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  • From: Thomas Passin <list1@t...>
  • Date: Sun, 01 Dec 2013 12:46:08 -0500
On 12/1/2013 12:05 PM, Ian Graham wrote:

Worth having a look at
http://scribblethink.org/Work/Softestim/kcsest.pdf, which attempts to
demonstrate:

    "Algorithmic (KCS) complexity results can be interpreted as
    indicating some limits to software estimation. While these limits
    are abstract they nevertheless contradict enthusiastic claims
    occasionally made by commercial software estimation advocates.
    Specifically, if it is accepted that algorithmic complexity is an
    appropriate definition of the complexity of a programming project,
    then claims of purely objective estimation of project complexity,
    development time, and programmer productivity are necessarily
    incorrect."

Which effectively means it's impossible to predict cost / timelines for
sufficiently complex problems, without actually doing the problem.  A
bit of a 'duuh' maybe for those here, but it's still nice to have this
backed up by a fancy paper with a cool mathematical proof.
Ah yes, the halting problem arises in another guise. Strictly speaking, since many complex programs cannot be proven to ever complete, how then could one arrive at an accurate estimate for developing a successful complex program (at least if it's one of those)?

A lot depends on how similar the project is to others that have already been developed. Of course, if you start with a new team each time, the similarities may not be very helpful.

One way to approach the estimation problem is to proceed in phases. At each phase, you re-estimate based on what you have learned. But that can be awfully hard to write a contract for, and hard to find managers that can accept the approach. For the Affordable Health Care system, it probably would have been impossible to get Congress to fund several stages flexibly, so if later phase estimates had increased a lot, there wouldn't have been any way to get money to cover it. Of course, the way it's worked out, the money has had to be obtained from somewhere anyway.

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