Relational String Abstract Domains

Author(s):  
Vincenzo Arceri ◽  
Martina Olliaro ◽  
Agostino Cortesi ◽  
Pietro Ferrara
Keyword(s):  
2006 ◽  
Vol 41 (7) ◽  
pp. 44-53 ◽  
Author(s):  
Nathan Cooprider ◽  
John Regehr

Author(s):  
Agostino Cortesi ◽  
Francesco Logozzo

This chapter investigates a formal approach to the verification of non-functional software requirements that are crucial in Service-oriented Systems, like portability, time and space efficiency, and dependability/robustness. The key-idea is the notion of observable, i.e., an abstraction of the concrete semantics when focusing on a behavioral property of interest. By applying an abstract interpretation-based static analysis of the source program, and by a suitable choice of abstract domains, it is possible to design formal and effective tools for non-functional requirements validation.


2020 ◽  
Vol 34 (05) ◽  
pp. 7432-7439
Author(s):  
Yonatan Bisk ◽  
Rowan Zellers ◽  
Ronan Le bras ◽  
Jianfeng Gao ◽  
Yejin Choi

To apply eyeshadow without a brush, should I use a cotton swab or a toothpick? Questions requiring this kind of physical commonsense pose a challenge to today's natural language understanding systems. While recent pretrained models (such as BERT) have made progress on question answering over more abstract domains – such as news articles and encyclopedia entries, where text is plentiful – in more physical domains, text is inherently limited due to reporting bias. Can AI systems learn to reliably answer physical commonsense questions without experiencing the physical world?In this paper, we introduce the task of physical commonsense reasoning and a corresponding benchmark dataset Physical Interaction: Question Answering or PIQA. Though humans find the dataset easy (95% accuracy), large pretrained models struggle (∼75%). We provide analysis about the dimensions of knowledge that existing models lack, which offers significant opportunities for future research.


2020 ◽  
Vol 20 (6) ◽  
pp. 848-863
Author(s):  
PIERRE TALBOT ◽  
ÉRIC MONFROY ◽  
CHARLOTTE TRUCHET

AbstractCooperation among constraint solvers is difficult because different solving paradigms have different theoretical foundations. Recent works have shown that abstract interpretation can provide a unifying theory for various constraint solvers. In particular, it relies on abstract domains which capture constraint languages as ordered structures. The key insight of this paper is viewing cooperation schemes as abstract domains combinations. We propose a modular framework in which solvers and cooperation schemes can be seamlessly added and combined. This differs from existing approaches such as SMT where the cooperation scheme is usually fixed (e.g., Nelson-Oppen). We contribute to two new cooperation schemes: (i) interval propagators completion that allows abstract domains to exchange bound constraints, and (ii) delayed product which exchanges over-approximations of constraints between two abstract domains. Moreover, the delayed product is based on delayed goal of logic programming, and it shows that abstract domains can also capture control aspects of constraint solving. Finally, to achieve modularity, we propose the shared product to combine abstract domains and cooperation schemes. Our approach has been fully implemented, and we provide various examples on the flexible job shop scheduling problem.


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