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Unexpected experimental effects

January 16th, 2009

The only way to find out the factors that effect developers’ source code performance is to carry out experiments where they are the subjects.  Developer performance on even simple programming tasks can be effected by a large number of different factors.  People are always surprised at the very small number of basic operations I ask developers to perform in the experiments I run.  My reply is that only by minimizing the number of factors that might effect performance can I have any degree of certainty that the results for the factors I am interested in are reliable.

Even with what appear to be trivial tasks I am constantly surprised by the factors that need to be controlled.  A good example is one of the first experiments I ever ran.  I thought it would be a good idea to replicate, using a software development context, a widely studied and reliably replicated human psychological effect; when asked to learn and later recall/recognize a list of words people make mistakes.  Psychologists study this problem because it provides a window into the operation structure of the human memory subsystem over short periods of time (of the order of at most tens of seconds).  I wanted to find out what sort of mistakes developers would make when asked to remember information about a sequence of simple assignment statements (e.g., qbt = 6;).

I carefully read the appropriate experimental papers and had created lists of variables that controlled for every significant factor (e.g., number of syllables, frequency of occurrence of the words in current English usage {performance is better for very common words}) and the list of assignment statements was sufficiently long that it would just overload the capacity of short term memory (about 2 seconds worth of sound).

The results contained none of the expected performance effects, so I ran the experiment again looking for different effects; nothing.  A chance comment by one of the subjects after taking part in the experiment offered one reason why the expected performance effects had not been seen.  By their nature developers are problem solvers and I had set them a problem that asked them to remember information involving a list of assignment statements that appeared to be beyond their short term memory capacity.  Problem solvers naturally look for patterns and common cases and the variables in each of my carefully created list of assignment statements could all be distinguished by their first letter.  Subjects did not need to remember the complete variable name, they just needed to remember the first letter (something I had not controlled for).  Asking around I found that several other subjects had spotted and used the same strategy.  My simple experiment was not simple enough!

I was recently reading about an experiment that investigated the factors that motivate developers to comment code.  Subjects were given some code and asked to add additional functionality to it. Some subjects were given code containing lots of comments while others were given code containing few comments.  The hypothesis was that developers were more likely to create comments in code that already contained lots of comments, and the results seemed to bear this out.  However, closer examination of the answers showed that most subjects had cut and pasted chunks (i.e., code and comments) from the code they were given.  So code the percentage of code in the problem answered mimicked that in the original code (in some cases subjects had complicated the situation by refactoring the code).

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