Lets say I have range of integers [l, r) and a function check(int idx)
which satisfies the following condition:
there is an index t (l <= t < r) such that for each i (l <= i <= t) check(i) == true
and for each j (t < j < r) check(j) == false
. Is there a standard way to find index t?
Standard binary_search()
needs comparator that takes two arguments, so it can't be applied here (correct me if I'm wrong).

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first of all, `std::binary_search` does not do what you need. It just checks whether a range contains the element - it does not return the index. https://stackoverflow.com/questions/446296/where-can-i-get-a-useful-c-binary-search-algorithm – Sergey Kolesnik Dec 13 '21 at 08:34
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`t` is known, so even if `check` only takes one argument, you have 2 indexes to compare. – super Dec 13 '21 at 08:36
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7[`std::partition_point`](https://en.cppreference.com/w/cpp/algorithm/partition_point)? – Jarod42 Dec 13 '21 at 08:41
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Along with using `std::distance` after getting the partition point. That will find you the index. So given your description, the solution is a one or two line function. – PaulMcKenzie Dec 13 '21 at 08:44
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I’m not sure if std::partition works on a range of integers – vdavid Dec 13 '21 at 09:25
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Can we assume that the range is *already* partitioned or that's something the function needs to check too? – Bob__ Dec 13 '21 at 09:30
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@Bob__ yes, we can assume that. – ArthurBesse Dec 13 '21 at 11:05
1 Answers
Assuming you are searching for a continuous range of integers (and not, for example, an indexed array) I would suggest a dichotomic search:
int find_t(int l, int r) {
// Preconditions
assert(check(l) == true);
//assert(check(r) == false); // this precondition is not mandatory
int max_idx_true = l; // highest known integer which satisfies check(idx) == true
int min_idx_false = r; // lowest known integer which satisfies check(idx) == false
while (max_idx_true+1 < min_idx_false) {
int mid_idx = (max_idx_true+min_idx_false)/2;
if (check(mid_idx)) max_idx_true = mid_idx;
else min_idx_false = mid_idx;
}
int t = max_idx_true;
// Postconditions
assert(check(t) == true);
assert(t+1 == r || check(t+1) == false);
return t;
}
This algorithm narrows the closest integers where check(idx) is true and the next one is false. In your case, you are looking for t which corresponds to max_idx_true
.
It should be noted that the following preconditions must be satisfied for this to work:
l
<r
check(l)
is true- for any
idx
, ifcheck(idx)
is true thencheck(idx-1)
is always true - for any
idx
, ifcheck(idx)
is false thencheck(idx+1)
is always false
Below is a source code example for testing the algorithm and output lines to better understand how it works. You can also try it out here.
#include <iostream>
#include <cassert>
using namespace std;
// Replace this function by your own check
bool check(int idx) {
return idx <= 42;
}
int find_t(int l, int r) {
assert(check(l) == true);
//assert(check(r) == false); // this precondition is not mandatory
int max_idx_true = l; // highest known integer which satisfies check(idx) == true
int min_idx_false = r; // lowest known integer which satisfies check(idx) == false
int n = 0; // Number of iterations, not needed but helps analyzing the complexity
while (max_idx_true+1 < min_idx_false) {
++n;
int mid_idx = (max_idx_true+min_idx_false)/2;
// Analyze the algorithm in detail
cerr << "Iteration #" << n;
cerr << " in range [" << max_idx_true << ", " << min_idx_false << ")";
cerr << " the midpoint " << mid_idx << " is " << boolalpha << check(mid_idx) << noboolalpha;
cerr << endl;
if (check(mid_idx)) max_idx_true = mid_idx;
else min_idx_false = mid_idx;
}
int t = max_idx_true;
assert(check(t) == true);
assert(t+1 == r || check(t+1) == false);
return t;
}
int main() {
// Initial constants
int l = 0;
int r = 100;
int t = find_t(l, r);
cout << "The answer is " << t << endl;
return 0;
}
The main advantage of the dichomotic search is that it finds your candidate with a complexity of only O(log2(N)).
For example if you initialize int l = -2000000000
and int r = 2000000000
(+/- 2 billions) you need to known the answer in about 4 billion numbers, yet the number of iterations will be 32 at worst.

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