[jboss-svn-commits] JBL Code SVN: r13722 - in labs/jbossrules/trunk/documentation/manual/en: Chapter-Examples and 1 other directories.
jboss-svn-commits at lists.jboss.org
jboss-svn-commits at lists.jboss.org
Mon Jul 23 08:13:44 EDT 2007
Author: mark.proctor at jboss.com
Date: 2007-07-23 08:13:43 -0400 (Mon, 23 Jul 2007)
New Revision: 13722
Added:
labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/EventManager.png
labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/JavaDialectConfiguration.png
labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/MVELDialectConfiguration.png
labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/RuleFlowEventListener.png
labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/StatefulSession.png
labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/StatelessSession.png
labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/StatelessSessionResult.png
Removed:
labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/Section-Leaps_Algorithm.xml
labs/jbossrules/trunk/documentation/manual/en/drools_logo.gif
Modified:
labs/jbossrules/trunk/documentation/manual/en/Chapter-Examples/Section-Examples.xml
labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/Agenda.png
labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/AgendaEventListener.png
labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/PackageBuilder.png
labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/PackageBuilderConfiguration.png
labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/RuleBase.png
labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/RuleBaseConfiguration.png
labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/RuleBaseFactory.png
labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/Section-Rules.xml
labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/Section-The_Drools_Rule_Engine.xml
labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/Section-What_is_a_Rule_Engine.xml
labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/WorkingMemory.png
labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/WorkingMemoryEventListener.png
labs/jbossrules/trunk/documentation/manual/en/drools_logo.png
labs/jbossrules/trunk/documentation/manual/en/master.xml
Log:
-more docs updates
Modified: labs/jbossrules/trunk/documentation/manual/en/Chapter-Examples/Section-Examples.xml
===================================================================
--- labs/jbossrules/trunk/documentation/manual/en/Chapter-Examples/Section-Examples.xml 2007-07-23 05:30:26 UTC (rev 13721)
+++ labs/jbossrules/trunk/documentation/manual/en/Chapter-Examples/Section-Examples.xml 2007-07-23 12:13:43 UTC (rev 13722)
@@ -1,22 +1,70 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<section>
- <title>Getting the examples</title>
-
- <para>Some examples are included as "integration tests" in the Drools source
- code - specifically the drools-compiler module. On top of these, you can
- download the drools-examples module; which is a self contained Eclipse
- project. This module is always having more samples added to it by users. The
- example project in eclipse requires that you have the plugin instilled: load
- up the drools-examples project (it has an eclipse project already setup).
- The rules all have example classes that execute the rules. If you want to
- try the examples in another project (or another IDE) then you will need to
- setup the dependencies by hand of course.</para>
-
- <para>The examples can be found at
- http://anonsvn.labs.jboss.com/labs/jbossrules/trunk/drools-examples/ (you
- can browse online, or use a subversion client and download the project into
- Eclipse</para>
-
- <para>Future documentation will include walk throughs for each of the
- examples.</para>
+<?xml version="1.0" encoding="UTF-8"?>
+<section>
+ <title>Getting the examples</title>
+
+ <para>Some examples are included as "integration tests" in the Drools source
+ code - specifically the drools-compiler module. On top of these, you can
+ download the drools-examples module; which is a self contained Eclipse
+ project. This module is always having more samples added to it by users. The
+ example project in eclipse requires that you have the plugin instilled: load
+ up the drools-examples project (it has an eclipse project already setup).
