Precise Goal-Independent Abstract Interpretation of Constraint Logic Programs

AbstractWe present a goal-independent abstract interpretation framework for pure constraint logic programs, and prove the sufficiency of a set of conditions for abstract domains to ensure that the analysis will never lose precision. Along the way, we formally define pure constraint logic programming systems, give a formal semantics that is independent of the actual constraint domain, and formally define the maximally precise abstraction of a pure constraint logic program

Lower bound cost estimation for logic programs

It is generally recognized that information about the runtime cost of computations can be useful for a variety of applications, including program transformation, granularity control during parallel execution, and query optimization in deductive databases. Most of the work to date on compile-time cost estimation of logic programs has focused on the estimation of upper bounds on costs. However, in many applications, such as parallel implementations on distributed-memory machines, one would prefer to work with lower bounds instead. The problem with estimating lower bounds is that in general, it is necessary to account for the possibility of failure of head unification, leading to a trivial lower bound of 0. In this paper, we show how, given type and mode information about procedures in a logic program, it is possible to (semi-automatically) derive nontrivial lower bounds on their computational costs. We also discuss the cost analysis for the special and frequent case of divide-and-conquer programs and show how —as a pragmatic short-term solution —it may be possible to obtain useful results simply by identifying and treating divide-and-conquer programs specially

Generalized Semantics and Abstract Interpretation for Constraint Logic Programs

We present simple and powerful generalized algebraic semantics for constraint logic programs that are parameterized with respect to the underlying constraint system. The idea is to abstract away from standard semantic objects by focusing on the general properties of any\u2014possibly nonstandard\u2014semantic definition. In constraint logic programming, this corresponds to a suitable definition of the constraint system supporting the semantic definition. An algebraic structure is introduced to formalize the notion of a constraint system, thus making classical mathematical results applicable. Both top-down and bottom-up semantics are considered. Nonstandard semantics for constraint logic programs can then be formally specified using the same techniques used to define standard semantics. Different nonstandard semantics for constraint logic languages can be specified in this framework. In particular, abstract interpretation of constraint logic programs can be viewed as an instance of the constraint logic programming framework itself