We're using ILOG For DotNet and have a deployed pilot project.
Here's a summary of our immature Rules Architecture:
- All data-access done outside of rules.
- Rules are deployed the same way as code (source control, release process, yada yada).
- Projects (services) that use Rules have a reference to
ILOG.Rules.dll and new-up RuleEngines via a custom pooling class. RuleEngines are pooled because it is expensive to bind a RuleSet to a RuleEngine.
- Almost all rules are written to expect Assert'd objects, rather than RuleFlow parameters.
- Since the rules run in the same memory space, instances that are modified by the rules are the same instances in the program - which is immediate propagation of state.
- Almost all rules are run via RuleFlow (even if it is a single RuleStep in the RuleFlow).
We're looking at RuleExecutionServer as an hosting platform as well as RuleTeamServerForSharePoint to be the host for rules source. Eventually, we will have Rules deployed to production outside of the code release process.
The primary obstacle in all our Rule endeavors is Modeling and Rule Authoring skillsets.
This snippet compiles the Rules into fast executable code (using Expression trees) and does not need any complicated switch statements:
(Edit : full working example with generic method)
public Func<User, bool> CompileRule(Rule r)
{
var paramUser = Expression.Parameter(typeof(User));
Expression expr = BuildExpr(r, paramUser);
// build a lambda function User->bool and compile it
return Expression.Lambda<Func<User, bool>>(expr, paramUser).Compile();
}
You can then write:
List<Rule> rules = new List<Rule> {
new Rule ("Age", "GreaterThan", "21"),
new Rule ( "Name", "Equal", "John"),
new Rule ( "Tags", "Contains", "C#" )
};
// compile the rules once
var compiledRules = rules.Select(r => CompileRule(r)).ToList();
public bool MatchesAllRules(User user)
{
return compiledRules.All(rule => rule(user));
}
Here is the implementation of BuildExpr:
Expression BuildExpr(Rule r, ParameterExpression param)
{
var left = MemberExpression.Property(param, r.MemberName);
var tProp = typeof(User).GetProperty(r.MemberName).PropertyType;
ExpressionType tBinary;
// is the operator a known .NET operator?
if (ExpressionType.TryParse(r.Operator, out tBinary)) {
var right = Expression.Constant(Convert.ChangeType(r.TargetValue, tProp));
// use a binary operation, e.g. 'Equal' -> 'u.Age == 21'
return Expression.MakeBinary(tBinary, left, right);
} else {
var method = tProp.GetMethod(r.Operator);
var tParam = method.GetParameters()[0].ParameterType;
var right = Expression.Constant(Convert.ChangeType(r.TargetValue, tParam));
// use a method call, e.g. 'Contains' -> 'u.Tags.Contains(some_tag)'
return Expression.Call(left, method, right);
}
}
Note that I used 'GreaterThan' instead of 'greater_than' etc. - this is because 'GreaterThan' is the .NET name for the operator, therefore we don't need any extra mapping.
If you need custom names you can build a very simple dictionary and just translate all operators before compiling the rules:
var nameMap = new Dictionary<string, string> {
{ "greater_than", "GreaterThan" },
{ "hasAtLeastOne", "Contains" }
};
The code uses the type User for simplicity. You can replace User with a generic type T to have a generic Rule compiler for any types of objects. Also, the code should handle errors, like unknown operator name.
Note that generating code on the fly was possible even before the Expression trees API was introduced, using Reflection.Emit. The method LambdaExpression.Compile() uses Reflection.Emit under the covers (you can see this using ILSpy).
Best Answer
Most rule engines that I have seen are viewed as a black box by system code. If I were to build a domain model, I would probably want certain business rules to be intrinsic to the domain model, e.g. business rules that tell me when an object has invalid values. This allows multiple systems to share the domain model without duplicating business logic. I could have each system use the same rule service to validate my domain model, but this appears to weaken my domain model (as was pointed out in the question). Why? Because instead of consistently enforcing my business rules across all systems at all times, I am relying on system programmers to determine when the business rules should be enforced (by calling the rule service). This may not be a problem if the domain model comes to you completely populated, but can be problematic if you're dealing with a user interface or system that changes values in the domain model over its lifetime.
There is another class of business rules: decision making. For example, an insurance company may need to classify the risk of underwriting an applicant and arrive at a premium. You could place these types of business rules in your domain model, but a centralized decision for scenarios like this are usually desirable and, actually, fit quite well into a service-oriented architecture. This does beg the question of why a rule engine and not system code. The place where a rule engine may be a better choice is where business rules responsible for the decision change over time (as some other answers have pointed out).
Rule engines usually allow you to change rules without restarting your system or deploying new executable code (regardless of what promises you receive from a vendor, do make sure you test your changes in a non-production environment because, even if the rule engine is flawless, humans are still changing the rules). If you're thinking, "I can do that by using a database to store values that change", you're right. A rule engine is not a magical box that does something new . It is intended to be a tool that provides a higher level of abstraction so you can focus less on reinventing the wheel. Many vendors take this a step further by letting you create templates so that business users can fill in the blanks instead of learning a rule language.
One parting caution about templates: templates can never take less time than writing a rule without a template because the template must, at the bare minimum, describe the rule. Plan for a higher initial cost (the same as if you were to build a system that used a database to store values that change vs. writing the rules in directly in system code) - the ROI is because you save on future maintenance of system code.