+ The rules all have example classes that execute the rules. If you want to
+ try the examples in another project (or another IDE) then you will need to
+ setup the dependencies by hand of course.</para>
+
+ <para>The examples can be found at
+ http://anonsvn.labs.jboss.com/labs/jbossrules/trunk/drools-examples/ (you
+ can browse online, or use a subversion client and download the project into
+ Eclipse</para>
+
+ <para>Future documentation will include walk throughs for each of the
+ examples.</para>
+
+ <section>
+ <title>Hello World</title>
+
+ <para></para>
+ </section>
+
+ <section>
+ <title>State Example</title>
+
+ <para></para>
+ </section>
+
+ <section>
+ <title>Fibonacci Example</title>
+
+ <para></para>
+ </section>
+
+ <section>
+ <title>Golfing Example</title>
+
+ <para></para>
+ </section>
+
+ <section>
+ <title>Trouble Ticket</title>
+
+ <para></para>
+ </section>
+
+ <section>
+ <title>PricingRuleDTExample</title>
+
+ <para></para>
+ </section>
+
+ <section>
+ <title>Honest Politician</title>
+
+ <para></para>
+ </section>
+
+ <section>
+ <title>Conways Game of Life</title>
+
+ <para></para>
+ </section>
</section>
\ No newline at end of file
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+ application/octet-stream
Deleted: labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/Section-Leaps_Algorithm.xml
===================================================================
--- labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/Section-Leaps_Algorithm.xml 2007-07-23 05:30:26 UTC (rev 13721)
+++ labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/Section-Leaps_Algorithm.xml 2007-07-23 12:13:43 UTC (rev 13722)
@@ -1,81 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<section>
- <title>Leaps Algorithm</title>
-
- <para>The Leaps algorithm for production systems uses a "lazy" approach to
- condition evaluations. A modified version of this algorithm, implemented as part
- of Drools v3, attempts to take the best features of both Leaps and Rete
- approaches in processing facts in the working memory. Leaps is not being
- described here in detail but only some relevant sections to described how
- current implementation deviates from "classical" leaps algorithm.</para>
-
- <para>The "classical" Leaps approach puts all incoming (asserted) facts on
- the main stack according to the order facts were asserted in the working
- memory (FIFO). It inspects facts one by one trying to find a match for each
- relevant (based on type of the fact and data types required by CEs) rule by
- iterating over collections of facts that match the datatype of each CE. As soon
- as such match is found, the system remembers the current iteration position so
- it can possibly resume iteration later and then fires the matching rules consequence.
- After execution of consequence is completed, the system trys to resume processing by
- inspecting a fact on the top of the main processing stack and either start
- processing from beginning or resumes the processing that was suspended.</para>
-
- <section>
- <title>Conflict Resolution</title>
-
-<!-- FIXME - This needs to be clarified. It is unclear at best as it stands now... -->
-
- <para>Please note that Leaps allows for rule firing before ALL cross-fact
- matches are attempted as per RETE approach, which explains the reported
- significant performance gains for this algorithm. It's made possible by
- pushing conflict resolution upfront before matching begins (sort order
- of facts on the stack and rules matching order), while with RETE all matches
- should (must) be attempted, activations are sorted based on the conflict resolution
- strategy and head element's consequence fired.</para>
-
- <para>The current implementation allows for flexible conflict resolution
- strategy selection. Even though it's not exposed as a pluggable feature, you
- can either use the supplied conflict resolution strategies
- (org.drools.leaps.conflict) or develop new ones to customize the default
- behavior. Update: The general approach for the conflict resolution stategy
- does not specifying whether the order of activation was based on fact or
- rule attributes. The current implementation does, however, allow for
- specifying that the conflict resolution strategy be based on the fact and
- rule attribute so it is more apparent.</para>
- </section>
-
- <section>
- <title>'Not' and 'Exists'</title>
-
- <para>The main deviation of the Drools 3 implmentation of Leaps from the
- "classical" Leaps is in the way it deals with "negative" and "exists" CE processing.
- The "classical" approach makes use of a "shadow" fact stack, a full scan of
- relevant collections to determine presence of certain facts matching NOT
- or EXISTS conditions and conversion of source rules to account for the
- instances where retracted facts "release" rule activations that were
- previously blocked by it. The current implementation takes a different
- approach. Its functionality is similar to the way RETE negates nodes by
- creating tuples with deferred activation in "lazy" manner.</para>
-<!-- FIXME - Last sentence of previous paragraph was confusing. Need to
- verfiy I didn't change the meaning.
