2,804 research outputs found
Abstract verification and debugging of constraint logic programs
The technique of Abstract Interpretation [13] has allowed the development of sophisticated program analyses which are provably correct and practical. The semantic approximations produced by such analyses have been traditionally applied to optimization during program compilation. However, recently, novel and promising applications of semantic approximations have been proposed in the more general context of program verification and debugging [3],[10],[7]
CHR Grammars
A grammar formalism based upon CHR is proposed analogously to the way
Definite Clause Grammars are defined and implemented on top of Prolog. These
grammars execute as robust bottom-up parsers with an inherent treatment of
ambiguity and a high flexibility to model various linguistic phenomena. The
formalism extends previous logic programming based grammars with a form of
context-sensitive rules and the possibility to include extra-grammatical
hypotheses in both head and body of grammar rules. Among the applications are
straightforward implementations of Assumption Grammars and abduction under
integrity constraints for language analysis. CHR grammars appear as a powerful
tool for specification and implementation of language processors and may be
proposed as a new standard for bottom-up grammars in logic programming.
To appear in Theory and Practice of Logic Programming (TPLP), 2005Comment: 36 pp. To appear in TPLP, 200
Using global analysis, partial specifications, and an extensible assertion language for program validation and debugging
We discuss a framework for the application of abstract interpretation as an aid during program development, rather than in the more traditional application of program optimization. Program validation and detection of errors is first performed statically by comparing (partial) specifications written in terms of assertions against information obtained from (global) static analysis of the program. The results of this process are expressed in the user assertion language. Assertions (or parts of assertions) which cannot be checked statically are translated into run-time tests. The framework allows the use of assertions to be optional. It also allows using very general properties in assertions, beyond the predefined set understandable by the static analyzer and including properties defined by user programs. We also report briefly on an implementation of the framework. The resulting tool generates and checks assertions for Prolog, CLP(R), and CHIP/CLP(fd) programs, and integrates compile-time and run-time checking in a uniform way. The tool allows using properties such as types, modes, non-failure, determinacy,
and computational cost, and can treat modules separately, performing incremental analysis
Description and Optimization of Abstract Machines in a Dialect of Prolog
In order to achieve competitive performance, abstract machines for Prolog and
related languages end up being large and intricate, and incorporate
sophisticated optimizations, both at the design and at the implementation
levels. At the same time, efficiency considerations make it necessary to use
low-level languages in their implementation. This makes them laborious to code,
optimize, and, especially, maintain and extend. Writing the abstract machine
(and ancillary code) in a higher-level language can help tame this inherent
complexity. We show how the semantics of most basic components of an efficient
virtual machine for Prolog can be described using (a variant of) Prolog. These
descriptions are then compiled to C and assembled to build a complete bytecode
emulator. Thanks to the high level of the language used and its closeness to
Prolog, the abstract machine description can be manipulated using standard
Prolog compilation and optimization techniques with relative ease. We also show
how, by applying program transformations selectively, we obtain abstract
machine implementations whose performance can match and even exceed that of
state-of-the-art, highly-tuned, hand-crafted emulators.Comment: 56 pages, 46 figures, 5 tables, To appear in Theory and Practice of
Logic Programming (TPLP
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