Use a depth-first traversal (pre-order) that visits the left child before the right child, collecting values only when a node has no children. This ensures leaf nodes are recorded in left-to-right order. Discuss iterative and recursive implementations, and analyze time and space complexity.
Pro tip: At Apple, interviewers value clean, efficient code and awareness of edge cases. Mention that an iterative solution avoids recursion depth limits for skewed trees, and always test with an empty tree, a single node, and a tree with only left or right children.
Confirm the definition of a leaf node (no children) and that the tree is not necessarily balanced. Ask about input size to discuss recursion limits.
Select a depth-first search (pre-order) that processes left before right. Explain why this yields left-to-right leaf order.
Write a recursive function that checks if a node is a leaf; if so, add its value to the result list. Otherwise, recurse on left then right. Optionally, present an iterative version using a stack.
State O(n) time and O(h) space for recursion (or O(n) for iterative stack). Discuss edge cases: empty tree, single node, skewed tree, and trees with varying depths.
Walk through a sample tree to verify the output order. Mention that you would write unit tests covering the edge cases.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the problem: we need the latest palindrome date strictly before the given date, where the palindrome is formed by the concatenated YYYYMMDD digits. The key insight is that any 8-digit palindrome is fully determined by its first 4 digits (the year), so we can iterate over candidate years, construct the corresponding palindrome date, and check validity with leap year rules. Then pick the largest valid palindrome date that is less than the input.
Pro tip: Mention that you can avoid iterating day-by-day by generating candidates from the year, and explicitly handle the edge case where the constructed palindrome date falls in the same year as the input but is not earlier—then decrement the year. Also note that dates before 1000 AD would have a 7-digit representation, but the problem likely assumes modern dates; clarify this assumption.
Confirm the input format, that the palindrome is over the 8-character YYYYMMDD string, and that we need the most recent date strictly earlier than the given date. Ask about date range (e.g., year >= 1000) to avoid 7-digit edge cases.
For a given year Y (4 digits), the palindrome date is formed by mirroring the year: YYYYMMDD where MMDD is the reverse of YYYY. So the month is the reverse of the last two digits of the year, and the day is the reverse of the first two digits.
Check if the month is between 1 and 12, and the day is valid for that month and year, including leap year rules (divisible by 4, except centuries unless divisible by 400).
Start from the year of the input date, construct the palindrome, and if it's valid and strictly earlier than the input, return it. Otherwise, decrement the year and repeat until a valid palindrome is found.
Discuss time complexity (O(1) since at most a few years back) and edge cases: input date itself is a palindrome (must return earlier), leap years, and dates near year boundaries.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the problem: confirm input/output types, edge cases (empty array, single element), and that the first output is always 0. Then propose a simple O(n) single-pass solution that compares each element with its predecessor, handling the first index separately. Finally, discuss potential optimizations or variations, such as in-place modification or bitwise operations.
Pro tip: Mention that this is a common building block in digital signal processing and hardware verification, and that Apple often values clean, efficient code with clear edge-case handling. Also, consider asking if the input can be modified in-place to save memory.
Ask about input size, data types, and whether the output should be a new array or can modify the input. Confirm edge cases: empty array, single element, and arrays with no rising edges.
Explain that you'll iterate through the array starting from index 1, comparing each element with the previous one. If previous is 0 and current is 1, set output to 1; otherwise 0. Set output[0] = 0.
Implement the solution in your preferred language, using clear variable names and handling edge cases. For example, in Python: output = [0]*len(samples); for i in range(1, len(samples)): output[i] = 1 if samples[i-1]==0 and samples[i]==1 else 0.
Walk through a few test cases: [0,1,0,1] -> [0,1,0,1]; [1,0,1] -> [0,0,1]; [0,0,0] -> [0,0,0]; empty array -> empty array. Verify correctness.
State that time complexity is O(n) and space is O(n) for the output. Mention that if in-place modification is allowed, space can be O(1) by updating the input array from the end or using a temporary variable.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Choose a well-known O(n log n) sorting algorithm like merge sort or quicksort, and implement it cleanly with clear variable names and comments. If you opt for a simpler O(n^2) algorithm like bubble sort, explicitly state its time complexity and explain why you chose it despite the inefficiency. Focus on correctness, edge cases, and discussing trade-offs.
Pro tip: At Apple, attention to detail and performance are paramount. After implementing, briefly analyze the algorithm's stability, in-place nature, and worst-case performance, and mention how you would test it with edge cases like empty arrays, duplicates, and already sorted data.
Confirm the input format (array of integers), expected output (sorted array), and any constraints like memory or stability. Ask if in-place sorting is required or if additional space is acceptable.
Choose an O(n log n) algorithm such as merge sort or quicksort. Briefly justify your choice based on trade-offs (e.g., merge sort for stability, quicksort for average-case speed).
Write clean, modular code with clear variable names and comments. Handle edge cases like empty arrays or single elements. If using bubble sort, explicitly state its O(n^2) complexity.
State the time and space complexity of your solution. Discuss stability, in-place vs. out-of-place, and worst-case scenarios (e.g., quicksort's O(n^2) worst case).
Walk through a small example and mention testing with edge cases: empty array, duplicates, negative numbers, already sorted, reverse sorted. Consider writing unit tests.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.