- It was this:
- Its functionality is similar to the way RETE negative node by
- creating tuples with deferred activation in "lazy" manner.
--->
-
- <para>After finding matchs for all "positive" conditions, the current
- implementation starts looking for facts that might satisfy "not" and
- "exists" conditions. As soon as such a fact is found the system stops looking
- for a given CE and stores found fact handle. All the "not" and "exists"
- CEs are checked, with the CE's tuple being evaluated to see if it is eligible
- for activation - no matching "not" facts and all "exists" CEs have matching
- facts. The tuple is either activated or if it has blocking conditions ("not" facts or
- missing "exists"), then it's is deferred for further inspection.</para>
-
- <para>All fact assertions are then checked again, to see if they can activate tuples
- that were deferred from activation. At the same time, all facts that are
- being retracted are inspected to see if they remove a blocking condition from the
- deferred tuples or if they will deactivate an activation that was triggered by
- matching a given fact in an "exists" condition.</para>
- </section>
-</section>
\ No newline at end of file
Modified: labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/Section-Rules.xml
===================================================================
--- labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/Section-Rules.xml 2007-07-23 05:30:26 UTC (rev 13721)
+++ labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/Section-Rules.xml 2007-07-23 12:13:43 UTC (rev 13722)
@@ -2,7 +2,7 @@
<section>
<title>Knowledge Representation</title>
- <section>
+ <!--section>
<title>Production Rules</title>
<para>A
@@ -196,7 +196,7 @@
in response to changes in Working Memory's data. Rules are also fully
declarative in that they describe "what" not "how" like imperative
languages such as Java.</para>
- </section>
+ </section-->
<section>
<title>First Order Logic</title>
Modified: labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/Section-The_Drools_Rule_Engine.xml
===================================================================
--- labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/Section-The_Drools_Rule_Engine.xml 2007-07-23 05:30:26 UTC (rev 13721)
+++ labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/Section-The_Drools_Rule_Engine.xml 2007-07-23 12:13:43 UTC (rev 13722)
@@ -37,7 +37,7 @@
reference is maintained, unless configured otherwise. The Working Memory
consists of a number of sub components, inculding Working Memory Event
Support, Truth Maintenance System, Agenda and Agenda Event Support. Object
- assertion may result in the creation of one or more Activations. The
+ insertion may result in the creation of one or more Activations. The
Agenda is responsible for scheduling the execution of these
Activations.</para>
@@ -73,15 +73,17 @@
</mediaobject>
</figure>
- <para>Three classes are used for authoring: DrlParser, XmlParser and
- PackageBuilder. The two parser classes produce "descr" AST models from a
- provided Reader instance. PackageBuilder provides convienience APIs so
- that you can mostly forget about those classes. The two convienience
- methods are "addPackageFromDrl" and "addPackageFromXml" - both take an
+ <para>Four classes are used for authoring: DrlParser, XmlParser,
+ ProcessBuilder and PackageBuilder. The two parser classes produce "descr"
+ (description) AST models from a provided Reader instance. ProcessBuilder
+ reads in an xstream serialisation representation of the Rule Flow.
