A methodology for the generation of efficient error detection mechanisms

A dependable software system must contain error detection mechanisms and error recovery mechanisms. Software components for the detection of errors are typically designed based on a system specification or the experience of software engineers, with their efficiency typically being measured using fault injection and metrics such as coverage and latency. In this paper, we introduce a methodology for the design of highly efficient error detection mechanisms. The proposed methodology combines fault injection analysis and data mining techniques in order to generate predicates for efficient error detection mechanisms. The results presented demonstrate the viability of the methodology as an approach for the development of efficient error detection mechanisms, as the predicates generated yield a true positive rate of almost 100% and a false positive rate very close to 0% for the detection of failure-inducing states. The main advantage of the proposed methodology over current state-of-the-art approaches is that efficient detectors are obtained by design, rather than by using specification-based detector design or the experience of software engineers

Predicting protein function with hierarchical phylogenetic profiles: The Gene3D phylo-tuner method applied to eukaryotic Genomes

"Phylogenetic profiling'' is based on the hypothesis that during evolution functionally or physically interacting genes are likely to be inherited or eliminated in a codependent manner. Creating presence-absence profiles of orthologous genes is now a common and powerful way of identifying functionally associated genes. In this approach, correctly determining orthology, as a means of identifying functional equivalence between two genes, is a critical and nontrivial step and largely explains why previous work in this area has mainly focused on using presence-absence profiles in prokaryotic species. Here, we demonstrate that eukaryotic genomes have a high proportion of multigene families whose phylogenetic profile distributions are poor in presence-absence information content. This feature makes them prone to orthology mis-assignment and unsuited to standard profile-based prediction methods. Using CATH structural domain assignments from the Gene3D database for 13 complete eukaryotic genomes, we have developed a novel modification of the phylogenetic profiling method that uses genome copy number of each domain superfamily to predict functional relationships. In our approach, superfamilies are subclustered at ten levels of sequence identity from 30% to 100% - and phylogenetic profiles built at each level. All the profiles are compared using normalised Euclidean distances to identify those with correlated changes in their domain copy number. We demonstrate that two protein families will "auto-tune'' with strong co-evolutionary signals when their profiles are compared at the similarity levels that capture their functional relationship. Our method finds functional relationships that are not detectable by the conventional presence - absence profile comparisons, and it does not require a priori any fixed criteria to define orthologous genes

Proceedings of Abstracts Engineering and Computer Science Research Conference 2019

© 2019 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Note: Keynote: Fluorescence visualisation to evaluate effectiveness of personal protective equipment for infection control is © 2019 Crown copyright and so is licensed under the Open Government Licence v3.0. Under this licence users are permitted to copy, publish, distribute and transmit the Information; adapt the Information; exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application. Where you do any of the above you must acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This conference is a local event aiming at bringing together the research students, staff and eminent external guests to celebrate Engineering and Computer Science Research at the University of Hertfordshire. The ECS Research Conference aims to showcase the broad landscape of research taking place in the School of Engineering and Computer Science. The 2019 conference was articulated around three topical cross-disciplinary themes: Make and Preserve the Future; Connect the People and Cities; and Protect and Care

Final report on the evaluation of RRM/CRRM algorithms

Deliverable public del projecte EVERESTThis deliverable provides a definition and a complete evaluation of the RRM/CRRM algorithms selected in D11 and D15, and evolved and refined on an iterative process. The evaluation will be carried out by means of simulations using the simulators provided at D07, and D14.Preprin

Automated Black-Box Boundary Value Detection

The input domain of software systems can typically be divided into sub-domains for which the outputs are similar. To ensure high quality it is critical to test the software on the boundaries between these sub-domains. Consequently, boundary value analysis and testing has been part of the toolbox of software testers for long and is typically taught early to students. However, despite its many argued benefits, boundary value analysis for a given specification or piece of software is typically described in abstract terms which allow for variation in how testers apply it. Here we propose an automated, black-box boundary value detection method to support software testers in systematic boundary value analysis with consistent results. The method builds on a metric to quantify the level of boundariness of test inputs: the program derivative. By coupling it with search algorithms we find and rank pairs of inputs as good boundary candidates, i.e. inputs close together but with outputs far apart. We implement our AutoBVA approach and evaluate it on a curated dataset of example programs. Our results indicate that even with a simple and generic program derivative variant in combination with broad sampling over the input space, interesting boundary candidates can be identified

Re-Assembling the Sagittarius Dwarf Galaxy

What is the mass of the progenitor of the Sagittarius (Sgr) dwarf galaxy? Here, we reassemble the stellar debris using SDSS and 2MASS data to find the total luminosity and likely mass. We find that the luminosity is in the range 9.6-13.2 x10^7 solar luminosities or M_V ~ -15.1 - 15.5, with 70% of the light residing in the debris streams. The progenitor is somewhat fainter than the present-day Small Magellanic Cloud, and comparable in brightness to the M31 dwarf spheroidals NGC 147 and NGC 185. Using cosmologically motivated models, we estimate that the mass of Sgr's dark matter halo prior to tidal disruption was ~10^10 solar masses.Comment: 12 pages, 11 figures, 3 tables, submitted to Ap

Studying cities to learn about minds: some possible implications of space syntax for spatial cognition

What can we learn of the human mind by examining its products? The city is a case in point. Since the beginning of cities human ideas about them have been dominated by geometric ideas, and the real history of cities has always oscillated between the geometric and the ‘organic’. Set in the context of the suggestion from cognitive neuroscience that we impose more geometric order on the world than it actually possesses, and intriguing question arises: what is the role of the geometric intuition in how we understand cities and how we create them? Here I argue, drawing on space syntax research which has sought to link the detailed spatial morphology of cities to observable functional regularities, that all cities, the organic as well as the geometric, are pervasively ordered by geometric intuition, so that neither the forms of the cities nor their functioning can be understood without insight into their distinctive and pervasive emergent geometrical forms. The city is often said to be the creation of economic and social processes, but here it is argued that these processes operate within an envelope of geometric possibility defined by the human mind in its interaction with spatial laws that govern the relations between objects and spaces in the ambient world