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Prolog as a Rule Engine

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Prolog as a Rule Engine

Prolog is a general-purpose logic programming language. With some work, you can turn it into your very own rules engine.

· AI Zone ·
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I was challenged by my team lead in my previous company to create a Java application module that will be integrated into our current POC project to act as a rule engine. The idea is to have a module that will prove if the given URL is malicious, benign, or suspicious given all the information pertaining to the URL such as registrant, IP location, URL pattern, etc.

I started the formal development given the business requirements and as I went through development trying to hard code all the conditions using if-else statements, I realized that the code I was writing was not going to be effective. Then, I asked myself, "What if there’s a sudden change in the condition that needs to be implemented?" The first thing that came to my mind is to externalized those conditions that can be written inside a file or config. Eventually, I stopped the development right then and there and thought of something that would address my problem.

I began searching the web and came to existing rule engine applications like Drools and JRules, but I was hesitant because I didn't know how these technologies work and I really wanted to create my own that would satisfy the requirements. I’m aware that I should not repeat myself (DRY principle) in doing things that are already there, but I wanted to put my idea to the challenge.


Eventually, I came to Prolog, a general-purpose logic programming language associated with artificial intelligence and computational linguistics. The program logic is expressed in terms of relations, represented as facts and rules.

Now let's try to give a brief explanation what "facts" and "rules" mean. I'll try to keep it simple so that we can get the idea of how we can use Prolog as a rule engine.


Clauses with empty bodies are called facts. An example of a fact is:



A rule is in the form of:

Head :- Body.

Let's try to create our three rules: malicious, benign, and suspicious.

We could say that a domain is malicious if it belongs to the registrant sample@domain.com.

malicious :- registrant.email("sample@domain.com").

We could say that a domain is benign if it does not belong to the registrant sample@domain.com. We use negation here. (We could add more to the body of our rule to increase our confidence in our rule)

benign :- not(registrant.email("sample@domain.com")),reputation.score(SCORE),SCORE>70.

We could say that a domain is suspicious if the domain is not malicious and not benign.

suspicious :- not(malicious),not(benign).

Now that we already have our facts and rules, we can now proceed.

I'm using the TuProlog IDE so that we can test our rules based on the facts given.

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You can view the source code here for your reference. 

P.S. Sorry for the coding — this was created during my second year in my IT career.

prolog ,rules engine ,ai ,tutorial

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