Introduction to specification pattern

Lalit Kale Lalit Kale
design-patternsarchitecturesoftware-design

Business logic has a way of growing into something unrecognisable. What starts as a clean conditional check becomes a twelve-level nested if block over six months, maintained by three different people who each added their own layer of assumptions. You can still run the code. You just can’t reason about it anymore.

The Specification Pattern offers a way out. Rooted in Domain-Driven Design and first articulated by Eric Evans and Martin Fowler, it treats business rules as first-class objects—composable, testable, and named in terms the domain actually uses.

The problem with naked conditionals

Consider a discount-eligibility check. An order qualifies for a discount if it’s domestic, exceeds a certain value, has stock available, and is non-taxable. In code, that typically looks like:

public bool HasDiscount()
{
    if (this.ShippingAddress.Country == "IN" &&
        this.TotalAmount > 5000 &&
        this.StockLevel > 100 &&
        !this.IsTaxable)
    {
        return true;
    }
    return false;
}

This works. Until the tax rules change. Or “domestic” starts meaning something different. Or someone adds a promotional override and forgets to check one of the other conditions. The logic is buried, anonymous, and fragile.

What the pattern does

The Specification Pattern extracts each rule into its own class with a single responsibility: answering whether a candidate object satisfies it. You then compose specifications using And, Or, and Not combinators. The discount check becomes:

public bool HasDiscountWithSpecification()
{
    var spec = new DiscountSpecification();
    return spec.IsSatisfiedBy(this);
}

And the DiscountSpecification makes the rules explicit:

public override bool IsSatisfiedBy(Order candidate)
{
    return domesticOrderSpec
        .And(highValueSpec)
        .And(highStockSpec)
        .And(taxableSpec.Not())
        .IsSatisfiedBy(candidate);
}

Each component specification is independently named, independently testable, and independently changeable. When the tax rules shift, you touch taxableSpec. Nothing else moves.

Fluent interfaces and method chaining

The pattern pairs naturally with fluent interfaces. Method chaining—where each call returns the same object type—gives you a syntax that reads almost like a policy statement. That’s not just aesthetics; it reduces the cognitive distance between the business requirement and the code. A product owner reading domesticOrderSpec.And(highValueSpec) can follow the logic. They can’t follow twelve nested conditionals.

Where it fits

Specifications shine wherever you need to select, validate, or filter objects by rules that might change:

  • Search and filtering criteria in query layers
  • Validation in domain models
  • Object selection for batch processing
  • Unit test predicates
  • Complex parsing conditions

The pattern isn’t a universal hammer. For truly simple checks that will never compose or change, a plain method is fine. But as soon as rules start combining, or teams start debating what “eligible” means in different contexts, a specification makes the conversation concrete.

The deeper value

What makes this pattern worth learning isn’t the syntax—it’s the design discipline it enforces. It pushes you to name your rules. Named rules can be discussed, challenged, and refined. Anonymous conditions buried in method bodies can only be decoded. That difference matters more than you might expect when requirements shift under pressure.

Sample code is available on GitHub for reference.