Using Ontologies in Formal Developments Targeting Certification

This is the author accepted manuscript. The final version is available from Springer Verlag via the DOI in this recordIFM 2019: 15th International Conference on integrated Formal Methods, 4-6 December 2019, Bergen, NorwayA common problem in the certification of highly safety or security critical systems is the consistency of the certification documentation in general and, in particular, the linking between semi-formal and formal content of the certification documentation. We address this problem by using an existing framework, Isabelle/DOF, that allows writing certification documents with consistency guarantees, in both, the semi-formal and formal parts. Isabelle/DOF supports the modeling of document ontologies using a strongly typed ontology definition language. An ontology is then enforced inside documents including formal parts, e.g., system models, verification proofs, code, tests and validations of corner-cases. The entire set of documents is checked within Isabelle/HOL, which includes the definition of ontologies and the editing of integrated documents based on them. This process is supported by an IDE that provides continuous checking of the document consistency. In this paper, we present how a specific software-engineering certification standard, namely CENELEC 50128, can be modeled inside Isabelle/DOF. Based on an ontology covering a substantial part of this standard, we present how Isabelle/DOF can be applied to a certification case-study in the railway domain.IRT System

Isabelle/DOF: Design and Implementation

This is the author accepted manuscript. The final version is available from Springer Verlag via the DOI in this record17th International Conference, SEFM 2019 Oslo, Norway, September 18–20, 2019DOF is a novel framework for defining ontologies and enforcing them during document development and evolution. A major goal of DOF is the integrated development of formal certification documents (e. g., for Common Criteria or CENELEC 50128) that require consistency across both formal and informal arguments. To support a consistent development of formal and informal parts of a document, we provide Isabelle/DOF, an implementation of DOF on top of the formal methods framework Isabelle/HOL. A particular emphasis is put on a deep integration into Isabelleâs IDE, which allows for smooth ontology development as well as immediate ontological feedback during the editing of a document. In this paper, we give an in-depth presentation of the design concepts of DOFâs Ontology Definition Language (ODL) and key aspects of the technology of its implementation. Isabelle/DOF is the first ontology language supporting machine-checked links between the formal and informal parts in an LCF-style interactive theorem proving environment. Sufficiently annotated, large documents can easily be developed collabo- ratively, while ensuring their consistency, and the impact of changes (in the formal and the semi-formal content) is tracked automatically.IRT SystemX, Paris-Saclay, Franc

Do logarithmic proximity measures outperform plain ones in graph clustering?

We consider a number of graph kernels and proximity measures including commute time kernel, regularized Laplacian kernel, heat kernel, exponential diffusion kernel (also called "communicability"), etc., and the corresponding distances as applied to clustering nodes in random graphs and several well-known datasets. The model of generating random graphs involves edge probabilities for the pairs of nodes that belong to the same class or different predefined classes of nodes. It turns out that in most cases, logarithmic measures (i.e., measures resulting after taking logarithm of the proximities) perform better while distinguishing underlying classes than the "plain" measures. A comparison in terms of reject curves of inter-class and intra-class distances confirms this conclusion. A similar conclusion can be made for several well-known datasets. A possible origin of this effect is that most kernels have a multiplicative nature, while the nature of distances used in cluster algorithms is an additive one (cf. the triangle inequality). The logarithmic transformation is a tool to transform the first nature to the second one. Moreover, some distances corresponding to the logarithmic measures possess a meaningful cutpoint additivity property. In our experiments, the leader is usually the logarithmic Communicability measure. However, we indicate some more complicated cases in which other measures, typically, Communicability and plain Walk, can be the winners.Comment: 11 pages, 5 tables, 9 figures. Accepted for publication in the Proceedings of 6th International Conference on Network Analysis, May 26-28, 2016, Nizhny Novgorod, Russi

Influence of a knot on the strength of a polymer strand

Many experiments have been done to determine the relative strength of different knots, and these show that the break in a knotted rope almost invariably occurs at a point just outside the `entrance' to the knot. The influence of knots on the properties of polymers has become of great interest, in part because of their effect on mechanical properties. Knot theory applied to the topology of macromolecules indicates that the simple trefoil or `overhand' knot is likely to be present with high probability in any long polymer strand. Fragments of DNA have been observed to contain such knots in experiments and computer simulations. Here we use {\it ab initio} computational methods to investigate the effect of a trefoil knot on the breaking strength of a polymer strand. We find that the knot weakens the strand significantly, and that, like a knotted rope, it breaks under tension at the entrance to the knot.Comment: 3 pages, 4 figure

Delineating pathological pathways in a chemically-induced mouse model of Gaucher disease

Great interest has been shown in understanding the pathology of Gaucher disease (GD), due to the recently discovered genetic relationship with Parkinson's disease. For such studies, suitable animal models of GD are required. Chemical induction of GD by inhibition of acid β-glucosidase (GCase) using the irreversible inhibitor, conduritol B-epoxide (CBE), is particularly attractive, although few systematic studies examining the effect of CBE on development of symptoms associated with neurological forms of GD have been performed. We now demonstrate a correlation between the amount of CBE injected into mice and levels of accumulation of the GD substrates, glucosylceramide and glucosylsphingosine, and show that disease pathology, indicated by altered levels of pathological markers, depends on both levels of accumulated lipids and the time at which their accumulation begins. Gene array analysis shows a remarkable similarity in the gene expression profiles of CBE-treated mice and a genetic GD mouse model, the Gba(flox/flox) ;nestin-Cre mouse, with 120 of the 144 genes up-regulated in CBE-treated mice also up-regulated in Gba(flox/flox) ;nestin-Cre mice. We also demonstrate that various aspects of neuropathology and some behavioral abnormalities can be arrested upon cessation of CBE treatment during a specific time window. Together, our data demonstrate that injection of mice with CBE provides a rapid and relatively easy way to induce symptoms typical of neuronal forms of GD. This is particularly useful when examining the role of specific biochemical pathways in GD pathology, since CBE can be injected into mice defective in components of putative pathological pathways, alleviating the need for time-consuming crossing of mice