+ PackageBuilder provides convienience APIs so that you can mostly forget
+ about those classes. The three convienience methods are
+ "addPackageFromDrl", "addPackageFromXml" and addRuleFlow - all take an
instance of Reader as an argument. The example below shows how to build a
- package that includes both XML and DRL rule files, which are in the
- classpath. Note that all added package sources must be of the same package
- namespace for the current PackageBuilder instance!</para>
+ package that includes both XML, DRL and rule files and a ruleflow file,
+ which are in the classpath. Note that all added package sources must be of
+ the same package namespace for the current PackageBuilder instance!</para>
<example>
<title>Building a Package from Multiple Sources</title>
@@ -90,7 +92,8 @@
PackageBuilder builder = new PackageBuilder();
builder.addPackageFromDrl( new InputStreamReader( getClass().getResourceAsStream( "package1.drl" ) ) );
-builder.addPackageFromXml( new InputStreamReader( getClass().getResourceAsStream( "package2.drl" ) ) );
+builder.addPackageFromXml( new InputStreamReader( getClass().getResourceAsStream( "package2.xml" ) ) );
+builder.addRuleFlow( new InputStreamReader( getClass().getResourceAsStream( "ruleflow.rfm" ) ) );
Package pkg = builder.getPackage();
</programlisting>
Modified: labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/Section-What_is_a_Rule_Engine.xml
===================================================================
--- labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/Section-What_is_a_Rule_Engine.xml 2007-07-23 05:30:26 UTC (rev 13721)
+++ labs/jbossrules/trunk/documentation/manual/en/Chapter-Rule_Engine/Section-What_is_a_Rule_Engine.xml 2007-07-23 12:13:43 UTC (rev 13722)
@@ -30,37 +30,38 @@
(<ulink
url="http://en.wikipedia.org/wiki/Formal_grammar">wikipedia</ulink>).</para>
- <para>Business Rule Management Systems build additional value on top of
- a general purpose Rule Engines by providing, business user focused,
- systems for rule creation, management, deployment, collaboration, analysis
- and end user tools. Further adding to this value is the fast evolving and
- popular methodology "Business Rules Approach", which is a helping
- to formalize the role of Rule Engines in the enterprise.</para>
+ <para>Business Rule Management Systems build additional value on top of a
+ general purpose Rule Engines by providing, business user focused, systems
+ for rule creation, management, deployment, collaboration, analysis and end
+ user tools. Further adding to this value is the fast evolving and popular
+ methodology "Business Rules Approach", which is a helping to formalize the
+ role of Rule Engines in the enterprise.</para>
<para>The term Rule Engine is quite ambiguous in that it can be any system
that uses rules, in any form, that can be applied to data to produce
outcomes; which includes simple systems like form validation and dynamic
- expression engines. The book "How to Build a Business Rules Engine (2004)" by
- Malcolm Chisholm exemplifies this ambiguity. The book is actually about
- how to build and alter a database schema to hold validation rules. The book
- then shows how to generate VB code from those validation rules to validate
- data entry - while a very valid and useful topic for some, it caused quite
- a suprise to this author, unaware at the time in the subtleties of Rules
- Engines differences, who was hoping to find some hidden secrets to help
- improve the Drools engine. JBoss jBPM uses expressions and delegates in its
- Decision nodes; which control the transitions in a Workflow. At each node
- it evaluates has a rule set that dicates the transition to undertake - this is
- also a Rule Engine. While a Production Rule System is a kind of Rule
- Engine and also an Expert System, the validation and expression evaluation
- Rule Engines mention previously are not Expert Systems.</para>
+ expression engines. The book "How to Build a Business Rules Engine (2004)"
+ by Malcolm Chisholm exemplifies this ambiguity. The book is actually about
+ how to build and alter a database schema to hold validation rules. The
+ book then shows how to generate VB code from those validation rules to
+ validate data entry - while a very valid and useful topic for some, it
+ caused quite a suprise to this author, unaware at the time in the
+ subtleties of Rules Engines differences, who was hoping to find some
+ hidden secrets to help improve the Drools engine. JBoss jBPM uses
+ expressions and delegates in its Decision nodes; which control the
+ transitions in a Workflow. At each node it evaluates has a rule set that
+ dicates the transition to undertake - this is also a Rule Engine. While a
+ Production Rule System is a kind of Rule Engine and also an Expert System,
+ the validation and expression evaluation Rule Engines mention previously
+ are not Expert Systems.</para>
<para>A Production Rule System is turing complete with a focus on
