Sorting is a fundamental operation in computer science, and choosing the right sorting algorithm depends on the problem at hand, the size of the dataset, and performance constraints. In TypeScript, several sorting algorithms can be implemented, each with its strengths and weaknesses. Quicksort is a popular choice due to its average-case time complexity of O(n log n) and in-place sorting, meaning it doesn’t require extra memory. It works by selecting a pivot element and partitioning the array into two halves—elements less than the pivot and elements greater than the pivot—before recursively sorting both halves. Merge sort, another divide-and-conquer algorithm, guarantees O(n log n) time complexity, even in the worst case, but requires additional space for the auxiliary array used in merging. Heapsort, based on the heap data structure, also offers O(n log n) performance and is particularly efficient for sorting large datasets due to its minimal memory usage. For smaller datasets or when simplicity is prioritized, insertion sort or selection sort may be sufficient, but these algorithms have O(n²) time complexity. Understanding these algorithms and their trade-offs is key to optimizing performance in real-world applications, such as processing large arrays of data or preparing data for searching algorithms.