bluuebunny/crossref_metadata_2025 huggingface dataset:
Gut Microbiota Predict
Enterococcus
Expansion but Not Vancomycin-Resistant
Enterococcus
Acquisition
Authors: Chanderraj Rishi , Brown Christopher A. , Hinkle Kevin , Falkowski Nicole , Ranjan Piyush , Dickson Robert P. , Woods Robert J.
Published: November 2020

The Centers for Disease Control and Prevention estimates that VRE causes an estimated 54,000 infections and 539 million dollars in attributable health care costs annually. Despite improvements in hand washing, environmental cleaning, and antibiotic use, VRE is still prevalent in many hospitals. There is a pressing need to better understand the processes by which patients acquire VRE. Multiple lines of evidence suggest that intestinal microbiota may help some patients resist VRE acquisition. In this large case-control study, we compared the 16S profile of intestinal microbiota on admission in patients that did and did not subsequently acquire VRE. The 16S profile did not predict subsequent VRE acquisition, in part due to rapid and dramatic change in the gut microbiome following hospitalization. However,
Blautia
spp. present on admission predicted decreased
Enterococcus
abundance after VRE acquisition, and
Lactobacillus
spp. present on admission predicted
Enterococcus
dominance after VRE acquisition. Thus, VRE acquisition and domination may be distinct processes.
Labour companionship and women’s experiences of mistreatment during childbirth: results from a multi-country community-based survey
Authors: Balde Mamadou Dioulde , Nasiri Khalidha , Mehrtash Hedieh , Soumah Anne-Marie , Bohren Meghan A , Diallo Boubacar Alpha , Irinyenikan Theresa Azonima , Maung Thae Maung , Thwin Soe Soe , Aderoba Adeniyi K , Vogel Joshua P , Mon Nwe Oo , Adu-Bonsaffoh Kwame , Tunçalp Özge
Published: November 2020

Background

Evidence has shown the benefits of labour companions during childbirth. Few studies have documented the relationship between the absence of labour companions and mistreatment of women during childbirth in low-income and middle-income countries using a standardised tool.

Methods

We conducted a secondary analysis of the WHO multi-country study on how women are treated during childbirth, where a cross-sectional community survey was conducted with women up to 8 weeks after childbirth in Ghana, Guinea, Nigeria and Myanmar. Descriptive analysis and multivariable logistic regression were used to examine whether labour companionship was associated with various types of mistreatment.

Results

Of 2672 women, about half (50.4%) reported the presence of a labour companion. Approximately half (49.6%) of these women reported that the timing of support was during labour and after childbirth and most of the labour companions (47.0%) were their family members. Across Ghana, Guinea and Nigeria, women without a labour companion were more likely to report physical abuse, non-consented medical procedures and poor communication compared with women with a labour companion. However, there were country-level variations. In Guinea, the absence of labour companionship was associated with any physical abuse, verbal abuse, or stigma or discrimination (adjusted OR (AOR) 3.6, 1.9–6.9) and non-consented vaginal examinations (AOR 3.2, 1.6–6.4). In Ghana, it was associated with non-consented vaginal examinations (AOR 2.3, 1.7–3.1) and poor communication (AOR 2.0, 1.3–3.2). In Nigeria, it was associated with longer wait times (AOR 0.6, 0.3–0.9).

Conclusion

Labour companionship is associated with lower levels of some forms of mistreatment that women experience during childbirth, depending on the setting. Further work is needed to ascertain how best to implement context-specific labour companionship to ensure benefits while maintaining women’s choices and autonomy.
Ethical considerations for universal newborn hearing screening in the Pacific Islands: a Samoan case study
Authors: Kaspar Annette , Driscoll Carlie , Pifeleti Sione , Faumuina Penaia A
Published: November 2020

Permanent congenital and early-onset hearing impairment (PCEOHI) is the most common sensory disorder among newborns. The WHO recommends newborn and infant hearing screening for all member states to facilitate early identification and intervention for children with PCEOHI. Ethical implications of newborn/infant hearing screening in low-income and middle-income countries should be considered. Although the Pacific Island region is estimated to have among the highest global burden of hearing loss, hearing health services are limited and virtually non-existent in Pacific Island countries. The aim of this brief report is to consider the ethical implications of implementing hospital-based universal newborn hearing screening (UNHS) in Samoa. Based on well-acknowledged screening principles, this report found that the Samoan context does not satisfy the screening principles for such a programme, and that the implementation of UNHS would, therefore, be unethical. This conclusion was reached even after considering the hypothetical provision of necessary screening and diagnostic audiology equipment from external donors. We recommend that current efforts should be directed towards the wider professional community involved in the daily care of children with a permanent hearing loss. Given the high prevalence of paediatric ear disease in the Pacific Islander population, an interim ear and hearing programme could be considered at the community level. These strategies should provide the infrastructure and referral pathways required in the advent of UNHS in Samoa.
Cleaning products and respiratory health outcomes in occupational cleaners: a systematic review and meta-analysis
Authors: Archangelidi Olia , Sathiyajit Sean , Consonni Dario , Jarvis Debbie , De Matteis Sara
Published: November 2020

