Common Array Patterns
The topic discusses three common array patterns: two pointers, sliding window, and prefix sums, which optimize problem-solving in arrays due to their contiguous memory allocation and constant time index access. The two pointers technique is effective for sorted arrays and conditions involving pairs, while the sliding window maintains a contiguous subarray to efficiently compute sums. Prefix sums allow for quick range-sum queries by precomputing totals. Recognizing the appropriate pattern quickly is crucial in coding interviews, with specific signals indicating which technique to apply based on the problem's constraints.
We'll cover the following...
You're already familiar with two pointers, sliding windows, and prefix sums as individual techniques. This lesson dives deeper into why these patterns solve certain problems optimally and how to spot which pattern a problem uses.
All three patterns leverage a fundamental property of arrays: contiguous memory allocation and
Interview lens: The most valuable skill in an array interview is recognizing which one to reach for within the first minute of reading the problem.
Two pointers
The two pointers pattern places one pointer at each end of the array and moves them toward each other based on some condition. It works on sorted arrays and trades the O(n) cost of a nested loop for a single
The problem we will use to anchor this is: given a sorted array, remove duplicates in place and return the new length. One pointer scans forward, and the other marks the boundary of unique elements. When the scanner finds a new unique value, the boundary pointer advances, and the value is written there.
Time and space complexity
Time
: Single pass through the array. Space
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