LeetCode Problem Workspace
Array Reduce Transformation
Implement the Array Reduce Transformation pattern by applying a reducer function on an array with a given initial value.
0
Topics
1
Code langs
0
Related
Practice Focus
Easy · Array Reduce Transformation core interview pattern
Answer-first summary
Implement the Array Reduce Transformation pattern by applying a reducer function on an array with a given initial value.
Ace coding interviews with Interview AiBoxInterview AiBox guidance for Array Reduce Transformation core interview pattern
In this problem, you're tasked with reducing an array using a custom reducer function. The function is applied sequentially, and the initial value is used to start the reduction. The solution emphasizes understanding the pattern of sequential reduction and its trade-offs.
Problem Statement
You are given an integer array nums, a reducer function fn, and an initial value init. The goal is to return the final result obtained by applying fn to each element of the array, sequentially. Each time the reducer function is applied, the result of the previous application is passed as an argument to the next call, along with the current element of the array.
The operations proceed as follows: first, val = fn(init, nums[0]); then, val = fn(val, nums[1]); and so on until every element in nums has been processed. The final value of val after the entire array has been traversed is returned. If nums is empty, return init.
Examples
Example 1
Input: nums = [1,2,3,4] fn = function sum(accum, curr) { return accum + curr; } init = 0
Output: 10
initially, the value is init=0. (0) + nums[0] = 1 (1) + nums[1] = 3 (3) + nums[2] = 6 (6) + nums[3] = 10 The final answer is 10.
Example 2
Input: nums = [1,2,3,4] fn = function sum(accum, curr) { return accum + curr * curr; } init = 100
Output: 130
initially, the value is init=100. (100) + nums[0] * nums[0] = 101 (101) + nums[1] * nums[1] = 105 (105) + nums[2] * nums[2] = 114 (114) + nums[3] * nums[3] = 130 The final answer is 130.
Example 3
Input: nums = [] fn = function sum(accum, curr) { return 0; } init = 25
Output: 25
For empty arrays, the answer is always init.
Constraints
- 0 <= nums.length <= 1000
- 0 <= nums[i] <= 1000
- 0 <= init <= 1000
Solution Approach
Initial Setup
Start by initializing a variable, say res, to the given initial value. This variable will hold the intermediate results during the reduction process.
Sequential Reduction
Apply the reducer function fn to res and each element of nums one by one. After processing each element, res will store the updated result which will be used in the next iteration.
Handle Edge Cases
Ensure that if nums is empty, the function directly returns the initial value init. This edge case must be handled early in the implementation to avoid unnecessary computation.
Complexity Analysis
| Metric | Value |
|---|---|
| Time | Depends on the final approach |
| Space | Depends on the final approach |
The time complexity is O(n) where n is the length of the input array nums, as we iterate through each element once. The space complexity is O(1) as we only need a single variable for the accumulation process, regardless of the array size.
What Interviewers Usually Probe
- Look for understanding of sequential operations and the effect of passing intermediate results to the reducer function.
- Test if the candidate accounts for edge cases like empty arrays properly.
- Observe if the candidate can explain the time and space complexities effectively.
Common Pitfalls or Variants
Common pitfalls
- Forgetting to handle empty arrays and returning the correct initial value.
- Not correctly passing the updated value from one iteration to the next.
- Misunderstanding the reducer function’s behavior and applying it incorrectly to elements.
Follow-up variants
- Introduce variations where the reducer function performs operations like subtraction or multiplication instead of addition.
- Test cases with arrays containing negative numbers to ensure correctness in all cases.
- Consider reducing objects or more complex data types instead of just numbers.
FAQ
How do I solve the Array Reduce Transformation problem?
Start by initializing a result variable with the initial value, then iteratively apply the reducer function to each element in the array.
What happens if the input array is empty?
If the array is empty, simply return the initial value, as no operations are performed on the array.
What is the time complexity of the Array Reduce Transformation?
The time complexity is O(n), where n is the length of the array, as each element is processed exactly once.
Can I use this pattern for other operations on arrays?
Yes, this reduce pattern can be adapted for various operations like summing, multiplying, or even more complex transformations on the array elements.
What is the correct approach to handle the initial value in this problem?
Initialize a result variable with the given initial value and apply the reducer function sequentially to each element of the array, passing the result forward each time.
Solution
Solution 1
#### TypeScript
type Fn = (accum: number, curr: number) => number;
function reduce(nums: number[], fn: Fn, init: number): number {
let acc: number = init;
for (const x of nums) {
acc = fn(acc, x);
}
return acc;
}