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<employees> <employee> <name>John Do</name> <phone>212-222-2222</phone> <age>20</age> <email>john@youremail.com</email> </employee> <employee> <name>Jane Smith</name> <phone>212-333-3333</phone>

Compile the application. Now we can import the SWF file and use Sothink to decompile it back into a Flex 3 project as shown in Figure 11-1.

echo "Could not move from $TEMPPATH/$SAARCHIVEDMG" exit 3 fi "$hdiutil" mount -nobrowse "$SABACKUPDIR"/"$SAARCHIVEDMG" >> "$SCRIPTLOG" echo "Mounting ServerAdmin Backup DMG" fi ## One last sanity check if [ ! -d "$SAARCHIVE_MOUNTPOINT" ]; then echo "Disk image did not seem to mount! Exiting!" exit 5 fi ## and last but not least, dump our settings echo "Checking for changes..." "$serveradmin" settings all | "$grep" -v "info:currentTime" > "$TEMPPATH"/sa_export_"$DATE".txt "$diff" "$SAARCHIVE_MOUNTPOINT"/latest.txt "$TEMPPATH"/"sa_export_$DATE.txt" &> /dev/null if [ $ == 0 ]; then echo "No changes were detected, not saving export" else echo "Changes found, saving output and creating diff file." "$diff" "$SAARCHIVE_MOUNTPOINT"/latest.txt "$TEMPPATH"/"sa_export_$DATE.txt" >> "$SAARCHIVE_MOUNTPOINT"/"sa_export_${DATE}-diff.txt" "$mv" -f "$TEMPPATH"/sa_export_"$DATE".txt "$SAARCHIVE_MOUNTPOINT"/"sa_export_$DATE.txt" cd "$SAARCHIVE_MOUNTPOINT" "$ln" -s "sa_export_$DATE.txt" "latest.txt" cd "$OLDPWD" fi if [ -d "$TEMPPATH" ]; then "$rm" -rf "$TEMPPATH" &> /dev/null fi ## if we're still here, then force the unmount (there is no messing around!) while [ -d "$SAARCHIVE_MOUNTPOINT" ]; do let COUNT++ if [ $COUNT -le 10 ]; then echo "Unmounting ServerAdmin Backup DMG: $SAARCHIVE_MOUNTPOINT" "$hdiutil" eject "$SAARCHIVE_MOUNTPOINT" >> "$SCRIPTLOG" elif [ $COUNT -eq 11 ]; then echo "ServerAdmin Backup DMG failed to unmount, forcing!" "$diskutil" unmount force "$SAARCHIVE_MOUNTPOINT" >> "$SCRIPTLOG" else echo "ServerAdmin Backup DMG failed to unmount!" break fi "$sleep" 1 done exit 0

If you haven t built an AIR application before, not to worry, the process is very similar to building a new Flex browser application.

Figure 3-10. Steps to add a data table to dataset 3. Click the header of the newly created data table, and name it dtCreditLimit. Let s start adding columns to dtCreditLimit by right-clicking the data table and selecting Add Column (see Figure 3-11).

There are a number of solutions for mass deployment and patch management in addition to those we cover from a technical point of view in this . These include LANrev, Puppet, Radmind, and even Deep Freeze by Faronics. Deep Freeze can be used to place a computer into a frozen state. The system can then be thawed for changes and rebooted to place it back into a frozen state. This is typically reserved for lab environments. LANrev is a popular product that supports Mac, Windows, and Linux. Radmind is a suite of command-line tools you can use to manage the software installation and configuration state across a group of computers. It provides a very complex toolset for ensuring consistent deployments across an arbitrary number of clients. Radmind can detect and manage changes to systems via a loadset, a predefined list of contents that you can compare to what s resident on clients and then use to replace, add, or remove client files. Using loadsets and overloads (listings of files, directories, and items associated with them), administrators can install, customize, and update software. Radmind is very good at keeping a collection of systems synchronized with a master environment----a capability you might need in a lab, for example. Radmind is slowly being uprooted by products like Casper and Package-based imaging solutions. The original developers have moved on from this tool. However, it still has a religious user base. Puppet is an open-source administration and policy framework, written in Ruby and used for numerous types of system automations. Radmind and Puppet take a similar approach to synchronizing systems with a master----both alter a remote set of files, but they use different methods. Radmind looks at file systems; Puppet uses facters, which are similar to the loadsets defined in Ruby, but far more granular. Puppet then employs a client library, which houses instructions for reaching predefined states. Because Radmind is great at maintaining file systems and Puppet is great at, and highly configurable for managing finely grained states, you ll find both useful. For example, you can use Radmind to manage certain directories you want to remain static, such as those involved in deployments of the Developer Tools from Mac OS X. Then you could put Puppet to work to let users change settings in a non-managed client environment while still allowing you to maintain some control. Or you might choose to manage servers with Puppet and workstations with Radmind. Both offer highly customizable environments for managing Mac OS X (and other operating systems). They are, however, far more difficult than GUI-centric tools, such as Casper Suite, LANrev, and DeployStudio. For that reason, Puppet and Radmind often get lumped together as very similar competing technologies. In fact, though, they re not that similar. If you re interested in exploring the capabilities of Puppet, consider the book Pulling Strings with Puppet: Configuration Management Made Easy by James Turnbull, published by Apress.

In this solution, we show how a convoy can be used to sequentially handle messages within an orchestration. The sequential convoy consists of the ReceivePortNameCorrelationSet and the ordered delivery flags specified on the receive location and send port. The first Receive shape initializes the correlation set, which is based on the receive port name by which the order was consumed. Initializing a correlation set instructs BizTalk Server to associate the correlation type data with the orchestration instance. This allows BizTalk to route all messages that have identical correlation type criteria (in our case, all messages consumed by the receive port bound to the orchestration) to the same instance. The Ordered Processing flag further instructs BizTalk Server to maintain order when determining which message should be delivered next to the orchestration.

Lexers generated by fslex keep track of partial information about the position of the most recently accepted token within the source stream of characters. In particular, the StartPos and EndPos properties on the LexBuffer type return Lexing.Position values. A partial signature of this position type is as follows: type Position with // The file name associated with the input stream. member FileName : string // The line number in the input stream, assuming fresh // positions have been updated modifying the // EndPos property of the LexBuffer. member Line : int // The character number in the input stream member AbsoluteOffset : int // Return the column number marked by the position, e.g. the // difference between the AbsoluteOffset and the StartOfLineAbsoluteOffset. member Column : int // Convert a position just beyond the end of a line to a // position at the start of the next line. member NextLine : Position ... end In some cases, certain lexer actions must perform extra bookkeeping. In particular, the lexer should update the EndPos property of the LexBuffer each time a newline marker is processed (this is left up to the lexer because the interpretation of newline characters can differ between various lexers). In particular, you can change the endOfLine rule in the lexer in Listing 16-3 to make this update: | newline { lexbuf.EndPos <- lexbuf.EndPos.NextLine; token lexbuf }