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<?xml-stylesheet type="text/xsl" href="http://blogs.msdn.com/utility/FeedStylesheets/rss.xsl" media="screen"?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:slash="http://purl.org/rss/1.0/modules/slash/" xmlns:wfw="http://wellformedweb.org/CommentAPI/"><channel><title>Model-Driven Approaches</title><link>http://blogs.msdn.com/jmeier/archive/2008/08/01/model-driven-approaches.aspx</link><description>When people ask me my take on model-driven approaches, I think of two ends of the spectrum -- human and the machine. Key Points Model for humans . For humans, I find using a whiteboard (whiteboard modeling) works well -- it's universal. Model for machines</description><dc:language>en-US</dc:language><generator>CommunityServer 2.1 SP1 (Build: 61025.2)</generator><item><title>re: Model-Driven Approaches</title><link>http://blogs.msdn.com/jmeier/archive/2008/08/01/model-driven-approaches.aspx#8800661</link><pubDate>Fri, 01 Aug 2008 19:33:44 GMT</pubDate><guid isPermaLink="false">91d46819-8472-40ad-a661-2c78acb4018c:8800661</guid><dc:creator>Billigflug New York</dc:creator><description>&lt;p&gt;Well structured, nice post. Modelling always has the advantage that you can play with your ideas on a simplified playground. &lt;/p&gt;
</description></item><item><title>re: Model-Driven Approaches</title><link>http://blogs.msdn.com/jmeier/archive/2008/08/01/model-driven-approaches.aspx#8805742</link><pubDate>Sat, 02 Aug 2008 19:32:37 GMT</pubDate><guid isPermaLink="false">91d46819-8472-40ad-a661-2c78acb4018c:8805742</guid><dc:creator>J.D. Meier</dc:creator><description>&lt;p&gt;Thanks.&lt;/p&gt;
&lt;p&gt;&amp;gt; you can play with your ideas on a simplified playground&lt;/p&gt;
&lt;p&gt;Exactly! &amp;nbsp;&lt;/p&gt;
</description></item><item><title>re: Model-Driven Approaches</title><link>http://blogs.msdn.com/jmeier/archive/2008/08/01/model-driven-approaches.aspx#8870313</link><pubDate>Fri, 15 Aug 2008 21:07:46 GMT</pubDate><guid isPermaLink="false">91d46819-8472-40ad-a661-2c78acb4018c:8870313</guid><dc:creator>xowl</dc:creator><description>&lt;p&gt;I think there are two places where CASE-type model&amp;lt;-&amp;gt;code conversion works well and they both share the property that only the surface of the model--the part that defines how the modeled process and objects--is retained in the conversion. &lt;/p&gt;
&lt;p&gt;One is automated ER diagramming tools that allow good visual models that work for learning, sharing, and designing to be converted into creation and updating code. This was one of the earliest CASE successes and is still a major win in data modeling.&lt;/p&gt;
&lt;p&gt;The other is automated interface extraction tools that take sequence-type diagrams and identify exposed interfaces for your objects. It allows for clear common closure on interfaces, it can be reversed from a call tree (with moderate success), and it's far, far more successful than automatic conversion of full entity models to code objects.&lt;/p&gt;
&lt;p&gt;Given that ER database conversion is pretty early in the CASE history and that sequence and interface (whether from modern sequence diagrams, mid-90s DFDs, or whathaveyou) are from early BPR, we're seeing that some of the older (10-15 year) modeling tools are finally mature enough to be useful. Although, to be fair, ER/win has been great since approximately the dawn of time.&lt;/p&gt;
&lt;p&gt;I make teams I work with remove any automated model coupling that generates code and put warning on generated models. I have never seen either be reliable enough. Even with ER/win or a sequence diagram-&amp;gt;interface tool I want a complex neural net trained to analyze code to verify the results.&lt;/p&gt;
</description></item><item><title>re: Model-Driven Approaches</title><link>http://blogs.msdn.com/jmeier/archive/2008/08/01/model-driven-approaches.aspx#8871221</link><pubDate>Sat, 16 Aug 2008 05:44:30 GMT</pubDate><guid isPermaLink="false">91d46819-8472-40ad-a661-2c78acb4018c:8871221</guid><dc:creator>J.D. Meier</dc:creator><description>&lt;p&gt;Hey xowl&lt;/p&gt;
&lt;p&gt;&amp;gt; remove any automated model coupling that generates code &lt;/p&gt;
&lt;p&gt;&amp;gt; I want a complex neural net trained to analyze code to verify the results&lt;/p&gt;
&lt;p&gt;Good points!&lt;/p&gt;
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