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by numerous experimental studies.
This article contributes no new concept since McConnell’s Chapter 20 says
all there is to say about the topic; my aim
is simply to make the Shortest Possible
Schedule Theorem better known, in particular to practitioners.
The myth about shortening project
times begins with an observation clearly
correct. Everyone understands if our project has been evaluated through accepted
cost-estimation techniques, to require
three developers over a year, we cannot
hire 36 people to complete it in a month.
Productivity does not always scale up.
Yet neither does common sense. Too
often the conclusion from the preceding
trivial observation takes the form of an
old saw, “Brooks’ Law”: adding people
to a late project delays it further. The ex-
planation is that newcomers cost more
through communication overhead than
they bring through actual contributions.
While a few other sayings of Brooks’
Mythical Man-Month have stood the test
of time, this one has always struck me
as describing, rather than any actual
law, a definition of bad management.
Of course if you keep haplessly throwing
people at deadlines, you are going to add
communication problems and make
things worse. But if you are a competent
manager, expanding team size is one of
the tools at your disposal to improve the
state of a project, and it would be fool-
ish to deprive yourself of it. A definitive
refutation of the supposed law, also by
McConnell, was published 20 years ago.
For all the criticism it deserves,
Brooks’ pronouncement was limited
in its scope: it addressed adding staff
to a project already late. It is even more
wrong to apply it to the more general
issue of cost-estimating and staffing
software projects at any stage of their
progress. Forty-year-old platitudes have
even less weight here. As McConnell’s
book shows, cost estimation is no longer a black art. It is not an exact science
either, but techniques exist to produce
The Shortest Possible Schedule theorem is one of the most interesting results. It is much more interesting than
Brooks’s purported law, because it is
backed by empirical studies (rather than
asking us to believe a pithy pronouncement), and instead of a general negative
view, it provides a positive result complemented by a limitation of that result,
and both are expressed quantitatively.
Figure 1 gives the general idea of the
SPS theorem. Figure 2 provides a more
The “nominal project” is the result of
a cost and schedule estimation yielding
the optimum point. The figure and the
theorem give project managers both a
reason to rejoice and a reason to despair:
˲ Rejoice: by putting in more money,
that is, more people (in software engi-
The Shortest Possible
Schedule Theorem: Yes,
You Can Throw Money
at Software Deadlines
October 27, 2019
Some folk wisdom going around in software engineering, often repeated for decades, is just wrong. It can be particularly damaging when it affects key aspects
of software development and is contradicted by solid scientific evidence. The
present discussion covers a question
that meets both of these conditions:
whether it makes sense to add staff to a
project to shorten its delivery time.
My aim is to popularize a result that
is well known in the software engineering literature, going back to the early
work of Barry Boehm,
1 and explained
with great clarity by Steve McConnell in
his 2006 book on software cost estimation Shortest Possible Schedule.
2 While an
empirical rather than a logical result, I
believe it deserves to be called a theorem
(McConnell stays shy of using the term)
because it is as close as we have in the
area of software engineering management to a universal property, confirmed
In Search of
Bertrand Meyer considers how to speed up software engineering.
DOI: 10.1145/3371385 http://cacm.acm.org/blogs/blog-cacm