A visual language for temporal specifications based on Spider diagrams

Spider Diagrams are a well-established visual language to specify sets, their relationships, and constraints on their cardinalities. However, they do not support evolution of specifications, where one wants to state that under certain circumstances a specification becomes invalid and a new one must be used, nor transformation of specifications, where one needs operators to manipulate specifications. In this paper, we attack the first problem by developing a new system of timed Spider Diagrams which allow modellers to indicate the temporal range of validity of a specification. The approach is illustrated with examples of policies for library management

A Normal Form for Spider Diagrams of Order

We develop a reasoning system for an Euler diagram based visual logic, called spider diagrams of order. We de- fine a normal form for spider diagrams of order and provide an algorithm, based on the reasoning system, for producing diagrams in our normal form. Normal forms for visual log- ics have been shown to assist in proving completeness of associated reasoning systems. We wish to use the reasoning system to allow future direct comparison of spider diagrams of order and linear temporal logic

A cognitive exploration of the “non-visual” nature of geometric proofs

Why are Geometric Proofs (Usually) “Non-Visual”? We asked this question as a way to explore the similarities and differences between diagrams and text (visual thinking versus language thinking). Traditional text-based proofs are considered (by many to be) more rigorous than diagrams alone. In this paper we focus on human perceptual-cognitive characteristics that may encourage textual modes for proofs because of the ergonomic affordances of text relative to diagrams. We suggest that visual-spatial perception of physical objects, where an object is perceived with greater acuity through foveal vision rather than peripheral vision, is similar to attention navigating a conceptual visual-spatial structure. We suggest that attention has foveal-like and peripheral-like characteristics and that textual modes appeal to what we refer to here as foveal-focal attention, an extension of prior work in focused attention

Graphical Structures for Design and Verification of Quantum Error Correction

We introduce a high-level graphical framework for designing and analysing quantum error correcting codes, centred on what we term the coherent parity check (CPC). The graphical formulation is based on the diagrammatic tools of the zx-calculus of quantum observables. The resulting framework leads to a construction for stabilizer codes that allows us to design and verify a broad range of quantum codes based on classical ones, and that gives a means of discovering large classes of codes using both analytical and numerical methods. We focus in particular on the smaller codes that will be the first used by near-term devices. We show how CSS codes form a subset of CPC codes and, more generally, how to compute stabilizers for a CPC code. As an explicit example of this framework, we give a method for turning almost any pair of classical [n,k,3] codes into a [[2n - k + 2, k, 3]] CPC code. Further, we give a simple technique for machine search which yields thousands of potential codes, and demonstrate its operation for distance 3 and 5 codes. Finally, we use the graphical tools to demonstrate how Clifford computation can be performed within CPC codes. As our framework gives a new tool for constructing small- to medium-sized codes with relatively high code rates, it provides a new source for codes that could be suitable for emerging devices, while its zx-calculus foundations enable natural integration of error correction with graphical compiler toolchains. It also provides a powerful framework for reasoning about all stabilizer quantum error correction codes of any size.Comment: Computer code associated with this paper may be found at https://doi.org/10.15128/r1bn999672

Validation of UML Models for Interactive Systems with CPN and SPIN

Unified Modelling Language (UML) is considered to be the standard language for object-oriented modeling and analysis. However, UML cannot be used for automatic analysis and simulation. The system model developed on the basis of UML tool is not executable in nature. So, behavior of the model cannot be validated until it is implemented. In this thesis, an approach for transforming UML Interaction Overview Diagram (IOD) to Colored Petri Net (CPN) models is proposed. This transformation is used to bridge the gap between informal notation (UML diagrams) and more formal notation (CPN models) for analysis purpose. CPN model is validated by CPN tool. CPN tool is executable, and it is possible to inspect the behavior of the system by simulating CPN model. An interaction overview diagram has been designed for the different operation of an Automatic Teller Machine (ATM) using Magic Draw. Later, this diagram is transformed to CPN model. The specification of the proposed system has been analyzed by simulating the CPN model on CPN tool. Model checking is an important technique for ensuring the correctness of any system. This thesis presents a case study for model checking through an example of verifying ATM with Simple PROMELA Interpreter (SPIN). The ATM system was modeled in Process or Protocol Meta Language (PROMELA) for business flow of an ATM system. It is then checked for deadlock and unreachable code with SPIN model checker. Here the SPIN model checker is used to apply Linear Temporal Logic (LTL) formula on the ATM system and check for liveness and safety properties. The results showed that the ATM model did not have deadlock and unreachable code, and also satisfied the liveness and safety properties

BlogForever D2.6: Data Extraction Methodology

This report outlines an inquiry into the area of web data extraction, conducted within the context of blog preservation. The report reviews theoretical advances and practical developments for implementing data extraction. The inquiry is extended through an experiment that demonstrates the effectiveness and feasibility of implementing some of the suggested approaches. More specifically, the report discusses an approach based on unsupervised machine learning that employs the RSS feeds and HTML representations of blogs. It outlines the possibilities of extracting semantics available in blogs and demonstrates the benefits of exploiting available standards such as microformats and microdata. The report proceeds to propose a methodology for extracting and processing blog data to further inform the design and development of the BlogForever platform