This one tripped me up more than it should have.
Clarify input format and constraints, then propose a single-pass O(n) algorithm using a stack or running sum with a pending multiplication term. Walk through the algorithm with a small example, and discuss edge cases like leading/trailing operators and spaces.
Pro tip: Mention that you can avoid a stack by maintaining a running total and a current term for multiplication, which uses O(1) space and is more efficient. This shows you optimize beyond the basic stack solution.
Ask about input format (spaces, commas), whether the expression is always valid, and if negative numbers are possible. Confirm that O(n) time and O(1) space are desired.
Explain that you'll parse the string left to right, maintaining a running total and a current term for multiplication. When you see '+', add the current term to the total and reset; when you see '*', multiply the current term by the next number.
Trace the algorithm on a sample input like '3+2*2' to demonstrate how it respects precedence and yields the correct result (7).
Cover cases like multiple-digit numbers, spaces, and expressions starting with a number. State that time complexity is O(n) and space is O(1).
Implement the solution with clear variable names and handle parsing carefully. Test with a few cases if time permits.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Use binary search to find the first and last occurrence of the target, then return the difference plus one. This achieves O(log n) time by performing two modified binary searches. Alternatively, find any occurrence and expand, but that could be O(n) in worst case, so the two-boundary approach is preferred.
Pro tip: Mention that you can optimize by searching for the target+0.5 and target-0.5 to find insertion points, but clarify that this only works for integers. Also, discuss edge cases like empty array or target not present.
Restate the problem to ensure understanding: sorted array, target value, return count, O(log n) requirement. Ask about duplicates, data types, and edge cases.
Explain that you'll use binary search to find the first and last index of the target. If not found, return 0. Otherwise, count = last - first + 1.
Write a helper function for binary search that finds the first occurrence (leftmost) and another for the last occurrence (rightmost). Adjust mid calculation and conditions to continue searching even after finding the target.
Check for empty array, target not present, all elements same. Analyze time complexity: O(log n) for each search, so O(log n) total. Space complexity O(1).
Walk through a few examples: target present multiple times, once, not at all. Verify the code logic and boundary conditions.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Clarify the problem constraints and edge cases, then design a linear scan that tracks consecutive missing numbers and formats runs of length >=3 as ranges. Implement and test with examples, ensuring O(n) time and O(1) extra space.
Pro tip: Mention that you can avoid extra space by scanning the sorted list and using the gap between consecutive present numbers to identify missing runs, and handle the boundaries (0 and 99) explicitly.
Ask about input format, whether the list is guaranteed sorted and unique, and how to handle empty lists or full ranges. Confirm the exact output format for runs and individual numbers.
Use a linear scan: iterate through the sorted list, and for each gap between consecutive present numbers (including before the first and after the last), collect the missing numbers. Format runs of length >=3 as 'a->b' and shorter runs as comma-separated values.
Initialize a pointer to 0. For each number in the list, if it's greater than the pointer, the missing numbers are from pointer to number-1. After the loop, handle missing numbers from pointer to 99. Use a helper to format a range of missing numbers.
Test with cases like empty list, full list, single missing number, run of exactly 3, run at the start or end, and multiple runs. Verify output matches expected format.
State that the solution is O(n) time and O(1) extra space (excluding output). Discuss potential variations, such as handling unsorted input or different ranges.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Classic sliding window and I knew the pattern going in, but I fumbled the condition for shrinking the window.
Use a sliding window with two pointers to expand and contract the window while maintaining character counts. Track the number of characters that have met their required frequency to know when the window is valid. When valid, shrink the window from the left to find the minimum length, updating the result accordingly.
Pro tip: Clarify edge cases upfront (e.g., empty strings, characters not in t) and discuss how you'd handle Unicode or large character sets. Mention that the algorithm runs in O(|s| + |t|) time and O(k) space, where k is the number of unique characters in t.
Restate the problem to ensure clarity: find the smallest substring of s containing all characters of t with exact frequencies. Discuss edge cases like empty s or t, or when t has characters not in s.
Use a hash map (or array for ASCII) to store the required frequency of each character in t. Use another hash map to store the frequency of characters in the current window.
Initialize left and right pointers at 0. Expand right to include characters, updating the window frequency and a counter for how many characters have met the required frequency. When all characters are satisfied, shrink the window from the left while maintaining validity, updating the minimum length and start index.
Keep track of the minimum window length and its starting index. After the loop, return the substring if found, otherwise return an empty string.
Explain that the time complexity is O(|s| + |t|) because each character is visited at most twice, and space is O(k) where k is the number of unique characters in t. Walk through a small example to verify correctness.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.