           SPELL=dspam
if [[ $DSPAM_BRANCH == scm ]]; then
if [[ $DSPAM_SCM_AUTO == y ]]; then
         VERSION=$(date +%Y%m%d)
else
         VERSION=scm
fi
          SOURCE="${SPELL}-git.tar.bz2"
   SOURCE_URL[0]=git://dspam.git.sourceforge.net/gitroot/dspam/dspam:dspam-scm
   SOURCE_IGNORE=volatile
  FORCE_DOWNLOAD=on
SOURCE_DIRECTORY="$BUILD_DIRECTORY/$SPELL-scm"
elif [[ $DSPAM_BRANCH == devel ]]; then
         VERSION=3.9.1-RC1
          SOURCE="${SPELL}-${VERSION}.tar.gz"
   SOURCE_URL[0]=$SOURCEFORGE_URL/$SPELL/$SOURCE
     SOURCE_HASH=sha512:fd70938b3ef368fbfb992921a596972dc665ce9c6869ca362274c4bd02174fbfd3419438f63c1cdef06167fcde1ceea30fe359228642010bef4d77036e6bcf2f
SOURCE_DIRECTORY="$BUILD_DIRECTORY/$SPELL-$VERSION"
else
         VERSION=3.9.0
          SOURCE="${SPELL}-${VERSION}.tar.gz"
     SOURCE_HASH=sha512:9208e973855e4527802603570ae7a8fbdafe9c4a40aaa55eda91810d98c13a234e1e1f681c9a219869fbb58c5be10d908d8a974d63d75dab965641b29ef557e6
   SOURCE_URL[0]=$SOURCEFORGE_URL/$SPELL/$SOURCE
SOURCE_DIRECTORY="$BUILD_DIRECTORY/$SPELL-$VERSION"
fi
        WEB_SITE="http://dspam.sourceforge.net/"
            DOCS="$DOCS RELEASE.NOTES UPGRADING"
      LICENSE[0]='GPL'
      PATCHLEVEL=0
        KEYWORDS="email mail spam filter"
           SHORT='A server-side anti-spam agent for UNIX email servers'
cat << EOF
DSPAM is a scalable and open-source content-based spam filter designed for 
multi-user enterprise systems. On a properly configured system, many users 
experience results between 99.5% - 99.95%, or one error for every 200 to 2000 
messages. DSPAM supports many different MTAs and can also be deployed as a 
stand-alone SMTP appliance. For developers, the DSPAM core engine (libdspam) can
be easily incorporated directly into applications for drop-in filtering (GPL 
applies; commercial licenses are also available).

DSPAM has been implemented on many large and small scale systems with the largest
being reported at about 350,000 mailboxes. It is presently being used or planned
for use in multiple commercial solutions.

DSPAM is an adaptive filter which means it is capable of learning and adapting to
each user's email. Instead of working off of a list of "rules" to identify spam,
DSPAM's probabilistic engine examines the content of each message and learns what
type of content the user deems as spam (or nonspam). This approach to 
machine-learning provides much higher levels of accuracy than commercial
"hodge-podge" solutions, and with minimal resources. DSPAM's best recorded levels
of accuracy have included 99.991% by one avid user (2 errors in 22,786) and 99.987%
by the author (1 error in 7000), which is ten times more accurate than a human being!
EOF
