title: Sorting and searching cheatsheet for coding interviews
description: Sorting and searching study guide for coding interviews, including practice questions, techniques, time complexity, and recommended resources
Sorting is the act of rearranging elements in a sequence in order, either in numerical or lexicographical order, and either ascending or descending.
A number of basic algorithms run in O(n<sup>2</sup>) and should not be used in interviews. In algorithm interviews, you're unlikely to need to implement any of the sorting algorithms from scratch. Instead you would need to sort the input using your language's default sorting function so that you can use binary searches on them.
On a sorted array of elements, by leveraging on its sorted property, searching can be done on them in faster than O(n) time by using a binary search. Binary search compares the target value with the middle element of the array, which informs the algorithm whether the target value lies in the left half or the right half, and this comparison proceeds on the remaining half until the target is found or the remaining half is empty.
While you're unlikely to be asked to implement a sorting algorithm from scratch during an interview, it is good to know the various time complexities of the different sorting algorithms.
- Readings
- [Sorting Out The Basics Behind Sorting Algorithms](https://medium.com/basecs/sorting-out-the-basics-behind-sorting-algorithms-b0a032873add), basecs
- [Heapsort](https://youtu.be/ryRfapIQHW0) ([slides](https://samuelalbanie.com/files/digest-slides/2022-12-brief-guide-to-heapsort-and-binary-heaps.pdf)), Samuel Albanie, University of Cambridge
- [Quicksort](https://youtu.be/kbiKn1K08RM) ([slides](https://samuelalbanie.com/files/digest-slides/2023-01-brief-guide-to-quicksort.pdf)), Samuel Albanie, University of Cambridge
- [Lower bounds for comparison sorts](https://www.youtube.com/watch?v=JWSiXs9aB5U) ([slides](https://samuelalbanie.com/files/digest-slides/2023-01-brief-guide-to-comparison-sorting-lower-bounds.pdf)), Samuel Albanie, University of Cambridge
- [Counting sort](https://www.youtube.com/watch?v=0aMcZpAySjw) ([slides](https://samuelalbanie.com/files/digest-slides/2023-01-brief-guide-to-counting-sort.pdf)), Samuel Albanie, University of Cambridge
- [Radix sort](https://www.youtube.com/watch?v=HzPbzQi9404) ([slides](https://samuelalbanie.com/files/digest-slides/2023-01-brief-guide-to-radix-sort.pdf)), Samuel Albanie, University of Cambridge
- [Bucket sort](https://www.youtube.com/watch?v=mz2fBJyoEVc) ([slides](https://samuelalbanie.com/files/digest-slides/2023-01-brief-guide-to-bucket-sort.pdf)), Samuel Albanie, University of Cambridge
Make sure you know the time and space complexity of the language's default sorting algorithm! The time complexity is almost definitely O(nlog(n))). Bonus points if you can name the sort. In Python, it's [Timsort](https://en.wikipedia.org/wiki/Timsort). In Java, [an implementation of Timsort](https://github.com/openjdk/jdk/blob/d9052b946682d1c0f2629455d73fe4e6b95b29db/src/java.base/share/classes/java/util/TimSort.java) is used for sorting objects, and [Dual-Pivot Quicksort](https://github.com/openjdk/jdk/blob/d9052b946682d1c0f2629455d73fe4e6b95b29db/src/java.base/share/classes/java/util/DualPivotQuicksort.java) is used for sorting primitives.
When a given sequence is in a sorted order (be it ascending or descending), using binary search should be one of the first things that come to your mind.
[Counting sort](https://en.wikipedia.org/wiki/Counting_sort) is a non-comparison-based sort you can use on numbers where you know the range of values beforehand. Examples: [H-Index](https://leetcode.com/problems/h-index/)