There is consistent evidence of increased respiratory symptoms in occupational cleaners; however, uncertainty remains on type of respiratory health effects, underlying causal agents, mechanisms and respiratory phenotypes. We aimed to conduct a systematic review and if possible, a meta-analysis of the available literature to characterise and quantify the cleaning-related respiratory health effects. We searched MEDLINE and EMBASE databases and included studies that evaluated the association of any respiratory health outcome with exposure to cleaning occupation or products in occupational cleaners. A modified GRADE was used to appraise the quality of included studies. We retrieved 1124 articles, and after applying our inclusion criteria, 39 were selected for the systematic review. We performed a meta-analysis of the 21 studies evaluating asthma which showed a 50% increased pooled relative risk in cleaners (meta-relative risk (RR)=1.50; 95% CI 1.44 to 1.56). Population-based cross-sectional studies showed more stable associations with asthma risk. No evidence of atopic asthma as dominant phenotype emerged. Also, we estimated a 43% increased risk (meta-RR=1.43; 95% CI 1.31 to 1.56) of chronic obstructive pulmonary disease. Evidence for associations with bronchial-hyper-responsiveness, lung function decline, rhinitis, upper and lower respiratory tract symptoms was weaker. In our systematic review and meta-analysis, we found that working as a cleaner is associated with an increased risk of reversible and even irreversible obstructive airway diseases. All studies lacked quantitative exposure assessment to cleaning products; this would help elucidate underlying causal agents and mechanisms. Exposure control and respiratory surveillance among cleaners is warranted to prevent the associated respiratory health burden. Trial registration number: CRD4201705915.
Translactational associations of dry off management, milking activity, and somatic cell count in herds with automated milking systems
Authors: Padua F.H. , King M.T.M. , DeVries T.J.
Published: November 2020

The objective of this study was to evaluate associations of dry off management factors, milking activity and production data, and somatic cell count prior to dry off and early in the subsequent lactation of cows milked by automated systems. Data were collected for 342 cows from five farms, for two milk tests prior to dry off, and for the two milk tests post calving. The results suggest that the post-calving milking performance of cows milked by automated systems may be more associated with individual cow traits than with their dry off management.
Optimizing the prefabrication finishing level in modular construction
Authors: Almashaqbeh Mohammad , El-Rayes Khaled
Published: November 2020

Prefabricated modules in modular construction projects can have a wide range of finishing levels that range from partially completed with only structural frame to fully completed with all structural, wall, mechanical, electrical, finishing and furnishing components. A higher module finishing level increases the offsite fabrication and transportation cost and decreases onsite assembly cost and duration while a lower finishing level produces the opposite results. This paper presents an optimization model that enables construction planners to identify an optimal finishing level for prefabricated modules to minimize the total cost of modular construction projects that includes all offsite fabrication, transportation, and onsite assembly costs. A case study of a modular construction project for a healthcare facility was analyzed to illustrate the use of the model and evaluate its performance. The results of this analysis highlight the original capabilities of the model in minimizing the total cost of modular construction projects by identifying an optimal finishing level for each module type in the project from a set of feasible alternatives with varying building components, weights, and cost rates.
Minimal gauge invariant couplings at order $$\alpha '^3$$: NS–NS fields
Authors: Garousi Mohammad R.
Published: November 2020

Removing the field redefinitions, the Bianchi identities and the total derivative freedoms from the general form of gauge invariant NS–NS couplings at order $$\alpha '^3$$

α

′
3

, we have found that the minimum number of independent couplings is 872. We find that there are schemes in which there is no term with structures $$R,\,R_{\mu \nu },\,\nabla _\mu H^{\mu \alpha \beta }$$

R
,

R

μ
ν

,

∇
μ

H

μ
α
β

, $$ \nabla _\mu \nabla ^\mu \Phi $$

∇
μ

∇
μ

Φ

. In these schemes, there are sub-schemes in which, except one term, the couplings can have no term with more than two derivatives. In the sub-scheme that we have chosen, the 872 couplings appear in 55 different structures. We fix some of the parameters in type II supersting theory by its corresponding four-point functions. The coupling which has term with more than two derivatives is constraint to be zero by the four-point functions.
FROM MULTILATERALISM TO MULTI-POLARISM: A STUDY OF TRADE SHOCK TRANSMISSION BETWEEN SELECTED AFRICAN ECONOMIES, THE BRIC AND THE REST OF THE GLOBAL ECONOMY
Authors: EKEOCHA PATTERSON C. , OGBUABOR JONATHAN E.
Published: November 2020

