Symbolic execution proofs for higher order store programs

Higher order store programs are programs which store, manipulate and invoke code at runtime. Important examples of higher order store programs include operating system kernels which dynamically load and unload kernel modules. Yet conventional Hoare logics, which provide no means of representing changes to code at runtime, are not applicable to such programs. Recently, however, new logics using nested Hoare triples have addressed this shortcoming. In this paper we describe, from top to bottom, a sound semi-automated verification system for higher order store programs. We give a programming language with higher order store features, define an assertion language with nested triples for specifying such programs, and provide reasoning rules for proving programs correct. We then present in full our algorithms for automatically constructing correctness proofs. In contrast to earlier work, the language also includes ordinary (fixed) procedures and mutable local variables, making it easy to model programs which perform dynamic loading and other higher order store operations. We give an operational semantics for programs and a step-indexed interpretation of assertions, and use these to show soundness of our reasoning rules, which include a deep frame rule which allows more modular proofs. Our automated reasoning algorithms include a scheme for separation logic based symbolic execution of programs, and automated provers for solving various kinds of entailment problems. The latter are presented in the form of sets of derived proof rules which are constrained enough to be read as a proof search algorithm

A refined parametric model for short term load forecasting

Abstract We present a refined parametric model for forecasting electricity demand which performed particularly well in the recent Global Energy Forecasting Competition (GEFCom 2012). We begin by motivating and presenting a simple parametric model, treating the electricity demand as a function of the temperature and day of the data. We then set out a series of refinements of the model, explaining the rationale for each, and using the competition scores to demonstrate that each successive refinement step increases the accuracy of the model’s predictions. These refinements include combining models from multiple weather stations, removing outliers from the historical data, and special treatments of public holidays

A decidable class of verification conditions for programs with higher order store

Recent years have seen a surge in techniques and tools for automatic and semi-automatic static checking of imperative heap-manipulating programs. At the heart of such tools are algorithms for automatic logical reasoning, using heap description formalisms such as separation logic. In this paper we work towards extending these static checking techniques to languages with procedures as first class citizens. To do this, we first identify a class of entailment problems which arise naturally as verification conditions during the static checking of higher order heap-manipulating programs. We then present a decision procedure for this class and prove its correctness. Entailments in our class combine simple symbolic heaps, which are descriptions of the heap using a subset of separation logic, with (limited use of) nested Hoare triples to specify properties of higher order procedures

Falsifying safety properties through games on over-approximating models\r\n

AbstractAbstractions of programs are traditionally over-approximations and have proved to be useful for the verification of safety properties. They are presently perceived as being useless for the falsification of safety properties, i.e. showing that program execution definitely reaches a “bad” state. Alternative techniques, such as the computation of under-approximating must transitions, have addressed this shortcoming in the past. We show that over-approximating models can indeed falsify safety properties by relying on and exploiting the seriality and partial determinism of programs: programs don't just stop for no reason, and most program statements have deterministic semantics. Our method is based on solving a two-person attractor game derived from over-approximating models and makes no assumptions about the abstraction domain used. An example demonstrates the successful use of our approach, and highlights the role played by seriality and our handling of nondeterminism. Finally, we show that our method can encode must transitions, if supplied, by a simple modification of the ownership of nodes in the attractor game derived from the over-approximating model

In the mood: the dynamics of collective sentiments on Twitter

We study the relationship between the sentiment levels of Twitter users and the evolving network structure that the users created by @-mentioning each other. We use a large dataset of tweets to which we apply three sentiment scoring algorithms, including the open source Sentistrength program. Specifically we make three contributions. Firstly, we find that people who have potentially the largest communication reach (according to a dynamic centrality measure) use sentiment differently than the average user: for example, they use positive sentiment more often and negative sentiment less often. Secondly, we find that when we follow structurally stable Twitter communities over a period of months, their sentiment levels are also stable, and sudden changes in community sentiment from one day to the next can in most cases be traced to external events affecting the community. Thirdly, based on our findings, we create and calibrate a simple agent-based model that is capable of reproducing measures of emotive response comparable with those obtained from our empirical dataset

An Ontology to support Knowledge Management in Behaviour-based Healthcare

A Do Something Different (DSD) behaviour change programme consists of a series of digitally delivered behavioural prompts, or "Dos", for targeted behaviour change designed to aid people to achieve personal goals or to break bad habits. "Dos" may address for example behaviour connected with exercise, smoking, diet, sleep or diabetes self-management, or personal development objectives such as leadership. DSD's current database contains thousands of such "Dos", developed by behaviour change experts. We have developed an ontology to organise the large database of behavioural prompts in order to help DSD with its knowledge management. We began by developing an ontology of function, bottom-up; then we expanded this into a multi-perspective ontology covering WHO, WHAT, HOW, WHEN, WHERE and WHY perspectives. The expected benefits from our ontology are: 1. response data from users can be aggregated by ontology category to get insights into users' behaviour, 2. the ontology enables the implementation of smarter algorithms for selecting which "Dos" to suggest to which users, and 3. the ontology assists in the process of generating new "Dos", either by domain experts or by crowd-sourcing. Finally we follow an ontology-theoretic approach to argue that our ontology should be re-usable across other behaviour change applications, but maybe not across other application types

Polynomial-Time Under-Approximation of Winning Regions in Parity Games

We propose a pattern for designing algorithms that run in polynomial time by construction and under-approximate the winning regions of both players in parity games. This approximation is achieved by the interaction of finitely many aspects governed by a common ranking function, where the choice of aspects and ranking function instantiates the design pattern. Each aspect attempts to improve the under-approximation of winning regions or decrease the rank function by simplifying the structure of the parity game. Our design pattern is incremental as aspects may operate on the residual game of yet undecided nodes. We present several aspects and one higher-order transformation of our algorithms - based on efficient, static analyses - and illustrate the benefit of their interaction as well as their relative precision within pattern instantiations. Instantiations of our design pattern can be applied for local model checking and as preprocessors for algorithms whose worst-case running time is exponential. This design pattern and its aspects have already been implemented in [H. Wang. Framework for Under-Approximating Solutions of Parity Games in Polynomial Time. MEng Thesis, Department of Computing, Imperial College London, 78 pages, June 2007]. © 2008 Elsevier B.V. All rights reserved

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens