scholarly journals Inconsistency-tolerant Hierarchical Probabilistic Computation Tree Logic and Its Application to Model Checking

Author(s):  
Norihiro Kamide ◽  
Noriko Yamamoto
2012 ◽  
Vol 23 (7) ◽  
pp. 1656-1668 ◽  
Author(s):  
Cong-Hua ZHOU ◽  
Zhi-Feng LIU ◽  
Chang-Da WANG

1998 ◽  
Vol 35 (8) ◽  
pp. 645-664 ◽  
Author(s):  
Danièle Beauquier ◽  
Anatol Slissenko

Author(s):  
Norihiro Kamide ◽  
◽  
Daiki Koizumi ◽  

Computation tree logic (CTL) is known to be one of the most useful temporal logics for verifying concurrent systems by model checking technologies. However, CTL is not sufficient for handling inconsistency-tolerant and probabilistic accounts of concurrent systems. In this paper, a paraconsistent (or inconsistency-tolerant) probabilistic computation tree logic (PpCTL) is derived from an existing probabilistic computation tree logic (pCTL) by adding a paraconsistent negation connective. A theorem for embedding PpCTL into pCTL is proven, thereby indicating that we can reuse existing pCTL-based model checking algorithms. A relative decidability theorem for PpCTL, wherein the decidability of pCTL implies that of PpCTL, is proven using this embedding theorem. Some illustrative examples involving the use of PpCTL are also presented.


10.29007/c8jt ◽  
2018 ◽  
Author(s):  
Franz Weitl ◽  
Shin Nakajima

A new algorithm for incrementally generating counterexamples for the temporal description logic ALCCTL is presented. ALCCTL is a decidable combination of the description logic ALC and computation tree logic CTL that is expressive for content- and structure-related properties of web documents being verified by model checking. In the case of a specification violation, existing model checkers provide a single counterexample which may be large and complex. We extend existing algorithms for generating counterexamples in two ways. First, a coarse counterexample is generated initially that can be refined subsequently to the desired level of detail in an incremental manner. Second, the user can choose where and in which way a counterexample is refined. This enables the interactive step-by-step analysis of error scenarios according to the user's interest.We demonstrate in a case study on a web-based training document that the proposed approach reveals more errors and explains the cause of errors more precisely than the counterexamples of existing model checkers. In addition, we demonstrate that the proposed algorithm is sufficiently fast to enable smooth interaction even in the case of large documents.


2007 ◽  
Vol 190 (3) ◽  
pp. 95-110 ◽  
Author(s):  
Pedro Baltazar ◽  
Paulo Mateus ◽  
Rajagopal Nagarajan ◽  
Nikolaos Papanikolaou

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