- knowledge representation to expression propositional and first order logic
- in a concise, non ambigious and declarative manner. The brain of a
- Production Rules System is an Inference Engine that is able to scale to a
- large number of rules and facts. The Inference Engine matches facts and
- data, against Production Rules, also called Productions or just Rules, to
- infer conclusions which result in actions. A Production Rule is a two-part
+ knowledge representation to express propositional and first order logic in
+ a concise, non ambigious and declarative manner. The brain of a Production
+ Rules System is an Inference Engine that is able to scale to a large
+ number of rules and facts. The Inference Engine matches facts and data,
+ against Production Rules, also called Productions or just Rules, to infer
+ conclusions which result in actions. A Production Rule is a two-part
structure using First Order Logic for knowledge representation.</para>
<programlisting>when
@@ -69,15 +70,11 @@
<actions></programlisting>
<para>The process of matching the new or existing facts against Production
- Rules is called
- <indexterm>
+ Rules is called <indexterm>
<primary>Pattern Matching</primary>
- </indexterm>
- Pattern Matching, which is performed by the
- <indexterm>
+ </indexterm> Pattern Matching, which is performed by the <indexterm>
<primary>Inference Engine</primary>
- </indexterm>
- Inference Engine. There are a number of algorithms used for
+ </indexterm> Inference Engine. There are a number of algorithms used for
Pattern Matching by Inference Engines including:</para>
<itemizedlist>
@@ -98,40 +95,30 @@
</listitem>
</itemizedlist>
- <para>Drools has implementations for both
- <indexterm>
- <primary>Rete</primary>
- </indexterm>
- Rete and
- <indexterm>
- <primary>Leaps</primary>
- </indexterm>
- Leaps; Leaps is considered experimental, as it is quite new.
- The Drools
- <indexterm>
- <primary>Rete</primary>
- </indexterm>
- Rete implementation is called ReteOO, signifying that Drools
- has an enhanced and optimised implementation of the Rete algorithm for
- Object Oriented systems. Other Rete based engines also have marketing
+ <para>Drools implements and extends the <indexterm>
+ <primary>Rete</primary>
+ </indexterm> Rete algorith, <indexterm>
+ <primary>Leaps</primary>
+ </indexterm> Leaps use to be supported but was removed due to poor
+ maintenance. The Drools <indexterm>
+ <primary>Rete</primary>
+ </indexterm> Rete implementation is called ReteOO, signifying that
+ Drools has an enhanced and optimised implementation of the Rete algorithm
+ for Object Oriented systems. Other Rete based engines also have marketing
terms for their proprietary enhancements to Rete, like RetePlus and Rete
III. It is important to understand that names like Rete III are purely
marketing where, unlike the original published Rete Algorithm, no details
- of the implementation are published. This makes questions such as "Does Drools
- implement Rete III?" nonsensical. The most common enhancements are
+ of the implementation are published. This makes questions such as "Does
+ Drools implement Rete III?" nonsensical. The most common enhancements are
covered in "Production Matching for Large Learning Systems (Rete/UL)"
(1995) by Robert B. Doorenbos.</para>
- <para>The Rules are stored in the
- <indexterm>
+ <para>The Rules are stored in the <indexterm>
<primary>Production Memory</primary>
- </indexterm>
- Production Memory and the facts that the Inference Engine
- matches against the
- <indexterm>
+ </indexterm> Production Memory and the facts that the Inference Engine
+ matches against the <indexterm>
<primary>WorkingMemory</primary>
- </indexterm>
- Working Memory. Facts are asserted into the Working Memory
+ </indexterm> Working Memory. Facts are asserted into the Working Memory
where they may then be modiied or retracted. A system with a large number
of rules and facts may result in many rules being true for the same fact
assertion, these rules are said to be in conflict. The Agenda manages the
@@ -204,13 +191,13 @@
</mediaobject>
</figure>
- <para>Backward chaining is 'goal-driven', meaning that we start with a conclusion
- which the engine tries to satisfy. If it can't it then searches for conclusions that
- it can, known as 'sub goals', that will help satisfy some unknown part of the
- current goal - it continues this process until either the initial conclusion
- is proven or there are no more sub goals. Prolog is an example of a Backward
- Chaining engine; Drools will adding support for Backward Chaining in its next
- major release.</para>
+ <para>Backward chaining is 'goal-driven', meaning that we start with a
+ conclusion which the engine tries to satisfy. If it can't it then searches
+ for conclusions that it can, known as 'sub goals', that will help satisfy
+ some unknown part of the current goal - it continues this process until
+ either the initial conclusion is proven or there are no more sub goals.
