Python Productivity Gain?

[Harry George]

corey.coughlin at attbi.com (Corey Coughlin) writes:

> It is a difficult problem, but I don't think it's completely
> insurmountable.  Take some programmers right out of school, or just a
> general population of people, give them training in language X for a
> fixed period of time, set them up to perform some task, and see how
> long it takes them.  Sure, some of them will be better programmers
> than others, but with a large enough sample population you should be
> able to draw some conclusions on the average, if there is an effect to
> be measured.  And yes, the bigger the population, the better the
> results, so it would be fairly expensive to conduct, but still, you
> could draw conclusions.  Getting funding would be tricky, though,
> that's a given.
> 
>

It is common for a ComSci prof or grad student to crank up such a
study, using undergrad and grad students as the subjects.  These
subjects can generally be coerced to participate ("it is required for
the course").  For "novice programmer" research, high school students
are often used.  These tend to be self-selected, and ar not
representative for the general population.

So it is possible to set up such an experiment, and even to attend to
all the statistical niceties.  The problem is that the experimental
model fails to match reality in other ways.

For example, real world teams have usually solved interpersonal
pecking orders and courting rituals before the coding starts.  They
have domain knowledge beyond reading a (possibly fake) case study.
They have well-honed development environments, and may have existing
sets of unittests.  Their requirements/directions are subject to major
changes in midstream.  

These conditions are hard to duplicate in a short term academic
settings.  They cannot be solved by larger sample size.  That's why I
suggest that "lab research" is not ready for prime time in this field.

Some researchers have gone out in the field to use working teams.
Others retrospectively examine past projects.  These have the flavor
of "field research".



 
> 
> 
> Paul Prescod <paul at prescod.net> wrote in message news:<mailman.86.1077050210.31398.python-list at python.org>...
> > kbass wrote:
> > 
> > > In different articles that I have read, persons have constantly eluded to
> > > the productivity gains of Python. One person stated that Python's
> > > productivity gain was 5 to 10 times over Java in some in some cases. The
> > > strange thing that I have noticed is that there were no examples of this
> > > productivity gain (i.e., projects, programs, etc.,...).  Can someone give me
> > > some real life examples of productivity gains using Python as opposed other
> > > programming languages.
> > 
> > The problem is always: how do you measure/judge this?
> > 
> > Are you going to get the SAME PROGRAMMERS to solve the same problem 
> > twice? If so, the second language will have a big advantage. Are you 
> > going to get different programmers? How do you know they are the same skill?
> > 
> > Also: productivity for what? If your Java code is a little bit of glue 
> > around some pre-existing EJBs then it may have an advantage. If you are 
> > using Python and Pyrex to wrap C code, then Python will certainly have 
> > an advantage.
> > 
> > Most Python programmers are speaking about their personal productivity 
> > gain measured based on "feel". It is possible to do a more formal study 
> > (dozens of programmers given a variety of tasks) but it would be quite 
> > expensive. What unbiased source is going to pay for it.
> > 
> >   Paul Prescod

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