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The list box on the right displays redaction terms. By default, this consists of <none> and Redacted. The term that has a check box next to it is considered the default redaction term, and is embedded in any new Redaction redline. The following list describes other features on this tab: Redaction text: To add a new redaction term, enter the text of the term into this empty field. Move up: Highlighting a redaction term in the list box and clicking this button causes it to move up the list. This list order defines the order in which terms appear in the shortcut menu. Move down: Highlighting a redaction term in the list box and clicking this button causes it to move down the list. This list order defines the order in which terms appear in the shortcut menu. Add: Adds the redaction term entered in the Redaction text field to the list box. The term appears in the redaction shortcut menu. Remove: Removes a redaction term from the list. You must first select and highlight the term to be removed in the list. The term will no longer appear in the redaction shortcut menu. Font: Opens the same Font dialog shown previously in Figure 12-17. Options selected from this dialog affect the font style, color, size, and other properties of redaction terms alone, not any text associated with other redlines. Make default: Makes the highlighted redaction term the default term when new redactions are created. The default redaction term is denoted by a check mark. The following sections describe other options on the Redlines toolbar.

Next, if we request /dwarfs/grumpy/bashful/sneezy with the test script: $ CATALYST_DEBUG=0 script/dispatchtest_test.pl /dwarfs/grumpy/bashful/sneezy we get the following output: <pre> --- Root -> catchall: - dwarfs - grumpy - bashful - sneezy - Root -> end </pre> Now you can see that $c->req->args is full of the trailing arguments from the request. Moving on, we can make a separate Dwarfs controller as part of the same application. Again, we ll comment out the begin and auto actions until we re going to use them. package DispatchTest::Controller::Dwarfs; use strict; use warnings; use parent 'Catalyst::Controller'; sub catchall : Path { my ( $self, $c ) = @_; push @{$c->stash->{matches}}, { 'Dwarfs' . ' -> ' . $c->action => $c->req->args }; } # # # # # # # # # # 1; sub begin : Private { my ($self, $c) = @_; push @{$c->stash->{matches}}, { 'Dwarfs' . ' -> ' . 'begin' => $c->req->args }, } sub auto : Private { my ($self, $c) = @_; push @{$c->stash->{matches}}, { 'Dwarfs' . ' -> ' . 'auto' }

At the beginning of this section, you learned that information needs can be formalized by identifying which entities are relevant for the information system, and then deciding which attributes are relevant for each entity. Now we can add a third step to the information analysis list of steps to produce a formal data model: 1. 2. 3. Which entities are relevant for the information system Which attributes are relevant for each entity Which integrity constraints should be enforced by the system

Another type of redline is the Hollow box option , which creates a hollow rectangular box. This type of redline doesn t mask portions of an image, but outlines them. Figure 12-22 displays an example of a hollow rectangular box.

Designing appropriate data models is not a sinecure, and it is typically a task for IT specialists. On the other hand, it is almost impossible to design data models without the active participation of the future end users of the system. End users usually have the most expertise in their professional area, and they are also involved in the final system acceptance tests. Over the years, many methods have been developed to support the system development process itself, to generate system documentation, to communicate with project participants, and to manage projects to control time and costs. Traditional methods typically show a strict phasing of the development process and a description of what needs to be done in which order. That s why these methods are also referred to as waterfall methods. Roughly formulated, these methods distinguish the following four phases in the system development process: 1. 2. 3. 4. Analysis: Describing the information needs and determining the information system boundaries Logical design: Getting answers to the three questions about entities, attributes, and constraints, which were presented in the previous section Physical design: Translating the logical design into a real database structure Build phase: Building database applications