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Instead of moving from the startValue
to target
, consider reversing the operations. Start from the target
and attempt to reach the startValue
. If the target
is even, divide it by 2. If it is odd, add 1 to it. Continue until the target
is less than or equal to the startValue
. This allows you to efficiently compute the minimum steps by potentially making large reductions through division by 2.
Time Complexity: O(log n)
, where n
is the target due to halving operation.
Space Complexity: O(1)
as no extra space is used.
1function brokenCalc(startValue, target) {
2 let operations = 0;
3 while (target > startValue) {
4 operations++;
5 if (target % 2 === 1) {
6 target++;
7 } else {
8 target /= 2;
9 }
10 }
11 return operations + (startValue - target);
12}
13
14const startValue = 3;
15const target = 10;
16console.log(brokenCalc(startValue, target));
This JavaScript code similarly uses reverse operations, efficiently minimizing the target with each step until it's below or equal to the startValue.
Using a greedy approach, always attempt the operation that brings the target closer to the startValue significantly, which is multiplication by 2 in the reverse. Only when all doubling possibilities are exhausted, should we use subtraction/addition operations.
Time Complexity: O(log n)
due to division operations.
Space Complexity: O(1)
.
1def
The Python script applies the greedy method to decrementally converge upon the startValue, being efficient with division when possible.