In Matters Computational I found this interesting linear search implementation (it’s actually my Java implementation ;-)):
public static int linearSearch(int[] a, int key) {
int high = a.length - 1;
int tmp = a[high];
// put a sentinel at the end of the array
a[high] = key;
int i = 0;
while (a[i] != key) {
i++;
}
// restore original value
a[high] = tmp;
if (i == high && key != tmp) {
return NOT_CONTAINED;
}
return i;
}
It basically uses a sentinel, which is the searched for value, so that you always find the value and don’t have to check for array boundaries. The last element is stored in a temp variable, and then the sentinel is placed at the last position. When the value is found (remember, it is always found due to the sentinel), the original element is restored and the index is checked if it represents the last index and is unequal to the searched for value. If that’s the case, -1 (NOT_CONTAINED) is returned, otherwise the index.
While I found this implementation really clever, I wonder if it is actually useful. For small arrays, it seems to be always slower, and for large arrays it only seems to be faster when the value is not found. Any ideas?
EDIT
The original implementation was written in C++, so that could make a difference.
It’s not thread-safe, for example, you can lose your
a[high]value through having a second thread start after the first has changeda[high]tokey, so will recordkeytotmp, and finish after the first thread has restoreda[high]to its original value. The second thread will restorea[high]to what it first saw, which was the first thread’skey.It’s also not useful in java, since the JVM will include bounds checks on your array, so your while loop is checking that you’re not going past the end of your array anyway.