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Assuming compilers are clever enough (part 1)
Developers often assume the compiler they use will do all sorts of fancy stuff for them. Is this because they are lazy and happy to push responsibility for parts of the code they write on to the compiler, or do they actually believe that their compiler does all the clever stuff they assume?
An example of unmet assumptions about compiler performance is the use of const in C/C++, final in Java or readonly in other languages. These are often viewed as a checking mechanism, i.e., the developer wants the compiler to check that no attempt is made to, accidentally, change the value of some variable, perhaps via code added during maintenance.
The surprising thing about variables in source code is that approximately 50% of them don’t change once they have been assigned a value (A Theory of Type Qualifiers for C measurements and Automatic Inference of Stationary Fields for Java).
Developers don’t use const/final qualifiers nearly as often as they could. Most modern compilers can deduce if a locally defined variable is only assigned a value once and make use of this fact during optimization. It takes a lot more resources to deduce this information for non-local variables; developers want their compiler to be fast and so implementors don’t won’t them waiting around while whole program analysis is performed.
Why don’t developers make more use of const/final qualifiers? Is this usage, or lack of, an indicator that developers don’t have an accurate grasp of variable usage, or that they don’t see the benefit of using these qualifiers or perhaps they pass responsibility on to the compiler (program size seems to grow sufficiently fast that whole program optimization often consumes more memory than likely to be available; and when are motherboards going to break out of the 4G limit?)
Average distance between two fields
If I randomly pick two fields from an aggregate type definition containing N fields what will be the average distance between them (adjacent fields have distance 1, if separated by one field they have distance 2, separated by two fields they have distance 3 and so on)?
For example, a struct containing five fields has four field pairs having distance 1 from each other, three distance 2, two distance 2, and one field pair having distance 4; the average is 2.
The surprising answer, to me at least, is (N+1)/3.
Proof: The average distance can be obtained by summing the distances between all possible field pairs and dividing this value by the number of possible different pairs.
Distance 1 2 3 4 5 6
Number of fields
4 3 2 1
5 4 3 2 1
6 5 4 3 2 1
7 6 5 4 3 2 1
The above table shows the pattern that occurs as the number of fields in a definition increases.
In the case of a definition containing five fields the sum of the distances of all field pairs is: (4*1 + 3*2 + 2*3 + 1*4) and the number of different pairs is: (4+3+2+1). Dividing these two values gives the average distance between two randomly chosen fields, e.g., 2.
Summing the distance over every field pair for a definition containing 3, 4, 5, 6, 7, 8, … fields gives the sequence: 1, 4, 10, 20, 35, 56, … This is sequence A000292 in the On-Line Encyclopedia of Integer sequences and is given by the formula n*(n+1)*(n+2)/6 (where n = N − 1, i.e., the number of fields minus 1).
Summing the number of different field pairs for definitions containing increasing numbers of fields gives the sequence: 1, 3, 6, 10, 15, 21, 28, … This is sequence A000217 and is given by the formula n*(n + 1)/2.
Dividing these two formula and simplifying yields (N + 1)/3.
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