DeAL TutorialRules
Rules Defined
Definitions- A rule is an expression of the form:
A B1, B2, ... , Bn.
where A and B1 through Bn are predicates. A is called the head of the rule and the expression to the right of the '''' is called the body.
part_cost1(X, Y) <- part_cost(top_tube, X, Y, Z).
- A rule that contains no variables is a ground rule or an
instantiated rule.
run_for_your_life <- physician(`Dr. Frankenstein`).
- A rule with no body is a unit clause.
distance(City, City, 0).
- A ground unit clause is fact.
distance(`Austin`, `Waco`, 110).
Facts are normally stored in the database (but facts occasionally occur in the program.)
Semantics of Rules
UnionThe two rules,
A <- B. A <- C.
are logically equivalent to
(B A) & (C A)
which is
(B C) A
.
We will refer to a predicate such as A, which is the result of the union of two (or more) rules, as a union predicate.
InterpretationA rule,
A B1, B2, ... , Bn.
is logically equivalent to: the conjunction of B1, B2, ... , Bn implies A .
When the truth value of each predicate in the body is TRUE, the head predicate is also TRUE.
Bottom-Up Evaluation
(a) h1(X,Y) <- p(X,Y).
(b) h2(X) <- h1(X,Y).
(c) p(X,Y) <- b(X,Y).
b(1,2).
b(2,4).
- Rule (c) is the only one whose body contains only a base
predicate. Matching the body with the data produces
{p(1,2),p(2,4)} as new facts.
The partial result is the set {b(1,2),b(2,4),p(1,2),p(2,4)} - Now rule (a) can be evaluated using the results of step (1).
The result is {b(1,2),b(2,4),p(1,2),p(2,4),h1(1,2),h1(2,4)}. - Rule (b) is evaluated using the result of step (2).
The result is {b(1,2),b(2,4),p(1,2),p(2,4),h1(1,2),h1(2,4),h2(1),h2(2)}. - No more results are produced.
Equality Predicate (.deal | .fac)
Say that t(X, Y, Z) is a base predicate; X,Y,Z are integers. Then, sums(X) <- t(X,Y,Z), X = Y + Z. returns all a,b,c such that the tuple t(a,b,c) appears in t and a = b + c. The equality serves as a test.
t(3,2,1). t(5,2,3). t(8,4,3). t(7,4,3). t(7,3,4). export sums(X). query sums(X).
returns {sums(3), sums(5), sums(7)}
export sums($X). query sums(5).
returns TRUE, and
query sums(8).
returns FALSE.
Equation Solving
t1(X, Z) is a base predicate; X, Z are integers.
sums1(Y) <- t1(X, Z), X = Y*Y + Z.
Fails at compile time! Although X, Z are known, the system cannot solve the equation for Y.
(DeAL will however solve simple linear equations.)
Equality Predicate Operating as Single Assignment
t1(X, Z) is a base predicate, X, Z are integers.
sums2(Y) <- t1(X, Z), Y = X + Z. export sums2(X).
compiles correctly! In this form the equality is used as a single assignment.
t1(1,2). t1(3,5). query sums2(X).
returns {sums2(3), sums2(8)}.
export sums2($X). query sums2(3).
returns TRUE and
query sums2(4).
returns FALSE.
Safety
Safety is a program property that ensures that the values of program variables can be effectively computed.
Safety thus depend on the execution used (e.g., bottom-up, top-down, or a combination of the two).
- For the bottom-up execution, the safe predicates are those that are derivable from from database relations (possibly using arithmetic and equality assignments).
- For top-down execution, safety also depends from the binding pattern of the export.
- Assume that goals in the rules are evaluated from left to right. Then the re-ordering of the goals could make a safe rule unsafe or vice-versa
- The safe binding patterns for equality and inequality predicates are summarized in the following table:
Built-in Predicates for Terms
Predicate name and Arguments |
Safe Binding Patterns |
Comments |
L = R | $L, $R | L, R arbitrary terms |
L, $R | L is a variable | |
$L, R | R is a variable | |
L ~= R | $L, $R | |
L > R | $L, $R | |
L < R | $L, $R | |
L <= R | $L, $R | |
L >= R | $L, $R |
Example: Safety
good_salary(X) <- X > 80000.
But,
export good_salary(X).
does not compile! The query form is unsafe. However,
export good_salary($X).
is safe. query good_salary(100,000).
is TRUE. query good_salary(50,000).
is FALSE.
In DeAL the bound values in the exports are always propagated down to the defining predicates---if these are not recursive. For recursive predicates the situation is more complex and will be discussed later.
Example: Safety - A Modified Example
well_paid_employee(Name, Salary) <- employee(Name, Salary), Salary > 80000.
Now export well_paid_employee(Name, Salary).
is safe.