Memorias de investigación
Artículos en revistas:
Sized Type Analysis for Logic Programs (Technical Communication)
Año:2013

Áreas de investigación
  • Ciencias de la computación y tecnología informática

Datos
Descripción
We present a novel analysis for relating the sizes of terms and subterms occurring at di?erent argument positions in logic predicates. We extend and enrich the concept of sized type as a representation that incorporates structural (shape) information and allows expressing both lower and upper bounds on the size of a set of terms and their subterms at any position and depth. For example, expressing bounds on the length of lists of numbers, together with bounds on the values of all of their elements. The analysis is developed using abstract interpretation and the novel abstract operations are based on setting up and solving recurrence relations between sized types. It has been integrated, together with novel resource usage and cardinality analyses, in the abstract interpretation framework in the Ciao preprocessor, CiaoPP, in order to assess both the accuracy of the new size analysis and its usefulness in the resource usage estimation application. We show that the proposed sized types are a substantial improvement over the previous size analyses present in CiaoPP, and also bene?t the resource analysis considerably, allowing the inference of equal or better bounds than comparable state of the art systems.
Internacional
Si
JCR del ISI
No
Título de la revista
Theory and Practice of Logic Programming, 29th Int'l. Conference on Logic Programming (ICLP'13) Special Issue, On-line Supplement
ISSN
1471-0684
Factor de impacto JCR
1,21
Información de impacto
Volumen
13
DOI
Número de revista
13 (4-5)
Desde la página
1
Hasta la página
14
Mes
AGOSTO
Ranking
CORE: A. Citeseer: position 188/1221 (top 15%), impact 1.21. Average position: top 24%.

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Participantes

Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Computación lógica, Lenguajes, Implementación y Paralelismo (CLIP)
  • Departamento: Inteligencia Artificial