Markus Völter

Transcription

1 of Markus Völter

2

3 Examples 1

4 Healthcare

5 Context & Motivation Mobile Apps that help patients w/ treatments Monitor side-effects and recommend actions Manage dosage of medications

6 Context & Motivation Mobile Apps that help patients w/ treatments Monitor side-effects and recommend actions Manage dosage of medications Algorithms for recommendations and dosage at the core of these apps. Safety-critical, since they could hurt patients. Customer develops many different apps/algos like this, efficiency of algo development is key.

7 Context & Motivation Health care professionals directly code algos, using a suitable language. typical DSL-based devapproach. Avoids indirections through requirements docs. Speed up dev significantly.}pretty

8 Some Language Impressions I

9 Some Language Impressions II

10 Some Language Impressions III

11 Safety-Critical

12 Read More! Recently Accepted. Detailed Case Study will be published soon. Sneak Peek:

13 Insurance

14 Context & Motivation Specify/Program Insurance Programs Write formal code in a DSL mixed with tables and text No tool support whatsoever No testing (except inspection) No reuse No modularity No varibility

15 Context & Motivation Specify/Program Insurance Programs Write formal code in a DSL mixed with tables and text No tool support whatsoever No testing (except inspection) No reuse No modularity No varibility

16 A real Example: Legacy Specify/Program Debug Debugging directly in C Search-for-use by text search Don t trust the documents may be outdated! Insurance Programs Pixelcrap Implement C Code Write formal code in a DSL mixed with tables and text No tool support whatsoever No testing (except inspection) No reuse No modularity No varibility Printed, PDF Developer reads spec Very idiomatic implementation Dev acts as a human compiler and implements it in C

17 Solution Approach Specify/Program/Test/Debug Insurance Programs Write formal code in a DSL mixed with tables and text Now with IDE support and executable tests The same notation!

18 A real Example: Future Specify/Program/Test/Debug Insurance Programs Generate C Code Still exactly the same C code, or improved as needed. Incremental Refinement/Refactoring of languages: Partially automated migration of models Add model natural notations (insurance-specific, math) Add Support for modularity, reuse, variants

19 Salary

20 Context & Motivation Calculate Salaries + Taxes for Employees Various deployment platforms Complex Business Logic Variability over 16 States Based on evolving Law Dates & Currencies Temporal Data + Arithmetics Reactive Rules

21 Currencies and Dates

22 Temporal Data

23 Result Data and Rules

24 Approach in a Nutshell 2

25 Integration of Fachler

26 [Fachlichkeit] It s what makes a business tick. Distinguishes the business. Business Rules (Financial) Calculations Data Structures Mappings or Queries Validations Scientific Processes Contracts Processes UIs}

27 Reality

28 Goal!

29 Separation from Technology

30 Outdated Technology Fachlichkeit burried Non-Understandable Logic in implementation code. Expensive to Evolve

31 Technology & Business Logic now have connected lifecycles.

32 Goal: Separate the Lifecycles Fachlichkeit Technology

33 Lessons Learned 3

34 Notation Notation Notation

35 Math Insurance Math

36 Security Analysis Fahrtenschreiber-Regeln

37 Feature Models Component Architectures

38 Dataflow Diagrams

39 Form Style

40 Precision vs. Programming

41 {Formulas, Rules Data Structures Tables Values Precision!= Programming Performance Scalability Robustness Deployment }

42

43 A Language is not Enough

44 Language Design::More than Lang GOOD Language Abstractions Notations Great IDE Syntax Coloring Code Completion Goto Definition Analyses Relevant Good Errors GREAT Refactorings Aligned with Processes Testing Write Tests Run them Report Back Debuggers Animate Execution Simulators

45 Testing

46 Inspector Tracing the values of expressions.

47 Debugger

48 Influences on the Language

49 Language Design::Influences Domain Structure Non Functionals Permissions, IP, Sharing User Skills Sep. of Concerns Different Views Get a better tool :-) Educate, Put results in context Refactor towards Structure Model Purpose Analyze, Generate Tool Capabilities Notations, Editing, Scale Software Engineering Practices

50 Language Design::Influences Domain Structure Non Functionals Permissions, IP, Sharing User Skills Sep. of Concerns Different Views Get a better tool :-) Educate, Put results in context Refactor towards Structure Model Purpose Analyze, Generate Tool Capabilities Notations, Editing, Scale Software Engineering Practices

51 In conflict with Agile?

52 DSLs and Agile is in Conflict. 1 Project Language Development Depend on, use System Development Later: 2 Project 1 Language Development Dep d on, use Project 2 System Development Project N

53 DSLs and Agile is in Conflict. 1 Project Language Development Depend on, use System Development Framework Library Platform Manage like any other intra-project dependency. Evolution of client code is easier than for F/L/P because of migration support!

54 DSLs and Agile is in Conflict. Later: 2 Project 1 Language Development Framework Library Platform Dep d on, use Project 2 System Development Manage like any other 3rd party depencency: Development Roadmap Issue Tracker Release Notes...

55 DSLs and Agile is in Conflict. 3 Project 2 System Development Models and DSLs are an Enabler for Agility: Integration of Domain Experts Living Requirements Decoupled Fachlichkeit & Technik

56 DSLs and Agile is in Conflict. 4 Project 1 Language Development Leading LWBs are so productive, you can literally sit with the domain experts and interactively prototype languages (and then clean up later) I ve looked at the implementation of the language in MPS, but I didn t find much. Is this all there is? Where s the magic? [Customer]

57 DSLs and Agile is in Conflict. 4 Project 1 Language Development Leading LWBs are so productive, you can literally sit with the domain experts and interactively prototype languages (and then clean up later) I ve looked at the implementation of the language in MPS, but I didn t find much. Is this all there is? Where s the magic? [Customer] Analyze Build Try out Cleanup Stabilize 1 hour Validate 1 to 3 days

58 Skills?

59 Organizations do not have the necessary skills. True. But... Big AI Data R E S T

60 Organizations do not have the necessary skills. True. But... Big AI Data R E S T So built it. Evolve. Hire. Buy.

61 Separation of concerns is key to avoid the legacy trap DSLs can isolate business logic completely from technical concerns DSLs can help integrate domain experts with communication/review or even coding Language Workbenches enable DSLs and MPS is by far the best one! Migrating to a new LWB is feasible b/c semantics of all models are known, by definition.