Searching for a word in a dictionary, finding a contact in a sorted phone book, searching for a value in a sorted database index.

External sorting of large datasets that don't fit in memory, sorting large files, used in various sorting algorithms in databases.

Searching for an item in a small, unsorted list, finding a specific file in a directory.

Sorting a hand of playing cards, sorting small datasets, used as a subroutine in more complex sorting algorithms.

Although not very efficient, it can be used in scenarios where memory usage is a primary concern due to its in-place sorting nature.

File system traversal, parsing complex data structures (like XML or JSON), implementing tree-based algorithms, and solving problems that can be broken down into smaller, self-similar subproblems.

Sorting is essential for indexing data, optimizing query performance, and presenting data in a structured manner.

Searching algorithms are used to efficiently locate specific records within a database, enabling quick retrieval of information.

Search engines use sorting algorithms to rank search results based on relevance, ensuring that the most relevant results appear at the top of the page.

Search engines use searching algorithms to quickly locate web pages that match a user's search query.

A search algorithm that finds the position of a target value within a sorted array by repeatedly dividing the search interval in half.

A divide-and-conquer sorting algorithm that divides the input array into smaller sub-arrays, recursively sorts them, and then merges the sorted sub-arrays.

A programming technique where a function calls itself in order to solve a problem.

The condition that stops a recursive function from calling itself infinitely.

A searching algorithm that sequentially checks each element of a list until a match is found or the entire list has been searched.

A sorting algorithm that builds the final sorted array one item at a time by repeatedly inserting the next element into its correct position within the already sorted portion of the array.

A sorting algorithm that repeatedly finds the minimum element from the unsorted portion of the array and places it at the beginning.

A resizable array implementation of the List interface in Java.

The position of an element within an array or ArrayList, starting from 0.

A contiguous portion of a list or array.

Linear Search: Works on unsorted lists, O(n) time complexity. Binary Search: Requires sorted lists, O(log n) time complexity.

Insertion Sort: Builds sorted array incrementally, adaptive. Selection Sort: Finds the minimum element in each iteration, not adaptive.

Insertion Sort: Simple, in-place, O(n^2) time complexity. Merge Sort: More complex, requires extra space, O(n log n) time complexity.

Selection Sort: Simple, in-place, O(n^2) time complexity. Merge Sort: More complex, requires extra space, O(n log n) time complexity.

Iterative: Uses loops, generally more efficient in terms of memory. Recursive: Uses function calls, can be more concise, but may lead to stack overflow.

Iterative: Uses loops, generally more efficient in terms of memory. Recursive: Uses function calls, can be more concise, but may lead to stack overflow.

Iterative: Uses loops, generally more efficient in terms of memory. Recursive: Uses function calls, can be more concise, but may lead to stack overflow.

Iterative: Uses loops, generally more efficient in terms of memory. Recursive: Uses function calls, can be more concise, but may lead to stack overflow.

Iterative: Uses loops, generally more efficient in terms of memory. Recursive: Uses function calls, can be more concise, but may lead to stack overflow.

Merge Sort is preferred for larger datasets due to its O(n log n) time complexity, while Insertion Sort is better for small datasets or nearly sorted data.