Asked in: JPMORGAN
Image of the Question
All Testcases Passed ✔
Solution
def performoperations(arr, operations):
array = arr[: : ]
for i,j in operations:
while i<j:
// ... rest of solution available after purchaseExplanation
```
To solve this problem, the fundamental task is to apply a sequence of subarray reversal operations on an array. Each operation is defined by two indices indicating the start and end of the subarray to reverse. The goal is to process these operations in order and return the final state of the array.
Here is how to think about the problem step-by-step:
1. **Understanding the Core Operation - Subarray Reversal**
Each operation takes a contiguous segment of the array and reverses the order of its elements, while leaving the rest of the array untouched. This means the elements before the start index and after the end index remain the same, and only the elements within the given range get flipped.
2. **Effect of One Operation**
When you reverse a subarray from index `start` to `end`, you essentially swap the element at `start` with the element at `end`, then move inward, swapping elements until you reach the middle of that subarray. This is an in-place operation and affects only the portion of the array between the two indices.
3. **Performing Multiple Operations**
The operations are performed one after another in the order given. After completing each operation, the array changes. Subsequent operations are then applied to this updated array. Since operations can overlap and affect the same elements multiple times, the cumulative effect may not be intuitive without performing the steps sequentially.
4. **Implementation Strategy**
The straightforward approach is to iterate over each operation:
- For the current operation’s `start` and `end` indices, reverse the subarray in place.
- Move to the next operation and apply the same logic on the updated array.
This approach directly follows the problem description and is conceptually simple.
5. **Complexity Considerations**
- Each reversal operation takes O(k) time, where k is the length of the subarray being reversed.
- Since there can be up to `q` operations and the array length is `n`, in the worst case, you might reverse large portions multiple times.
- Given the constraints (`n, q ≤ 1000`), this approach is efficient enough and will run comfortably within limits.
6. **Examples to Solidify Understanding**
Using the provided example:
- Initial array: [9, 8, 7, 6, 5, 4, 3, 2, 1, 0]
- Operation 1: reverse from 0 to 9 → entire array reversed
- Operation 2: reverse from 4 to 5 → swap elements at 4 and 5
- Operation 3, 4, 5, 6: similarly reverse specified subarrays
Each operation modifies the array state, so tracking changes step-by-step clarifies the final output.
7. **Edge Cases and Validation**
- Subarray of length 1 (start == end) means no change; operation can be skipped or done trivially.
- Reversing the entire array multiple times toggles the array back and forth.
- Overlapping or nested operations cause multiple re-reversals in parts of the array.
- Make sure indices are within array bounds and handle accordingly.
8. **Alternative Thoughts (Optional)**
While a direct approach works well here, one might consider more complex data structures like segment trees or balanced trees to optimize for much larger constraints, especially if many reversal operations were involved. However, for this problem size, such complexity is unnecessary.
9. **Summary**
The problem boils down to performing a sequence of explicit subarray reversals on an array. Start from the initial array, apply each operation in order by reversing the specified subarray, then proceed to the next. After all operations, return the final array state. This direct simulation approach is clear, manageable, and efficient given the problem constraints.
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