1582 articles
LC 74 asks you to search a globally sorted 2D matrix in O(log(m*n)). The key insight: treat the entire matrix as a 1D sorted array using flat-index mapping (row = mid // n, col = mid % n) and run standard binary search.
Find the minimum eating speed that lets Koko finish all bananas in h hours by binary searching over the answer space and using a feasibility check. The canonical binary-search-on-answer problem.
LC 1011 asks for the minimum ship capacity to deliver all packages within D days. Binary search on the capacity range [max(weights), sum(weights)] and greedily simulate loading to check feasibility. A classic binary-search-on-answer pattern.
Find any peak element in O(log n) by always moving toward the uphill neighbor. Understand the slope-chasing invariant that guarantees a peak exists in every search window.
Find the k closest elements to x in a sorted array in O(log(n-k) + k) by binary searching for the optimal left boundary of the result window rather than searching for x itself.