This study investigates trade shock transmission between selected African countries, the BRIC and the rest of the global economy with a view to understanding the likely disposition of African economies towards multilateralism in the years to come. The study extends the network approach of Diebold and Yilmaz [ (2009) . Measuring financial asset return and volatility spillovers, with application to global equity markets. The Economic Journal,  119(534), 158–171, https://doi.org/10.1111/j.1468-0297.2008.02208.x ] by constructing generalized trade linkage measures at various degrees of aggregation using generalized forecast error variance decompositions of an underlying global vector autoregressive model. The results indicate that the trade linkage between Africa and the rest of the global economy is substantial, with the total trade linkage index having an average value of 87%. We find that China, USA, UK, Japan, EU and Canada dominate Africa’s trade and therefore have the potential to spread trade shocks to it. The results further indicate that apart from the BRIC, other regional trading blocs such as Asia, the Americas, and Europe play influential roles in Africa’s trade. Overall, the findings show that African economies are predominantly net receivers of trade shocks originating from the aforementioned dominant sources. We conclude that these patterns of cross-country trade shock spillovers, coupled with the ongoing challenges of legitimacy facing the World Trade Organisation, would likely influence Africa’s move from multilateralism to multi-polarism in the years to come.
Almost inner derivations of Lie algebras II
Authors: Burde Dietrich , Dekimpe Karel , Verbeke Bert
Published: November 2020

We continue the algebraic study of almost inner derivations of Lie algebras over a field of characteristic zero and determine these derivations for free nilpotent Lie algebras, for almost abelian Lie algebras, for Lie algebras whose solvable radical is abelian and for several classes of filiform nilpotent Lie algebras. We find a family of [Formula: see text]-dimensional characteristically nilpotent filiform Lie algebras [Formula: see text], for all [Formula: see text], all of whose derivations are almost inner. Finally, we compare the almost inner derivations of Lie algebras considered over two different fields [Formula: see text] for a finite-dimensional field extension.
Threshold of primordial black hole formation in Eddington-inspired-Born–Infeld gravity
Authors: Chen Che-Yu
Published: November 2020

It is believed that primordial black holes (PBHs), if they exist, can serve as a powerful tool to probe the early stage of the cosmic history. Essentially, in the radiation-dominated universe, PBHs could form by the gravitational collapse of overdense primordial perturbations produced during inflation. In this picture, one important ingredient is the threshold of density contrast, which defines the onset of PBH formation. In the literature, most of the estimations of threshold, no matter numerically or analytically, are implemented in the framework of general relativity (GR). In this paper, by performing analytic estimations, we point out that the threshold for PBH formation depends on the gravitational theory under consideration. In GR, given a fixed equation of state, the analytic estimations adopted in this paper give a constant value of the formation threshold. If the theory is characterized by additional mass scales other than the Planck mass, the estimated threshold of density contrast may depend on the energy scale of the universe at the time of PBH formation. In this paper, we consider the Eddington-inspired-Born–Infeld gravity as an example. We find that the threshold would be enhanced if the Born–Infeld coupling constant is positive, and would be suppressed for a negative coupling constant. Also, we show explicitly that the threshold depends on the energy scale of the universe at the PBH formation time. This conclusion is expected to be valid for any gravitational theory characterized by additional mass scales, suggesting the possibility of testing gravitational theories with PBHs.
Microstructures and Electrical Properties of Carbon/Silica Nanocomposites: Influence of the Silica Nanoparticles
Authors: Elqahtani Zainab Mefrah , Gouadria Soumaya , Alharbi Fatemah Farraj , Omri K.
Published: November 2020

In this work, the inorganic/organic a Carbon-Silica (C-S) nanocomposites in additional amorphous carbon matrix was successfully obtained through the sol–gel method, the two components are mixed in an effort to blend the best properties of both. The acquired C-S nanocomposites were characterized by X-ray diffraction (XRD). It was observed by Transmission Electronic Microscopy that nanoparticles with sizes from 14[Formula: see text]nm to 20[Formula: see text]nm. After heat treatment, we explore the electrical properties of the obtained C-S material. The current–voltage ([Formula: see text]–[Formula: see text]) and alternating current (ac) techniques in the temperature range (80–300[Formula: see text]K) was examined.
Covariant momentum map thermodynamics for parametrized field theories
Authors: Chirco Goffredo , Laudato Marco , Mele Fabio Maria
Published: November 2020

A general-covariant statistical framework capable of describing classical fluctuations of the gravitational field is a thorny open problem in theoretical physics, yet ultimately necessary to understand the nature of the gravitational interaction, and a key to quantum gravity. Inspired by Souriau’s symplectic generalization of the Maxwell–Boltzmann–Gibbs equilibrium in Lie group thermodynamics, we investigate a space–time-covariant formulation of statistical mechanics for parametrized first-order field theories, as a simplified model sharing essential general covariant features with canonical general relativity. Starting from a covariant multi-symplectic phase space formulation, we define a general-covariant notion of Gibbs state in terms of the covariant momentum map associated with the lifted action of the diffeomorphisms group on the extended phase space. We show how such a covariant notion of equilibrium encodes the whole information about symmetry, gauge and dynamics carried by the theory, associated with a canonical spacetime foliation, where the covariant choice of a reference frame reflects in a Lie algebra-valued notion of local temperature. We investigate how physical equilibrium, hence time evolution, emerges from such a state and the role of the gauge symmetry in the thermodynamic description.
A Note on Almgren–Chriss Optimal Execution Problem with Geometric Brownian Motion
Authors: Baldacci Bastien , Benveniste Jerome
Published: November 2020

