Products
Decision Tables

Generally, tables are a convenient way of organising, storing and displaying business rules. We have all seen and used many forms of informational tables such as airline schedules, price lists, and product feature charts. Decision Tables extend the table concept by providing a detailed, concise, easily read, highly maintainable and logically organised way of representing and querying information and relationships.



Like all Common Knowledge Rule Extenders, the Decision Table Extender seamlessly integrates with Common Knowledge Studio and the Common Knowledge Rules Engine and can be easily combined with other business rule formats to create powerful solutions to complex business rule problems.

Overview of Capabilities
Common Knowledge Decision Tables provide a range of capabilities that allow you to create structured, readable and accessible representations of your business rules.
  • Interactive Designer - Visual, interactive designer provides an intuitive tabular format for representing business rules
  • Interactive Execution - Standalone execution and validation of Decision Tables entirely within Common Knowledge Studio
  • Explanations - Add explanations in the form of Reason Strings to any rule in a Decision Table
  • Documentation - Add custom information to your rules which will be included in auto-generated documentation
  • Evaluation Modes - Choice of evaluation and execution modes for the Decision Table including AND, OR and XOR


Feature List
Common Knowledge Decision Tables incorporate an ever-growing set of features that assist you during the design, authoring, execution and testing of your table-based business rules. Features include:
  • Nested Rules - Embed execution of any other Rule Extender within Decision Table conditions and actions
  • Complex Expressions - Specify complex expressions as the conditions and actions within a Decision Table to perform a range of operations including comparison (set, boolean and arithmetic), maths, statistics, string handling, financial, and date & time
  • Interactive Debugger - Interactively debug your Decision Tables using breakpoints, stack tracing and expression evaluation
  • Multiple Actions - Define an arbitrary number of complex actions to be performed for each rule
  • Rule Activation - Colour-highlighting of evaluated conditions and performed actions as Decision Tables are executed
  • Cell Formatting - Auto-size Decision Table columns and rows for easy table formatting
  • Cell Merging - Easy auto-merge of common-valued table entries and expressions to provide a powerful aggregated view of your rules
  • Efficient Evaluation - Optional short-circuit execution of rules expressions to ensure maximum performance
  • Single & Multiple Rule Activation - Limit rule activation to a single rule or allow multiple rules to concurrently activate as conditions are satisified
  • Evaluation Mode - Choose how Decision Table conditions are evaluated from AND, OR, and XOR
  • Execution Mode - Choose how Decision Tables are executed from Sequential or Lookup (very fast for sortable conditions)
  • Parameters and Return Values - Pass parameters directly to Decision Tables and have Decision Tables return a result


What's New in Version 3.1
The following features are new to version 3.1 of Common Knowledge and augment the existing capabilities of Decision Tables to represent your business rules:
  • Print & Preview - Print and Print Preview of Decision Tables
  • Undo Redo - Full undo/redo of any Decision Table edits
  • Multiple Lines - Wrap-around text within Decision Table cells
  • Fixed Space Fonts - Optionally display text in Decision Tables using a fixed space font
  • Search Replace - Full Search/Replace throughout all Decision Table elements






Video Video Demo
View an online video demonstrating how easy it is to build and test Decision Tables using Common Knowledge Studio.

Rete Rules
Read how the new Rete Rules Rule Extender can be used to represent business rules in an intuitive and declarative manner and to evaluate those business rules using a forward chaining inference mechanism based on the Rete algorithm.


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