+ Prolog is an example of a Backward Chaining engine; Drools will adding
+ support for Backward Chaining in its next major release.</para>
<figure>
<title>Backward Chaining</title>
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Modified: labs/jbossrules/trunk/documentation/manual/en/master.xml
===================================================================
--- labs/jbossrules/trunk/documentation/manual/en/master.xml 2007-07-23 05:30:26 UTC (rev 13721)
+++ labs/jbossrules/trunk/documentation/manual/en/master.xml 2007-07-23 12:13:43 UTC (rev 13722)
@@ -73,8 +73,6 @@
<xi:include href="Chapter-Rule_Engine/Section-Rete_Algorithm.xml" />
- <xi:include href="Chapter-Rule_Engine/Section-Leaps_Algorithm.xml" />
-
<xi:include href="Chapter-Rule_Engine/Section-The_Drools_Rule_Engine.xml" />
<!--xi:include href="Chapter-Rule_Engine/Section-Rule_Base.xml" />
@@ -99,8 +97,20 @@
<xi:include href="Chapter-Install/Section-Eclipse.xml" />
</chapter>
+
+ <chapter>
+ <title>Decision Tables</title>
+ <xi:include href="Chapter-Decision_Tables/Section-Spreadsheet.xml" />
+ </chapter>
+
<chapter>
+ <title>The Rule Workbench (IDE)</title>
+
+ <xi:include href="Chapter-IDE/Section-QuickStart.xml" />
+ </chapter>
+
+ <chapter>
<title>The Rule Language</title>
<xi:include href="Chapter-Rule_Language/Section-Overview.xml" />
@@ -117,9 +127,9 @@
<xi:include href="Chapter-Rule_Language/Section-DSL.xml" />
- <xi:include href="Chapter-Rule_Language/Section-XML.xml" />
-
<xi:include href="Chapter-Rule_Language/Section-RuleFlow.xml" />
+
+ <xi:include href="Chapter-Rule_Language/Section-XML.xml" />
<!--xi:include href="Chapter-Rule_Language/Section-Column.xml" />
@@ -127,19 +137,17 @@
<xi:include href="Chapter-Rule_Language/Section-Conditional_Elements.xml" /-->
</chapter>
-
+
<chapter>
- <title>Decision Tables</title>
+ <title>Deployment and Testing</title>
- <xi:include href="Chapter-Decision_Tables/Section-Spreadsheet.xml" />
- </chapter>
+ <xi:include href="Chapter-Deployment/Section-Deployment.xml" />
- <chapter>
- <title>The Rule Workbench (IDE)</title>
-
- <xi:include href="Chapter-IDE/Section-QuickStart.xml" />
+ <xi:include href="Chapter-Deployment/Section-Testing.xml" />
</chapter>
+ <chapter>
+
<chapter>
<title>The BRMS (Business Rule Management System)</title>
@@ -168,31 +176,22 @@
<xi:include href="Chapter-JSR94/Section-References.xml" />
</chapter>
- <chapter>
+ <!--chapter>
<title>Performance tuning</title>
<xi:include href="Chapter-Performance_Tuning/Section-Performance.xml" />
- </chapter>
+ </chapter-->
- <chapter>
<title>Examples</title>
<xi:include href="Chapter-Examples/Section-Examples.xml" />
</chapter>
- <chapter>
- <title>Deployment and Testing</title>
-
- <xi:include href="Chapter-Deployment/Section-Deployment.xml" />
-
- <xi:include href="Chapter-Deployment/Section-Testing.xml" />
- </chapter>
-
- <chapter>
+ <!--chapter>
<title>Papers</title>
<xi:include href="Chapter-Papers/Section-Manners.xml" />
- </chapter>
+ </chapter-->
</part>
<index />
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