We solve explicitly the Almgren–Chriss optimal liquidation problem where the stock price process follows a geometric Brownian motion. Our technique is to work in terms of cash and to use functional analysis tools. We show that this framework extends readily to the case of a stochastic drift for the price process and the liquidation of a portfolio.
Signal Transduction of a Novel WBP2 Oncogene
Authors: Chu Tinghine , Seah Sock Hong , Lim Yoon Pin
Published: November 2020

WW-domain binding protein 2 (WBP2) was first discovered as a ligand of the WW-domain of Yes-associated Protein (YAP). A decade after its discovery, our laboratory implicated WBP2 in breast cancer development. Since then, WBP2 had also been shown to be involved in other types of cancer, such as glioma, liver and skin cancer. The oncogenic properties of WBP2 are mediated by several oncogenic signalling pathways, including EGFR, PI3K/Akt, ER, Wnt, and Hippo signalling pathways. Recently, WBP2 was demonstrated to play roles in diseases other than cancer, such as infertility and deafness. In the near future, we envisage a growing body of literature surrounding the role of WBP2 in more cancer types and signalling pathways.
Data, Politics and Public Health
Authors: Harrison Teresa M. , Pardo Theresa A.
Published: November 2020

In spring 2020, New York City became the acknowledged epicenter of the COVID-19 pandemic in the United States. To keep residents informed, Governor Cuomo conducted a streak of 111 daily press briefings reporting critical information about the status of the pandemic in the State at large, and New York City in particular. We show that through these briefings Governor Cuomo introduced an audience of New Yorkers and others to concepts basic to data-driven decision making such as data, science, models, and projections, and in so doing claimed that his decisions were unrelated to politics or whim. But we further suggest that data-driven decision making is not always immune from politics and human frailty in government. We conclude that basing policy decisions on data requires that policymakers insure the creation of a resilient and trustworthy health care data infrastructure to function as the scaffolding upon which policy making takes place.
Enabling accuracy-aware Quantum compilers using symbolic resource estimation
Authors: Meuli Giulia , Soeken Mathias , Roetteler Martin , Häner Thomas
Published: November 2020

Approximation errors must be taken into account when compiling quantum programs into a low-level gate set. We present a methodology that tracks such errors automatically and then optimizes accuracy parameters to guarantee a specified overall accuracy while aiming to minimize the implementation cost in terms of quantum gates. The core idea of our approach is to extract functions that specify the optimization problem directly from the high-level description of the quantum program. Then, custom compiler passes optimize these functions, turning them into (near-)symbolic expressions for (1) the total error and (2) the implementation cost (e.g., total quantum gate count). All unspecified parameters of the quantum program will show up as variables in these expressions, including accuracy parameters. After solving the corresponding optimization problem, a circuit can be instantiated from the found solution. We develop two prototype implementations, one in C++ based on Clang/LLVM, and another using the Q# compiler infrastructure. We benchmark our prototypes on typical quantum computing programs, including the quantum Fourier transform, quantum phase estimation, and Shor's algorithm.
Assertion-based optimization of Quantum programs
Authors: Häner Thomas , Hoefler Torsten , Troyer Matthias
Published: November 2020

Quantum computers promise to perform certain computations exponentially faster than any classical device. Precise control over their physical implementation and proper shielding from unwanted interactions with the environment become more difficult as the space/time volume of the computation grows. Code optimization is thus crucial in order to reduce resource requirements to the greatest extent possible. Besides manual optimization, previous work has adapted classical methods such as constant-folding and common subexpression elimination to the quantum domain. However, such classically-inspired methods fail to exploit certain optimization opportunities across subroutine boundaries, limiting the effectiveness of software reuse. To address this insufficiency, we introduce an optimization methodology which employs annotations that describe how subsystems are entangled in order to exploit these optimization opportunities. We formalize our approach, prove its correctness, and present benchmarks: Without any prior manual optimization, our methodology is able to reduce, e.g., the qubit requirements of a 64-bit floating-point subroutine by 34×.
Learning semantic program embeddings with graph interval neural network
Authors: Wang Yu , Wang Ke , Gao Fengjuan , Wang Linzhang
Published: November 2020

