Does drools have any validate utility that will scan a knowledge base? - drools

Question

If any incorrect rule pushed to knowledgebase. Can we scan the knowledgeBase to filter out the bad rules, which may create problem later?

Answer 1

Not only does this not exist, but it's not possible.
Simple syntax errors
The really easy problems -- straight up syntax errors -- are caught at runtime when the Drools rules are compiled. The rules themselves won't be loaded at all, and the Kie classes will throw an exception.
So, for example, let's say you were in a rush and you forgot the "when" keyword:
rule "Example 1"
salience 9
$s: SomeObject( foo == "bar" )
then
$s.doSomething()
end
This will be caught quickly at the time your rules are loaded. Other syntax errors like missing imports will be caught as well.
If you're following unit testing best practices, this will be caught at the unit testing stage, which -- given proper CI practices -- should keep the bad rules from being merged into your main code line.
If you're loading your rules from a Maven repository as a kjar, you'll likely want to have some sort of testing harness before publishing that kjar so that you don't end up with a situation where your service pulls new rules and ends up with a nonfunctional artifact.
Logical errors
Unlike syntax errors which can be caught early, logical errors really can't. The problem boils down to the fact that Drools is a framework for business logic -- it doesn't actually understand your business logic. And it can't, and it shouldn't need to.
If you write bad rules that put yourself into a bad situation, Drools has no way of actually identifying this because it doesn't understand your business needs.
Consider the following rules:
rule "A"
when
$f: Foo( value == 0 )
then
$f.setValue(100);
update($f);
end
rule "B"
when
$f: Foo( value > 10 )
then
$f.setValue(0);
update($f);
end
Assuming your initial input is Foo(value: 50), rule B will fire, setting value to 0. Then rule A will fire, setting value to 100. Then rule B will fire, setting value to 0. And so on, forever, until you kill the process manually.
This simple infinite loop is poor rule design, but it's only a bug because of your data characteristics. The above example is obvious and contrived, but that's because I'm just using it as an example. In practice, I once saw a set of 27 rules that triggered in a particular order given a very specific input and looped like that -- it took me a whole week to track down while manually tracing transactions through a customer system.
Drools can't "know" that this will cause an infinite loop because it doesn't understand your business rules or data. In the above Foo example with rules A and B, you could say "well obviously Drools could see that it's setting value in a way that'll trigger rules in a loop given the 'update' call" -- but you're making assumptions. What if I told you that there are situations where these rules don't loop? I never showed you the Foo model, maybe setValue has side effects.
The way you'd catch these is by actually validating your business logic. I usually start with unit tests and treat it as if I'm testing an "if" condition -- check the boundaries, check the edge cases, check the good value, check an obviously bad value, etc. Then I add end-to-end tests passing in real (sanitized) inputs collected from production -- the most common inputs, the weird inputs, the ones that have shown up in previous bug reports, etc.
And because that's not enough and you really need an understanding of all rules, we have internal style guidelines around DRL design to keep something like the above looping examples from happening. (We don't permit update, for example. There are specific rules around salience and retract as well.)
But built-in validation for this? Not actually possible; you need to do your own due diligence just like you would for your code.