Algebra Overview

Algebra uses type classes to represent algebraic structures. You can use these type classes to represent the abstract capabilities (and requirements) you want generic parameters to possess.

This section will explain the structures available.

algebraic properties and terminology

We will be talking about properties like associativity and commutativity. Here is a quick explanation of what those properties mean:

Though these properties are illustrated with symbolic operators, they work equally-well with functions. When you see a ⊕ b that is equivalent to f(a, b): ⊕ is an infix representation of the binary function f, and a and b are values (of some type A).

Similarly, when you see ¬a that is equivalent to g(a): ¬ is a prefix representation of the unary function g, and a is a value (of some type A).

basic algebraic structures

The most basic structures can be found in the algebra package. They all implement a method called combine, which is associative. The identity element (if present) will be called empty, and the inverse method (if present) will be called inverse.

(For a description of what each column means, see §algebraic properties and terminology.)

ring-like structures

The algebra.ring package contains more sophisticated structures which combine an additive operation (called plus) and a multiplicative operation (called times). Additive identity and inverses will be called zero and negate (respectively); multiplicative identity and inverses will be called one and reciprocal (respectively).

All ring-like structures are associative for both + and *, have commutative +, and have a zero element (an identity for +).

(For a description of what the terminology in each column means, see §algebraic properties and terminology.)

lattice-like structures

The algebra.lattice package contains more structures that can be somewhat ring-like. Rather than plus and times we have meet and join both of which are always associative, commutative and idempotent, and as such each can be viewed as a semilattice. Meet can be thought of as the greatest lower bound of two items while join can be thought of as the least upper bound between two items.

When zero is present, join(a, zero) = a. When one is present meet(a, one) = a.

When meet and join are both present, they obey the absorption law:

• meet(a, join(a, b)) = join(a, meet(a, b)) = a

Sometimes meet and join distribute, we say it is distributive in this case:

• meet(a, join(b, c)) = join(meet(a, b), meet(a, c))

• join(a, meet(b, c)) = meet(join(a, b), join(a, c))

Sometimes an additional binary operation imp (for impliciation, also written as →, meet written as ∧) is present. Implication obeys the following laws:

• a → a = 1

• a ∧ (a → b) = a ∧ b

• b ∧ (a → b) = b

• a → (b ∧ c) = (a → b) ∧ (a → c)

The law of the excluded middle can be expressed as:

• (a ∨ (a → 0)) = 1

Note that a BoundedDistributiveLattice gives you a CommutativeRig, but not the other way around: rigs aren't distributive with a + (b * c) = (a + b) * (a + c).

Also, a Bool gives rise to a BoolRing, since each element can be defined as its own negation. Note, Bool's .asBoolRing is not an extension of the .asCommutativeRig method as the plus operations are defined differently.

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