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Prologa

Modeling decision tables. Prologa. Prologa. Katholieke Universiteit Leuven Department of Applied Economics. LIRIS Leuven Institute for Research on Information Systems. Prologa (PROcedural Logic Analyzer). Computer supported Design Validation Manipulation Use, and

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Prologa

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  1. Modeling decision tables Prologa

  2. Prologa

  3. Katholieke Universiteit Leuven Department ofApplied Economics LIRIS Leuven Institute for Research on Information Systems

  4. Prologa (PROcedural Logic Analyzer) Computer supported • Design • Validation • Manipulation • Use, and • Transformation of Decision tables

  5. Importance and applications 1. Conditional logic • systems analysis • business rules • software engineering • procedures, texts, regulations • test case specifications

  6. Importance and applications 2. Knowledge-based systems • Knowledge acquisition • Validation and verification of knowledge systems (consistency, completeness, correctness) • Implementation of decision logic

  7. PROcedural Logic Analyzer

  8. Emphasis on: • Interactive specification of decision logic • User friendly and automatic manipulations • Automatic verification and validation • Interfaces to various representations (trees, code, rules) • Optimizations

  9. Acquisition Modeling Implementation An integrated development approach

  10. Modeling Basic Modeling Process

  11. Basic modeling process • Start new table • Input conditions and actions • Input decision rules • Display table • Optimize table

  12. Start new table

  13. Basic modeling process • Start new table • Input conditions and actions • Input decision rules • Display table • Optimize table

  14. Conditions and actions • Detecting decision criteria, relevant • states and possible outcomes

  15. Action and condition input

  16. Basic modeling process • Start new table • Input conditions and actions • Input decision rules • Display table • Optimize table

  17. Decision rules Relations between decision criteria and actions to be be executed: • General rules, exceptions, ... • Based upon starting text, interview, examples, etc.

  18. Decision rules Action(s) IF Condition combination(s) Various refinements: • Generally if • If and only if • Always if • Only possible if • Impossible if • ...

  19. Decision rule input

  20. Basic modeling process • Start new table • Input conditions and actions • Input decision rules • Display table • Optimize table

  21. Table display

  22. Expanded table

  23. Verification & Validation Automatic checking for: • Completeness • Consistency • Correctness • Redundant conditions • Redundant actions • Redundant combinations

  24. Avoiding contradictions

  25. Verification report

  26. Various manipulations • Add, update, delete, reorder conditions and actions ==> immediately reflected in table • Table layout

  27. Basic modeling process • Start new table • Input conditions and actions • Input decision rules • Display table • Optimize table

  28. Various optimizations • Layout • Contraction • Optimal condition order • Optimal execution time • Optimal rules

  29. Contracted decision table

  30. Modeling Additional features

  31. Additional features • Fill by mouse • Table manipulation • Automatic verification • Optimal contraction • Action and condition dictionary • Table structures • Interface features • Consultation of tables

  32. Fill by mouse

  33. Fuzzy tables

  34. Import from MS Excel

  35. Import from MS Excel

  36. Decision Tree

  37. Export options

  38. Pascal generation

  39. COBOL generation

  40. AionDS table generation

  41. Optimal execution code

  42. Minimal rules

  43. Modeling Structures of decision tables

  44. Structures of decision tables

  45. Decision table modularization

  46. Verification between tables

  47. Consultation of the knowledge Consultation environment

  48. Tables (logic) Text, explanation multimedia Consultation mechanism Application

  49. Filling in criteria

  50. Result of the consultation

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