Path: utzoo!utgpu!news-server.csri.toronto.edu!rpi!zaphod.mps.ohio-state.edu!pacific.mps.ohio-state.edu!linac!att!cbnews!cbnewsm!lfd
From: lfd@cbnewsm.att.com (Lee Derbenwick)
Newsgroups: comp.software-eng
Subject: Re: Personal growth and software engineering!
Summary: How do the workers know what to measure?
Message-ID: <1991Apr8.163111.3968@cbnewsm.att.com>
Date: 8 Apr 91 16:31:11 GMT
References: <9233@castle.ed.ac.uk> <1991Mar25.164133.29674@unislc.uucp> <549@tivoli.UUCP>
Organization: AT&T Bell Laboratories
Lines: 45

In article <549@tivoli.UUCP>, alan@tivoli.UUCP (Alan R. Weiss) writes:

> If the metrics are bogus, then fix them by including the workers
> in the process.  In this case, "process" can mean calling a short
> meeting, identifying dumb metrics, and coming up with meaningful ones.

And how are the workers to know how to measure the process?  We may be
able to _reject_ certain measures as bogus, but that is much easier
than creating good measures, which is an open research area.

Here are a couple of quality metrics I would _like_: they seem to capture
two key areas of software quality -- faults and maintainability.  Both,
unfortunately, violate causality:

1. Total number, severity, and time-to-discovery of remaining faults that
   will be experienced by customers as software failures.

2. Cost of introducing the next several enhancements that will be required
   of this code.

Please suggest how a "short meeting" of software developers could come up
with _feasible_ versions of these.  (It is _not_ feasible to wait a year
or two for the results of measurement -- by then, you've already made
changes to your development process and probably to your staff, so the
time constant is too long to use the metrics for process improvement.)

> Clearly the absence of measurements relegates software creation to
> the arts, rather than as an engineering and/or scientific discipline.

Yes, the _absence_ of measurements would relegate software creation
to the arts.  But the fact that our measurement capabilities are
incomplete forces it to be a mix of science and art -- just as the
other branches of engineering are.

Note that I am _not_ saying that there is no basis for measurements,
but many of the ones I've seen published seem to rest on very shaky
assumptions.  E.g., cost to maintain may be statistically correlated
with some function of the cyclomatic numbers of the routines composing
a module, but a statistical correlation doesn't say anything about any
specific case.  Treating it as if it does (unless the correlation is
nearly perfect) is pseudo-science, not science.

 -- Speaking strictly for myself,
 --   Lee Derbenwick, AT&T Bell Laboratories, Warren, NJ
 --   lfd@cbnewsm.ATT.COM  or  <wherever>!att!cbnewsm!lfd