Learning distributed representations of source code has been a challenging task for machine learning models. Earlier works treated programs as text so that natural language methods can be readily applied. Unfortunately, such approaches do not capitalize on the rich structural information possessed by source code. Of late, Graph Neural Network (GNN) was proposed to learn embeddings of programs from their graph representations. Due to the homogeneous (i.e. do not take advantage of the program-specific graph characteristics) and expensive (i.e. require heavy information exchange among nodes in the graph) message-passing procedure, GNN can suffer from precision issues, especially when dealing with programs rendered into large graphs. In this paper, we present a new graph neural architecture, called Graph Interval Neural Network (GINN), to tackle the weaknesses of the existing GNN. Unlike the standard GNN, GINN generalizes from a curated graph representation obtained through an abstraction method designed to aid models to learn. In particular, GINN focuses exclusively on intervals (generally manifested in looping construct) for mining the feature representation of a program, furthermore, GINN operates on a hierarchy of intervals for scaling the learning to large graphs.

We evaluate GINN for two popular downstream applications: variable misuse prediction and method name prediction. Results show in both cases GINN outperforms the state-of-the-art models by a comfortable margin. We have also created a neural bug detector based on GINN to catch null pointer deference bugs in Java code. While learning from the same 9,000 methods extracted from 64 projects, GINN-based bug detector significantly outperforms GNN-based bug detector on 13 unseen test projects. Next, we deploy our trained GINN-based bug detector and Facebook Infer, arguably the state-of-the-art static analysis tool, to scan the codebase of 20 highly starred projects on GitHub. Through our manual inspection, we confirm 38 bugs out of 102 warnings raised by GINN-based bug detector compared to 34 bugs out of 129 warnings for Facebook Infer. We have reported 38 bugs GINN caught to developers, among which 11 have been fixed and 12 have been confirmed (fix pending). GINN has shown to be a general, powerful deep neural network for learning precise, semantic program embeddings.
Mossad: defeating software plagiarism detection
Authors: Devore-McDonald Breanna , Berger Emery D.
Published: November 2020

Automatic software plagiarism detection tools are widely used in educational settings to ensure that submitted work was not copied. These tools have grown in use together with the rise in enrollments in computer science programs and the widespread availability of code on-line. Educators rely on the robustness of plagiarism detection tools; the working assumption is that the effort required to evade detection is as high as that required to actually do the assigned work.

This paper shows this is not the case. It presents an entirely automatic program transformation approach, MOSSAD, that defeats popular software plagiarism detection tools. MOSSAD comprises a framework that couples techniques inspired by genetic programming with domain-specific knowledge to effectively undermine plagiarism detectors. MOSSAD is effective at defeating four plagiarism detectors, including Moss and JPlag. MOSSAD is both fast and effective: it can, in minutes, generate modified versions of programs that are likely to escape detection. More insidiously, because of its non-deterministic approach, MOSSAD can, from a single program, generate
dozens
of variants, which are classified as no more suspicious than legitimate assignments. A detailed study of MOSSAD across a corpus of real student assignments demonstrates its efficacy at evading detection. A user study shows that graduate student assistants consistently rate MOSSAD-generated code as just as readable as authentic student code. This work motivates the need for both research on more robust plagiarism detection tools and greater integration of naturally plagiarism-resistant methodologies like code review into computer science education.
Scaling exact inference for discrete probabilistic programs
Authors: Holtzen Steven , Van den Broeck Guy , Millstein Todd
Published: November 2020

Probabilistic programming languages (PPLs) are an expressive means of representing and reasoning about probabilistic models. The computational challenge ofprobabilistic inferenceremains the primary roadblock for applying PPLs in practice. Inference is fundamentally hard, so there is no one-size-fits all solution. In this work, we target scalable inference for an important class of probabilistic programs: those whose probability distributions arediscrete. Discrete distributions are common in many fields, including text analysis, network verification, artificial intelligence, and graph analysis, but they prove to be challenging for existing PPLs.

We develop a domain-specific probabilistic programming language called Dice that features a new approach to exact discrete probabilistic program inference. Dice exploits program structure in order to factorize inference, enabling us to perform exact inference on probabilistic programs with hundreds of thousands of random variables. Our key technical contribution is a new reduction from discrete probabilistic programs to weighted model counting (WMC). This reduction separates the structure of the distribution from its parameters, enabling logical reasoning tools to exploit that structure for probabilistic inference. We (1) show how to compositionally reduce Dice inference to WMC, (2) prove this compilation correct with respect to a denotational semantics, (3) empirically demonstrate the performance benefits over prior approaches, and (4) analyze the types of structure that allow Dice to scale to large probabilistic programs.
WATCHER: in-situ failure diagnosis
Authors: Liu Hongyu , Silvestro Sam , Zhang Xiangyu , Huang Jian , Liu Tongping
Published: November 2020

