Sorting and Searching Algorithms Questions

Core computer science algorithms for ordering and locating data, including understanding, implementing, and applying common sorting algorithms and search techniques and analyzing their performance. Candidates should know comparison sorts such as merge sort, quick sort, heap sort, insertion sort, selection sort, and bubble sort and understand stability, in place versus out of place behavior, and best average and worst case time and space complexities. They should master binary search and linear search and variations and know when searching requires a different approach. Knowledge should include algorithmic patterns such as divide and conquer and two pointers, selection algorithms such as quickselect and nth element, and non comparison sorts such as counting sort, radix sort and bucket sort when appropriate. Candidates must be able to implement clean iterative or recursive versions, reason about recursion depth and stack usage, explain trade offs between using built in language sort utilities and custom implementations, and choose the right algorithm for a problem based on input size, memory constraints, and stability requirements. Interviewers often assess coding correctness, complexity analysis using big O notation, edge cases, comparator usage for custom ordering, and ability to justify algorithm choices.