DSA interview questions and answers

Build prefix products to the left of i and suffix products to the right of i, then multiply those two for each index.

Kadane's algorithm keeps a running sum, resetting it to the current value when the running sum goes negative, and tracks the global max.

Sort intervals by start time, then scan and either extend the last merged interval when the next start is at most the current end, or push a new interval.

Find the rightmost ascent, swap it with the smallest larger successor on its right, then reverse the suffix to make it the next smallest order.

Treat values as indices: negate nums[abs(x)-1] on first visit and record x when you see a negative already.

Take the first string as a candidate and shrink it whenever a later string mismatches at some index.

Skip leading spaces, read an optional sign, then accumulate digits while checking overflow against INT_MAX/MIN before multiplying by 10.

Naive sliding comparison is O((n-m+1)*m).

Expand around each center (and each pair of centers for even length), tracking the longest window.

For each word, sort its characters or count letters as a hash key and append the word to a map of lists.

Keep a prefix-sum frequency map starting with 0:1.

Put all numbers in a set, then only start a streak from values that have no predecessor x-1, and walk x+1, x+2, ...

Hash all sums of A[i]+B[j], then for each C[k]+D[l] add the count of the negated sum.

Same as Two Sum: one pass with value-to-index map, looking up target-x before inserting x so you never reuse the same index.

Sort, then for each index i run two pointers on the right side looking for -nums[i], skipping duplicates at all three positions.

Start at both ends and move the pointer at the shorter line inward, because width shrinks so you must try a taller side.

Walk t with a pointer into s

Squares of a sorted array are largest at the ends.

Grow a right pointer and store last-seen indices in a map

Expand right to grow the sum, then shrink left while the sum stays at least target, tracking the shortest window.