Diagnosing software failures is important but notoriously challenging. Existing work either requires extensive manual effort, imposing a serious privacy concern (for in-production systems), or cannot report sufficient information for bug fixes. This paper presents a novel diagnosis system, named WATCHER, that can pinpoint root causes of program failures within the failing process ("in-situ"), eliminating the privacy concern. It combines identical record-and-replay, binary analysis, dynamic analysis, and hardware support together to perform the diagnosis without human involvement. It further proposes two optimizations to reduce the diagnosis time and diagnose failures with control flow hijacks. WATCHER can be easily deployed, without requiring custom hardware or operating system, program modification, or recompilation. We evaluate WATCHER with 24 program failures in real-world deployed software, including large-scale applications, such as Memcached, SQLite, and OpenJPEG. Experimental results show that WATCHER can accurately identify the root causes in only a few seconds.
Satune: synthesizing efficient SAT encoders
Authors: Gorjiara Hamed , Xu Guoqing Harry , Demsky Brian
Published: November 2020

Modern SAT solvers are extremely efficient at solving boolean satisfiability problems, enabling a wide spectrum of techniques for checking, verifying, and validating real-world programs. What remains challenging, though, is how to encode a domain problem (e.g., model checking) into a SAT formula because the same problem can have multiple distinct encodings, which can yield performance results that are orders-of-magnitude apart, regardless of the underlying solvers used. We develop Satune, a tool that can automatically synthesize SAT encoders for different problem domains. Satune employs a DSL that allows developers to express domain problems at a high level and a search algorithm that can effectively find efficient solutions. The search process is guided by observations made over example encodings and their performance for the domain and hence Satune can quickly synthesize a high-performance encoder by incorporating patterns from examples that yield good performance. A thorough evaluation with JMCR, SyPet, Dirk, Hexiom, Sudoku, and KillerSudoku demonstrates that Satune can easily synthesize high-performance encoders for different domains including model checking, synthesis, and games. These encoders generate constraint problems that are often several orders of magnitude faster to solve than the original encodings used by the tools.
CAMP: cost-aware multiparty session protocols
Authors: Castro-Perez David , Yoshida Nobuko
Published: November 2020

This paper presents CAMP, a new static performance analysis framework for message-passing concurrent and distributed systems, based on the theory of multiparty session types (MPST). Understanding the run-time performance of concurrent and distributed systems is of great importance for the identification of bottlenecks and optimisation opportunities. In the message-passing setting, these bottlenecks are generally communication overheads and synchronisation times. Despite its importance, reasoning about these intensional properties of software, such as performance, has received little attention, compared to verifying extensional properties, such as correctness. Behavioural protocol specifications based on sessions types capture not only extensional, but also intensional properties of concurrent and distributed systems. CAMP augments MPST with annotations of communication latency and local computation cost, defined as estimated execution times, that we use to extract cost equations from protocol descriptions. CAMP is also extendable to analyse asynchronous communication optimisation built on a recent advance of session type theories. We apply our tool to different existing benchmarks and use cases in the literature with a wide range of communication protocols, implemented in C, MPI-C, Scala, Go, and OCaml. Our benchmarks show that, in most of the cases, we predict an upper-bound on the real execution costs with < 15% error.
Automatic and efficient variability-aware lifting of functional programs
Authors: Shahin Ramy , Chechik Marsha
Published: November 2020

A software analysis is a computer program that takes some representation of a software product as input and produces some useful information about that product as output. A software product line encompasses
many
software product variants, and thus existing analyses can be applied to each of the product variations individually, but not to the entire product line as a whole. Enumerating all product variants and analyzing them one by one is usually intractable due to the combinatorial explosion of the number of product variants with respect to product line features. Several software analyses (e.g., type checkers, model checkers, data flow analyses) have been redesigned/re-implemented to support variability. This usually requires a lot of time and effort, and the variability-aware version of the analysis might have new errors/bugs that do not exist in the original one.

Given an analysis program written in a functional language based on PCF, in this paper we present two approaches to transforming (lifting) it into a semantically equivalent variability-aware analysis. A light-weight approach (referred to as
shallow lifting
) wraps the analysis program into a variability-aware version, exploring all combinations of its input arguments. Deep lifting, on the other hand, is a program rewriting mechanism where the syntactic constructs of the input program are rewritten into their variability-aware counterparts. Compositionally this results in an efficient program semantically equivalent to the input program, modulo variability.

We present the correctness criteria for functional program lifting, together with correctness proof sketches of shallow lifting. We evaluate our approach on a set of program analyses applied to the BusyBox C-language product line.
A sparse iteration space transformation framework for sparse tensor algebra
Authors: Senanayake Ryan , Hong Changwan , Wang Ziheng , Wilson Amalee , Chou Stephen , Kamil Shoaib , Amarasinghe Saman , Kjolstad Fredrik
Published: November 2020

We address the problem of optimizing sparse tensor algebra in a compiler and show how to define standard loop transformations---split, collapse, and reorder---on sparse iteration spaces. The key idea is to track the transformation functions that map the original iteration space to derived iteration spaces. These functions are needed by the code generator to emit code that maps coordinates between iteration spaces at runtime, since the coordinates in the sparse data structures remain in the original iteration space. We further demonstrate that derived iteration spaces can tile both the universe of coordinates and the subset of nonzero coordinates: the former is analogous to tiling dense iteration spaces, while the latter tiles sparse iteration spaces into statically load-balanced blocks of nonzeros. Tiling the space of nonzeros lets the generated code efficiently exploit heterogeneous compute resources such as threads, vector units, and GPUs.

