Method

Inserts each element in its proper place
Selects the minimum and swaps it with the first unsorted element

Performance on Small Data

Efficient for small or partially sorted arrays
Less efficient than insertion sort


O(n^2) in the worst case, but can be faster for partially sorted data
Consistently O(n^2) regardless of initial order


Adaptive, performance varies based on initial order
Non-adaptive, consistent performance

Main Advantage

Faster for small or nearly sorted data
Simplicity and ease of implementation

Swapping Operations

Fewer swaps as it only rearranges within the sorted part
Swaps every time it finds the minimum element

Insertion Sort and Selection Sort Definitions

Insertion Sort

Involves fewer movements, making it efficient for smaller or nearly sorted data.
Insertion sort was the ideal choice due to the minimal rearrangements needed.

Selection Sort

A sorting algorithm that selects the smallest (or largest) element and moves it to the sorted section.
Selection sort methodically found and placed the smallest element at the beginning.

Insertion Sort

Efficient for small datasets and simple to implement.
For our small contact list, we used insertion sort for its efficiency.

Selection Sort

Divides the array into two parts: sorted and unsorted, working by swapping elements.
In each iteration, selection sort added the next smallest number to the sorted part.

Insertion Sort

A sorting algorithm that builds the final sorted array one item at a time.
Insertion sort efficiently organized the nearly sorted list of student names.

Selection Sort

Performs a fixed number of comparisons, with complexity always being O(n^2).
Selection sort was less efficient for the large dataset due to its quadratic complexity.

Insertion Sort

Works by dividing the array into sorted and unsorted parts.
Using insertion sort, each number was placed in its correct position iteratively.

Selection Sort

Non-adaptive, with consistent performance regardless of the initial array order.
Selection sort consistently performed with the same efficiency, irrespective of the data’s initial order.

Insertion Sort

Adapts to the existing order of elements, performing well on partially sorted arrays.
Insertion sort quickly handled the partially ordered dataset.

Selection Sort

Simple and easy to implement, but less efficient for larger lists.
We used selection sort for its simplicity in our basic programming tutorial.


What is insertion sort?

A sorting algorithm that builds the sorted array one element at a time.

What is selection sort?

A sorting method that repeatedly finds the minimum element and adds it to the sorted portion.

Can selection sort be more efficient for large datasets?

No, it's generally less efficient for larger datasets compared to more advanced algorithms.

How does insertion sort differ from selection sort in performance?

Insertion sort is generally faster for small or partially sorted data, while selection sort has consistent performance regardless of data order.

How does selection sort handle unsorted data?

It consistently performs the same number of comparisons regardless of the data's initial state.

Is insertion sort easy to implement?

Yes, it's straightforward and efficient for small datasets.

Can insertion sort be used in real-time applications?

Yes, especially where data is continuously added and needs to be sorted.

Is insertion sort adaptive?

Yes, its performance varies based on the initial order of data.

What is the time complexity of insertion sort?

Its worst-case complexity is O(n^2), but it can be faster for partially sorted data.

How many swaps does insertion sort make?

It makes fewer swaps, as it only rearranges within the sorted section.

How does insertion sort compare to more complex algorithms?

It's simpler and more efficient for small datasets, but less so for larger ones.

What are the disadvantages of insertion sort?

It becomes inefficient as the size of the dataset increases.

Does selection sort require more memory?

No, it sorts in place and does not require additional memory.

What type of data is selection sort not good for?

It's not ideal for large or complex datasets due to its quadratic complexity.

Is selection sort stable?

No, it's not stable as it may change the relative order of equal elements.

Does selection sort work well with duplicate elements?

Yes, it can sort arrays with duplicates, but it's not stable.

Can selection sort be optimized for better performance?

Basic optimizations can be made, but it generally remains O(n^2) in complexity.

Which sort is better for nearly sorted data?

Insertion sort is typically better for nearly sorted data.

Are there any variants of insertion sort?

Yes, variants like binary insertion sort improve the basic algorithm.

Is selection sort suitable for educational purposes?

Yes, due to its simplicity, it's often used for teaching sorting algorithms.
About Author
Written by
Janet White
Janet White has been an esteemed writer and blogger for Difference Wiki. Holding a Master's degree in Science and Medical Journalism from the prestigious Boston University, she has consistently demonstrated her expertise and passion for her field. When she's not immersed in her work, Janet relishes her time exercising, delving into a good book, and cherishing moments with friends and family.
Edited by
Aimie Carlson
Aimie Carlson, holding a master's degree in English literature, is a fervent English language enthusiast. She lends her writing talents to Difference Wiki, a prominent website that specializes in comparisons, offering readers insightful analyses that both captivate and inform.

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