Classic binary search, nothing to say really.
Recognize that the sorted array and O(log n) requirement point directly to binary search. Walk through the algorithm step-by-step, maintaining low and high pointers and narrowing the search space by comparing the middle element to the target. Emphasize edge cases and the importance of correct midpoint calculation to avoid overflow.
Pro tip: Mention using mid = low + (high - low) / 2 instead of (low + high) / 2 to prevent integer overflow, and discuss how you would handle duplicates if the problem required finding the first or last occurrence.
Confirm assumptions: array is sorted ascending, may contain duplicates, and return any valid index if duplicates exist. Ask about input size and constraints.
Explain that binary search achieves O(log n) by halving the search space each iteration, which is optimal for a sorted array.
Initialize low = 0, high = n-1. While low <= high, compute mid, compare arr[mid] with target, and adjust low or high accordingly. Return mid if found, else -1.
Discuss empty array, single element, target smaller than first or larger than last, and duplicates. Mention overflow-safe midpoint calculation.
State time complexity O(log n) and space complexity O(1). Optionally mention recursive vs iterative trade-offs.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
This one tripped me up more than I expected for something that sounds simple.
Combine a dynamic array (list) with a hash map that stores each element's index in the array. For insert, append to the array and record the index; for remove, swap the target element with the last element, update the moved element's index, then pop; for getRandom, pick a random index and return the element. This achieves average O(1) for all operations.
Pro tip: Mention that getRandom must be uniformly random and that the swap-with-last trick is key to O(1) removal. Also, clarify handling of duplicates if the data structure allows them.
Ask whether duplicates are allowed, whether remove is by value or by index, and whether getRandom should return each element with equal probability.
Select an array for O(1) random access and a hash map for O(1) lookup of element indices.
For insert, append to array and add to map. For remove, swap the target with the last element, update the map for the swapped element, then remove the last element from both array and map.
Generate a random index in the range of the array's size and return the element at that index.
Confirm average O(1) time for all operations and discuss edge cases like removing the last element, removing a non-existent element, and handling duplicates.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Spent too long on the base case before even thinking about the follow-up.
Start by clarifying the problem constraints and edge cases, then propose a two-stack (operands and operators) solution that respects operator precedence. For the follow-up, extend the same approach by treating parentheses as triggers to evaluate the current sub-expression, or switch to a recursive descent parser for clarity.
Pro tip: Mention that you can avoid the two-stack approach by using a single stack and evaluating on the fly, but emphasize that the two-stack method is more readable and easier to extend for parentheses. Also, proactively discuss handling division by zero and integer division truncation.
Ask about input format, operator precedence, integer division behavior, and whether parentheses are balanced. Confirm that the expression is valid and contains only non-negative integers.
Decide between two-stack (operators and operands) or recursive descent. For the base problem, two-stack is straightforward; for parentheses, recursive descent or a stack-based shunting-yard algorithm works well.
Use a precedence map (e.g., +,-: 1; *,/: 2) and a helper to apply the top operator to the top two operands. When encountering an operator, pop and apply while the stack top has higher or equal precedence.
Treat '(' as a push and ')' as a trigger to evaluate until the matching '('. Alternatively, use recursion: when encountering '(', recursively evaluate the sub-expression inside.
Walk through examples like '3+2*2', '(1+(4+5+2)-3)+(6+8)'. Mention O(n) time and O(n) space, and note that the solution handles nested parentheses.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.