Completeness analysis

The completeness analysis mechanism analyzes the condition part of each rule in a ruleset and detects whether there are cases where no rule applies.

Completeness analysis is a mechanism for checking whether there are rules missing from a set of rules.

A ruleset is considered complete if for any possible case at least one rule applies.

You run completeness analysis for the following purposes:

Check whether a ruleset is complete.
Obtain a report of the missing rules.
Add the missing rules to the ruleset.

For more information, see Analyzing a rule project and Generating reports from BIRT templates.

Completeness mechanism

The completeness mechanism analyzes the condition part of each rule in a ruleset and detects whether there are cases where no rule applies.

To check that a ruleset is complete, the completeness mechanism proceeds as follows to identify the cases that are missing:

If the rule project contains a ruleflow, the completeness mechanism analyzes the ruleflow task by task, to check that each rule task is complete.

For example, if a rule is missing in several rule tasks, the report lists the rule tasks where the rule is missing.
If the rule project does not contain any ruleflow, the completeness mechanism takes into account all the rules in the project.

Note:
A ruleflow must contain at least one rule task.

Example of completeness analysis

In the following example, the ruleset is composed of five rules that define the customer and that set the category of the customer to Silver, Platinum, or Gold.

Rule 1

if 
	the value of the customer is at least 500 and the value of the customer is less than 1000
then
	set the category of the customer to "Silver";

Rule 2

if 
	the age of the customer is at least 65 and the value of the customer is less than 500
then 
	set the category of the customer to "Platinum";

Rule 3

if 
	the value of the customer is at least 1000 and the value of the customer is less than 1500
then
	set the category of the customer to "Gold";

Rule 4

if 
	the value of the customer is at least 1500
then
	set the category of the customer to "Platinum";

Rule 5

if 
	the value of the customer is less than 500 and the age of the customer is less than 50
then
	set the category of the customer to "Platinum";

Ruleset completeness analysis detects that no rule applied in the case where the customer is between 50 and 65 and has a value of less than 500.

This missing case is presented as a rule skeleton that you can use to create the missing rule:

definitions 
     set  'Customer1'  to  a customer  ; 
 if 
     the value of  Customer1  is less than  500  
    and  the age of  Customer1  is less than  65  
    and  the age of  Customer1  is at least  50  
 then 

<action>

Missing rules

If completeness analysis shows that your ruleset is not complete, it proposes additional rules to complete the ruleset. These new rules are skeleton rules. You must edit the missing rule to define the action to be performed.

The completeness mechanism analyzes the conditions of each rule in the ruleset to define the set of conditions for the proposed rule. If the rules match a Customer object but test different attributes, for example age, value, and shopping cart, the set of conditions in the proposed rule takes into account the attributes tested in the analyzed rules. Therefore, the condition part in the suggested rule might appear complex and include many condition statements. It can be simplified to reflect a more natural way of expressing the rule conditions.

Note:

The analysis is based on the objects used in the existing rules and that match the working memory. For more information, see Working memory.

In the following example, the suggested rule tests the value and the age attributes. You can simplify the rule by removing either condition.

Example

If completeness analysis proposes the following rule:

definitions 
     set  'Customer1'  to  a customer  ; 
 if 
     the value of  Customer1  is less than  500  
    and  the age of  Customer1  is less than  65  
    and  the age of  Customer1  is at least  50  
 then 

<action>

you can remove the condition on the age of the customer, and keep only the condition on the value:

definitions 
     set  'Customer1'  to  a customer  ; 
 if 
     the value of  Customer1  is less than  500  
 then 

<action>

If the ruleset contains only action rules, the proposed missing rules are verbalized. However, if the ruleset includes technical rules, decision tables, or decision trees, or if there is too little information on verbalization, the missing rules are presented in IRL.

Note:

The completeness mechanism might generate rules that overlap. You can modify the conditions of these rules.

Performance

The performance of completeness analysis depends on several factors such as the number of rules in the ruleset, the number of rule tasks, and most importantly the number of missing rules.

To improve performance and reduce execution time of completeness analysis, set a limit to the number of missing rules to propose. For example, limit the results to ten missing rules. Once you have integrated the first ten missing rules, run completeness analysis again to identify other missing rules.