Skip to main contentSkip to search
Powered by Zoomin Software. For more details please contactZoomin
Progress DocumentationProgress Documentation
Progress Documentation
  • Home
  • Home
  • EnglishČeštinaDeutsch (Germany)Español (Spain)Français (France)Italiano (Italy)Português (Brasil)日本語Русский (Russia)中文 (简体) (China)中文 (繁體, 台灣) (Taiwan)ar-AR
  • Login

Corticon.js Rule Modeling

Techniques that refine rule testing

Save PDF
Save selected topicSave selected topic and subtopicsSave all topics
Share
Share to emailCopy topic URL
Print
Table of Contents
  • Introduction to Corticon.js rule modeling
  • Create the Vocabulary
    • Generate a Vocabulary
      • Use JSON to generate a vocabulary
      • Use JSON Schema to generate a vocabulary
    • Build a Vocabulary by hand
    • Extend a Vocabulary
      • Enumerations
        • How enumeration labels and values behave
        • Enumerations defined in the Vocabulary
        • Use enumerated Custom Data Types in Rulesheets
        • Use enumerated Custom Data Types in Ruletests
      • Domains
        • Domains in a Rulesheet
        • Domains in a Ruletest
  • Rule scope and context
    • Rule scope
    • Aliases
    • Scope and perspectives in the vocabulary tree
      • How to use roles
  • Rule writing techniques
    • How to generate rules with the AI Assistant
    • How to work with rules and filters in natural language
    • Filters versus conditions
    • Qualify rules with ranges and lists
      • Ranges and lists in conditions and filters
        • Value ranges in condition and filter expressions
        • Value lists in condition and filter expressions
      • Ranges and value sets in condition cells
        • Boolean condition versus values set
          • Exclusionary syntax
          • How to use other in condition cells
        • Numeric value ranges in conditions
        • String value ranges in condition cells
        • Value sets in condition cells
        • Variables as condition cell values
        • DateTime value ranges in condition cells
        • Inclusive and exclusive ranges
        • Value ranges that overlap
        • Alternatives to value ranges
    • How to use standard Boolean constructions
    • How to embed attributes in posted rule statements
    • How to include apostrophes in strings
    • How to initialize null attributes
    • How to handle nulls in compare operations
  • Collections
    • How Corticon Studio handles collections
    • How to visualize collections
    • A basic collection operator
    • How to filter collections
    • How to use aliases to represent collections
    • Advanced collection sorting syntax
    • Using sorts to find the first or last in grandchild collections
    • Singletons
    • Special collection operators
      • Universal quantifier
      • Existential quantifier
      • Another example using the existential quantifier
  • Rules containing calculations and equations
    • Operator precedence and order of evaluation
    • Data type compatibility and casting
      • Data type of an expression
      • Defeating the parser
      • Manipulating JS datatypes with casting operators
    • Supported uses of calculation expressions
      • Calculation as a comparison in a precondition
      • Calculation as an assignment in a noncondition
      • Calculation as a comparison in a condition
      • Calculation as an assignment in an action
    • Unsupported uses of calculation expressions
  • Rule dependency in chaining
  • Filters
    • Full filters
    • Limiting filters
    • Filters that use OR
    • What is a precondition
      • Summary of filter and preconditions behaviors
      • Performance implications of the precondition behavior
    • How to use collection operators in a filter
      • Location matters
      • Multiple filters on collections
      • Aggregations in collections
  • How to recognize and model parameterized rules
    • Parameterized rule where a specific attribute is a variable or parameter within a general business rule
    • Parameterized rule where a specific business rule is a parameter within a generic business rule
  • Logical analysis and optimization
    • Ask the AI Assistant for help
    • Test, validate, and optimize your rules
      • Generate Ruletests
      • Scenario testing
      • Rulesheet analysis and optimization
    • Traditional methods of analyzing logic
      • Flowcharts
      • Test suites
    • Validate and test Rulesheets in Corticon Studio
      • How to expand rules
      • The conflict checker
      • The completeness checker
        • Automatically determine the complete values set
        • Automatically compress the new columns
        • Handle limitations of the completeness checker
        • Let the expansion tool work for you with tabular rules
        • Memory management
      • Logical loop detection
    • Test rule scenarios in the Ruletest Expected panel
      • How to navigate in Ruletest Expected comparison results
      • Review test results when using the Expected panel
        • Output results match expected exactly
        • Different values output than expected
        • Fewer values output than expected
        • More values output than expected
        • All Expected panel problems
      • Techniques that refine rule testing
        • Set selected attributes to ignore validation
        • Use key attributes to improve difference detection in Ruletests
        • Numerical equivalence
    • How to optimize Rulesheets
      • The compress tool
      • How to produce characteristic Rulesheet patterns
      • Compression creates subrule redundancy
      • Effect of compression on Decision Service performance
    • Precise location of problem markers in editors
  • Advanced Ruleflow techniques and tools
    • How to use a Ruleflow in another Ruleflow
    • Conditional branching in Ruleflows
      • Example of branching based on a Boolean
      • Example of branching based on an enumeration
      • Logical analysis of a branch container
      • How branches in a Ruleflow are processed
    • How to generate Ruleflow dependency graphs
  • Troubleshooting Corticon.js Studio problems
    • Where did the problem occur
    • Use Corticon Studio to reproduce the behavior
      • Analyze Ruletest results
      • Trace rule execution
      • Use rule messages to expose values
      • Identify the breakpoint
      • At the breakpoint
        • No results
        • Incorrect results in Studio
    • How to compare and report on Rulesheet differences
  • Customize Corticon.js Studio
Table of Contents

Techniques that refine rule testing

Save PDF
Save selected topicSave selected topic and subtopicsSave all topics
Share
Share to emailCopy topic URL
Print
  • Last Updated: January 27, 2025
  • 1 minute read
    • Corticon.js
    • Documentation

The following settings help you tune the results of comparing the output data and expected data so that irrelevant errors are minimized:

  • Set selected attributes to ignore validation
  • Use key attributes to improve difference detection in Ruletests
  • Set how whitespace is handled
  • Numerical equivalence
Contents
  1. Set selected attributes to ignore validation
  2. Use key attributes to improve difference detection in Ruletests
  3. Numerical equivalence
Previous topic: Review test results when using the Expected panel
TitleResults for “How to create a CRG?”Also Available inAlert