We implement these concepts by extending the sparse iteration theory implementation in the TACO system. The associated scheduling API can be used by performance engineers or it can be the target of an automatic scheduling system. We outline one heuristic autoscheduling system, but other systems are possible. Using the scheduling API, we show how to optimize mixed sparse-dense tensor algebra expressions on CPUs and GPUs. Our results show that the sparse transformations are sufficient to generate code with competitive performance to hand-optimized implementations from the literature, while generalizing to all of the tensor algebra.
LiveDroid: identifying and preserving mobile app state in volatile runtime environments
Authors: Farooq Umar , Zhao Zhijia , Sridharan Manu , Neamtiu Iulian
Published: November 2020

Mobile operating systems, especially Android, expose apps to a volatile runtime environment. The app state that reflects past user interaction and system environment updates (e.g., battery status changes) can be destroyed implicitly, in response to runtime configuration changes (e.g., screen rotations) or memory pressure. Developers are therefore responsible for identifying app state affected by volatility and preserving it across app lifecycles. When handled inappropriately, the app may lose state or end up in an inconsistent state after a runtime configuration change or when users return to the app.

To free developers from this tedious and error-prone task, we propose a systematic solution, LiveDroid, which precisely identifies the
necessary
part of the app state that needs to be preserved across app lifecycles, and automatically saves and restores it. LiveDroid consists of: (i) a static analyzer that reasons about app source code and resource files to pinpoint the program variables and GUI properties that represent the necessary app state, and (ii) a runtime system that manages the state saving and recovering. We implemented LiveDroid as a plugin in Android Studio and a patching tool for APKs. Our evaluation shows that LiveDroid can be successfully applied to 966 Android apps. A focused study with 36 Android apps shows that LiveDroid identifies app state much more precisely than an existing solution that includes all mutable program variables but ignores GUI properties. As a result, on average, LiveDroid is able to reduce the costs of state saving and restoring by 16.6X (1.7X - 141.1X) and 9.5X (1.1X - 43.8X), respectively. Furthermore, compared with the manual state handling performed by developers, our analysis reveals a set of 46 issues due to incomplete state saving/restoring, all of which can be successfully eliminated by LiveDroid.
Eliminating abstraction overhead of Java stream pipelines using ahead-of-time program optimization
Authors: Møller Anders , Veileborg Oskar Haarklou
Published: November 2020

Java 8 introduced streams that allow developers to work with collections of data using functional-style operations. Streams are often used in pipelines of operations for processing the data elements, which leads to concise and elegant program code. However, the declarative data processing style comes at a cost. Compared to processing the data with traditional imperative language mechanisms, constructing stream pipelines requires extra heap objects and virtual method calls, which often results in significant run-time overheads.

In this work we investigate how to mitigate these overheads to enable processing data in the declarative style without sacrificing performance. We argue that ahead-of-time bytecode-to-bytecode transformation is a suitable approach to optimization of stream pipelines, and we present a static analysis that is designed to guide such transformations. Experimental results show a significant performance gain, and that the technique works for realistic stream pipelines. For 10 of 11 micro-benchmarks, the optimizer is able to produce bytecode that is as effective as hand-written imperative-style code. Additionally, 77% of 6879 stream pipelines found in real-world Java programs are optimized successfully.
FlowCFL: generalized type-based reachability analysis: graph reduction and equivalence of CFL-based and type-based reachability
Authors: Milanova Ana
Published: November 2020

Reachability analysis is a fundamental program analysis with a wide variety of applications. We present FlowCFL, a type-based reachability analysis that accounts for mutable heap data. The underlying semantics of FlowCFL is Context-Free-Language (CFL)-reachability.

We make three contributions. First, we define a dynamic semantics that captures the notion of flow commonly used in reachability analysis. Second, we establish correctness of CFL-reachability over graphs with inverse edges (inverse edges are necessary for the handling of mutable heap data). Our approach combines CFL-reachability with reference immutability to avoid the addition of certain inverse edges, which results in graph reduction and precision improvement. The key contribution of our work is the formal account of correctness, which extends to the case when inverse edges are removed. Third, we present a type-based reachability analysis and establish equivalence between a certain CFL-reachability analysis and the type-based analysis, thus proving correctness of the type-based analysis.
Taming type annotations in gradual typing
Authors: Campora John Peter , Chen Sheng
Published: November 2020

