The Shape of Code

Software developers read source code to obtain information. How might the information content of source code be quantified?

Both of the following functions assign the same value to x and if that is the only information a reader of that code is interested in, then the information content of both assignment statements could be said to be the same.

int foo(void)
{
x = 5;
...
}
 
int bar(void)
{
x = 2 + 3;
...

A reader seeking deeper understanding of the above code would ask why the value 5 is built from two values in bar. One reason might be that the author of the function wanted to explicitly call out background information about how the value 5 was derived (this is often done using symbolic names, but the use of literals themselves is sometimes encountered). Perhaps the author of foo did not see the need to expose this information or perhaps the shared value is purely coincidental.

If the two representations denote the same quantity doesn’t the second have a greater information content for a reader seeking deeper understanding?

In the following example:

... x + y & z ...
 
...
 
... num_red + num_white & lower_bits ...

an experienced developer with a knowledge of English is likely to interpret the expression as adding the number of occurrences of two quantities and using bit-wise AND to extract the lower bits. For some readers the second expression has a higher information content. Would use of the names number_of_red further increase the information content?

In the following example the first expression has not added any information that was not already present in the first expression above (except perhaps that the author was not certain of the precedence or perhaps did not expect subsequent readers to be certain).

... ( x + y ) & z ...
 
...
 
... x + ( y & z ) ...

The second expression uses parenthesis to achieve an operand/operator binding that is different from the default. Has this changed the information content of the expression?

There is experimental evidence that developers extract information from the names of variables to help them make decisions about operator precedence. To me the name all_32_bits_one suggests a sequence of bits and I would expect such a representation to be associated with the bit-wise AND operator, not binary plus. With no knowledge of the relative precedence of the two operators in the following expression the name of the middle operand would cause me to misinterpret the code. Does this change the information content of the expression? Does knowledge of the experimental evidence and the correct operator precedence change the information content (i.e., there is a potential fault in the code because the author may have assumed the incorrect precedence)?

... num_red + all_32_bits_one & sign_bit ...

There is experimental evidence that people use the amount of whitespace appearing between operands and their operators to visually highlight operator precedence

The relative quantities of whitespace used in the following two expressions appear to tell very different stories. Do the two expressions have a different information content?

... x  +  y & z ...
 
...
 
... x + y  &  z ...

The idea of measuring the information content of source code is very enticing. However, an accurate measure requires knowledge of the kind of information a reader is trying to obtain and of information that already exists in their brain.

Another question is the easy with which information can be extracted from code. Something that might be labeled as readability, except that readability has connotations of there being an abundant supply of information to extract.

Readability is an attribute that source code is often claimed to have, but what is it? While people are happy to use the term they have great difficulty in defining exactly what it is (I will eventually get around discussing my own own views in post). Ray Buse took a very simply approach to answering this question, he asked lots of people (to be exact 120 students) to rate short snippets of code and analysed the results. Like all good researchers he made his data available to others. This posting discusses my thoughts on the expected results and some analysis of the results.

The subjects were first, second, third year undergraduates and postgraduates. I would not expect first year students to know anything and for their results to be essentially random. Over the years, as they gain more experience, I would expect individual views on what constitutes readability to stabilize. The input from friends, teachers, books and web pages might be expected to create some degree of agreement between different students’ view of what constitutes readability. I’m not saying that this common view is correct or bears any relationship to views held by other groups of people, only that there might be some degree of convergence within a group of people studying together.

Readability is not something that students can be expected to have explicitly studied (I’m assuming that it plays an insignificant part in any course marks), so their knowledge of it is implicit. Some students will enjoy writing code and spends lots of time doing it while (many) others will not.

Separating out the data by year the results for first year students look like a normal distribution with a slight bulge on one side (created using plot(density(1_to_5_rating_data)) in R).

year by year this bulge turns (second year):

into a hillock (final year):

It is tempting to interpret these results as the majority of students assigning an essentially random rating, with a slight positive bias, for the readability of each snippet, with a growing number of more experienced students assigning less than average rating to some snippets.

Do the student’s view converge to a common opinion on readability? The answers appears to be No. An analysis of the final year data using Fleiss’s Kappa shows that there is virtually no agreement between students ratings. In fact every Interrater Reliability and Agreement function I tried said the same thing. Some cluster analysis might enable me to locate students holding similar views.

In an email exchange with Ray Buse I learned that the postgraduate students had a relatively wide range of computing expertise, so I did not analyse their results.

I wish I had thought of this approach to measuring readability. Its simplicity makes it amenable for use in a wide range of experimental situations. The one change I would make is that I would explicitly create the snippets to have certain properties, rather than randomly extracting them from existing source.