Describes a primitive programming style, one in which the programmer
relies on the computer's processing power instead of using his or her own
intelligence to simplify the problem, often ignoring problems of scale and
applying naive methods suited to small problems directly to large ones.
The term can also be used in reference to programming style: brute-force
programs are written in a heavyhanded, tedious way, full of repetition and
devoid of any elegance or useful abstraction (see also
*brute force and ignorance**).*

*The canonical example of a brute-force
algorithm is associated with the ‘traveling salesman problem’
(TSP), a classical NP-hard problem: Suppose a person
is in, say, Boston, and wishes to drive to N other
cities. In what order should the cities be visited in order to minimize
the distance travelled? The brute-force method is to simply generate all
possible routes and compare the distances; while guaranteed to work and
simple to implement, this algorithm is clearly very stupid in that it
considers even obviously absurd routes (like going from Boston to Houston
via San Francisco and New York, in that order). For very small
N it works well, but it rapidly becomes absurdly
inefficient when N increases (for N =
15, there are already 1,307,674,368,000 possible routes to
consider, and for N = 1000 — well, see
bignum). Sometimes, unfortunately, there is no
better general solution than brute force. See also
NP- and rubber-hose
cryptanalysis.*

*A more simple-minded example of brute-force programming is finding
the smallest number in a large list by first using an existing program to
sort the list in ascending order, and then picking the first number off the
front.*

*Whether brute-force programming should actually be considered stupid
or not depends on the context; if the problem is not terribly big, the
extra CPU time spent on a brute-force solution may cost less than the
programmer time it would take to develop a more ‘intelligent’
algorithm. Additionally, a more intelligent algorithm may imply more
long-term complexity cost and bug-chasing than are justified by the speed
improvement.*

*Ken Thompson, co-inventor of Unix, is reported to have uttered the
epigram “When in doubt, use brute force”. He probably
intended this as a ha ha only serious, but the
original Unix kernel's preference for simple, robust, and portable
algorithms over brittle ‘smart’ ones
does seem to have been a significant factor in the success of that OS.
Like so many other tradeoffs in software design, the choice between brute
force and complex, finely-tuned cleverness is often a difficult one that
requires both engineering savvy and delicate esthetic judgment.*