Gradual typing provides a methodology to integrate static and dynamic typing, harmonizing their often conflicting advantages in a single language. When a user wants to enjoy the advantages of static typing, most gradual languages require that they add type annotations. Many nontrivial tasks must be undertaken while adding type annotations, including understanding program behaviors and invariants. Unfortunately, if this is done incorrectly then the added type annotations can be wrong–leading to inconsistencies between the program and the type annotations. Gradual typing implementations detect such inconsistencies at runtime, raise cast errors, and generate messages. However, solely relying on such error messages for understanding and fixing inconsistencies and their resulting cast errors is often insufficient for multiple reasons. One reason is that while such messages cover inconsistencies in one execution path, fixing them often requires reconciling information from multiple paths. Another is that users may add many wrong type annotations that they later find difficult to identify and fix, when considering all added annotations.

Recent studies provide evidence that type annotations added during program migration are often wrong and that many programmers prefer compile-time warnings about wrong annotations. Motivated by these results, we develop exploratory typing to help with the static detection, understanding, and fixing of inconsistencies. The key idea of exploratory typing is that it systematically removes dynamic types and explores alternative types for static type annotations that can remedy inconsistencies. To demonstrate the feasibility of exploratory typing, we have implemented it in PyHound, which targets programs written in Reticulated Python, a gradual variant of Python. We have evaluated PyHound on a set of Python programs, and the evaluation results demonstrate that our idea can effectively detect inconsistencies in 98% of the tested programs and fix 93% of inconsistencies, significantly outperforming pytype, a widely used Python tool for enforcing type annotations.
Termination analysis for evolving programs: an incremental approach by reusing certified modules
Authors: He Fei , Han Jitao
Published: November 2020

Research on program termination has a long tradition. However, most of the existing techniques target a single program only. We propose in this paper an incremental termination analysis approach by reusing certified modules across different program versions. A transformation-based procedure is further developed to increase the reusability of certified modules. The proposed approach has wide applicability, applicable to various program changes. The proposed technique, to the best of our knowledge, represents a novel attempt to the termination analysis of evolving programs. We implemented the approach on top of Ultimate Automizer. Experimental results show dramatic improvement of our approach over the state-of-the-art tool.
Interactive synthesis of temporal specifications from examples and natural language
Authors: Gavran Ivan , Darulova Eva , Majumdar Rupak
Published: November 2020

Motivated by applications in robotics, we consider the task of synthesizing linear temporal logic (LTL) specifications based on examples and natural language descriptions. While LTL is a flexible, expressive, and unambiguous language to describe robotic tasks, it is often challenging for non-expert users. In this paper, we present an interactive method for synthesizing LTL specifications from a single example trace and a natural language description. The interaction is limited to showing a small number of behavioral examples to the user who decides whether or not they exhibit the original intent. Our approach generates candidate LTL specifications and distinguishing examples using an encoding into optimization modulo theories problems. Additionally, we use a grammar extension mechanism and a semantic parser to generalize synthesized specifications to parametric task descriptions for subsequent use. Our implementation in the tool LtlTalk starts with a domain-specific language that maps to a fragment of LTL and expands it through example-based user interactions, thus enabling natural language-like robot programming, while maintaining the expressive power and precision of a formal language. Our experiments show that the synthesis method is precise, quick, and asks only a few questions to the users, and we demonstrate in a case study how LtlTalk generalizes from the synthesized tasks to other, yet unseen, tasks.
Testing consensus implementations using communication closure
Authors: Drăgoi Cezara , Enea Constantin , Ozkan Burcu Kulahcioglu , Majumdar Rupak , Niksic Filip
Published: November 2020

Large scale production distributed systems are difficult to design and test. Correctness must be ensured when processes run asynchronously, at arbitrary rates relative to each other, and in the presence of failures, e.g., process crashes or message losses. These conditions create a huge space of executions that is difficult to explore in a principled way. Current testing techniques focus on systematic or randomized exploration of all executions of an implementation while treating the implemented algorithms as black boxes. On the other hand, proofs of correctness of many of the underlying algorithms often exploit semantic properties that reduce reasoning about correctness to a subset of behaviors. For example, the
communication-closure
property, used in many proofs of distributed consensus algorithms, shows that every asynchronous execution of the algorithm is equivalent to a
lossy synchronous
execution, thus reducing the burden of proof to only that subset. In a lossy synchronous execution, processes execute in lock-step rounds, and messages are either received in the same round or lost forever—such executions form a small subset of all asynchronous ones.

We formulate the
communication-closure hypothesis
, which states that bugs in implementations of distributed consensus algorithms will already manifest in lossy synchronous executions and present a testing algorithm based on this hypothesis. We prioritize the search space based on a bound on the number of failures in the execution and the rate at which these failures are recovered. We show that a random testing algorithm based on sampling lossy synchronous executions can empirically find a number of bugs—including previously unknown ones—in production distributed systems such as Zookeeper, Cassandra, and Ratis, and also produce more understandable bug traces.