Govind Kanshi Aniruddha Deswandikar. Microsoft Technology Center

Transcription

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2 Govind Kanshi Aniruddha Deswandikar Microsoft Technology Center

3 Agenda Goal Overview of capabilities of Oslo toolkit at high level (200) Audience practicing developers, architects How 3 specific problems and their specific solutions with possible demos at high level Focus on how Oslo helps model and develop one of those solutions

4 Problem Domain Custom Rules Rule abstraction for business users

5 M driven Rules engine

6 What happens Rules Order Store Model Runtime

7 Problem domain YATL Home Get groceries - 9:30. Home Call painter 9:45. Bank Call for checkbook 14:00. Home Call the plumber 16:15.

8 What happens Task Model Store Runtime

9 Problem domain Behavior Driven Design Expression of requirements in form of story Why again reduce the ceremony of writing separate tests and remove communication problem with stakeholder

10 example Feature: Search In order to learn more As an information seeker I want to find more information Scenario: Find what I'm looking for Given I am on the " page When I search for "drupal magento flex" in form with name "f" Then I should see a link to - Ref : Arthur Murauskas -

11 Behavior driven design

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13 What happens Requirements Model Runtime Tests Model

14 Summary Intent MODELED in domain specific notation Runtime extract Intent + Do something

15 Domain? Runtime Domain Model

16 Chess anyone? 1. d4 Nf6 2. c4 e6 3. Nc3 Bb4 Nimzo-Indian Defence

17 Remember Chemistry C 6 H 14

18 DSL Domain specific language We know them already T-sql, xml config files, attributes based com+ coding Music notation, Chess position Chemical processes Internal (use base language or in modified form) Ruby/Python C# - mservice, boo External Pretty much anything under the tree

19 Real deal Let us model the task list. Steps Grammar Use Intellipad tool Use m to compile the resulting grammar Model Use Intellipad tool Use m to compile the resulting model Use mx to install into repository Use mx to extract m out of input Runtime

20 Sample grammer and parser

21 Now what We had the grammar We defined a parser which parsed it and returned us something What do we do next with it We use output to do something interesting.

22 Runtime LoadFromAssembly we are done ParserFactory.Create() Talk to database Talk to another abstraction Spitout intent xaml/asp.net mvc /wf/ orchestration

23 Runtime Demo Name Title Company

24 What did we see Problem domain Our solution A tool which helps Define grammar based on input Which parses and applies production rules to provide output We create a runtime to do interesting things with it

25 Let us get terminology right Intellipad M Structure (Mschema) Instance (Mgraph) Repository place to store the model what we did not see today- Quadrant

26 Big picture Grammar Intent Domain Specific Notation Transformation Inference Transformation Model UI ASP.NET/WPF Persistence Workflow

27 Where do you go from here MODELS! MODELS! MODELS!

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30 Related Content Breakout Sessions (session codes and titles) Interactive Theater Sessions (session codes and titles) Hands-on Labs (session codes and titles) Hands-on Labs (session codes and titles)

31 Track Resources Resource 2 Resource 3 Resource 4

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