Evaluating QBF Solvers: Quantifier Alternations Matter

We present an experimental study of the effects of quantifier alternations on the evaluation of quantified Boolean formula (QBF) solvers. The number of quantifier alternations in a QBF in prenex conjunctive normal form (PCNF) is directly related to the theoretical hardness of the respective QBF satisfiability problem in the polynomial hierarchy. We show empirically that the performance of solvers based on different solving paradigms substantially varies depending on the numbers of alternations in PCNFs. In related theoretical work, quantifier alternations have become the focus of understanding the strengths and weaknesses of various QBF proof systems implemented in solvers. Our results motivate the development of methods to evaluate orthogonal solving paradigms by taking quantifier alternations into account. This is necessary to showcase the broad range of existing QBF solving paradigms for practical QBF applications. Moreover, we highlight the potential of combining different approaches and QBF proof systems in solvers.Comment: preprint of a paper to be published at CP 2018, LNCS, Springer, including appendi

On QBF Proofs and Preprocessing

QBFs (quantified boolean formulas), which are a superset of propositional formulas, provide a canonical representation for PSPACE problems. To overcome the inherent complexity of QBF, significant effort has been invested in developing QBF solvers as well as the underlying proof systems. At the same time, formula preprocessing is crucial for the application of QBF solvers. This paper focuses on a missing link in currently-available technology: How to obtain a certificate (e.g. proof) for a formula that had been preprocessed before it was given to a solver? The paper targets a suite of commonly-used preprocessing techniques and shows how to reconstruct certificates for them. On the negative side, the paper discusses certain limitations of the currently-used proof systems in the light of preprocessing. The presented techniques were implemented and evaluated in the state-of-the-art QBF preprocessor bloqqer.Comment: LPAR 201

Exploiting the Enumeration of All Feature Model Configurations

.Feature models are widely used to encode the configurations of a software product line in terms of mandatory, optional and exclusive features as well as propositional constraints over the features. Numerous computationally expensive procedures have been developed to model check, test, configure, debug, or compute relevant information of feature models. In this paper we explore the possible improvement of relying on the enumeration of all configurations when performing automated analysis operations. We tackle the challenge of how to scale the existing enumeration techniques by relying on distributed computing. We show that the use of distributed computing techniques might offer practical solutions to previously unsolvable problems and opens new perspectives for the automated analysis of software product lines.Junta de Andalucía P12-TIC-1867Ministerio de Economía y Competitividad TIN2015- 70560-

DepQBF 6.0: A Search-Based QBF Solver Beyond Traditional QCDCL

We present the latest major release version 6.0 of the quantified Boolean formula (QBF) solver DepQBF, which is based on QCDCL. QCDCL is an extension of the conflict-driven clause learning (CDCL) paradigm implemented in state of the art propositional satisfiability (SAT) solvers. The Q-resolution calculus (QRES) is a QBF proof system which underlies QCDCL. QCDCL solvers can produce QRES proofs of QBFs in prenex conjunctive normal form (PCNF) as a byproduct of the solving process. In contrast to traditional QCDCL based on QRES, DepQBF 6.0 implements a variant of QCDCL which is based on a generalization of QRES. This generalization is due to a set of additional axioms and leaves the original Q-resolution rules unchanged. The generalization of QRES enables QCDCL to potentially produce exponentially shorter proofs than the traditional variant. We present an overview of the features implemented in DepQBF and report on experimental results which demonstrate the effectiveness of generalized QRES in QCDCL.Comment: 12 pages + appendix; to appear in the proceedings of CADE-26, LNCS, Springer, 201

QRAT+: Generalizing QRAT by a More Powerful QBF Redundancy Property

The QRAT (quantified resolution asymmetric tautology) proof system simulates virtually all inference rules applied in state of the art quantified Boolean formula (QBF) reasoning tools. It consists of rules to rewrite a QBF by adding and deleting clauses and universal literals that have a certain redundancy property. To check for this redundancy property in QRAT, propositional unit propagation (UP) is applied to the quantifier free, i.e., propositional part of the QBF. We generalize the redundancy property in the QRAT system by QBF specific UP (QUP). QUP extends UP by the universal reduction operation to eliminate universal literals from clauses. We apply QUP to an abstraction of the QBF where certain universal quantifiers are converted into existential ones. This way, we obtain a generalization of QRAT we call QRAT+. The redundancy property in QRAT+ based on QUP is more powerful than the one in QRAT based on UP. We report on proof theoretical improvements and experimental results to illustrate the benefits of QRAT+ for QBF preprocessing.Comment: preprint of a paper to be published at IJCAR 2018, LNCS, Springer, including appendi

aspcud: A Linux Package Configuration Tool Based on Answer Set Programming

We present the Linux package configuration tool aspcud based on Answer Set Programming. In particular, we detail aspcud's preprocessor turning a CUDF specification into a set of logical facts.Comment: In Proceedings LoCoCo 2011, arXiv:1108.609

Evaluation of the impact of oximeter averaging times on automated FiO2 control in routine NICU care: a randomized cross-over study

ObjectiveChanges in oximeter averaging times have been noted to affect alarm settings. Automated algorithms (A-FiO2) assess FiO2 faster than oximeter averaging, potentially impacting their effectiveness.MethodsIn a single NICU routinely using 15 fabian-PRICO A-FiO2 systems, neonates were randomly exposed to SpO2 averaging time settings switched every 12 h among short (2–4 s), medium (10 s), and long (16 s) oximeter averaging times for the entire duration of their A-FiO2 exposure. Primary endpoints were the percent time in the set SpO2 target range (dependent on PMA), SpO2 < 80%, and SpO2 > 98%, excluding FiO2 = 0.21.ResultsTen VLBW neonates were enrolled over 11 months. At entry, they were 17 days old (IQR: 14–19), with an adjusted gestational age of 29 weeks (IQR: 27–30). The study included data from 272 days of A-FiO2 control (34% short, 32% medium, and 34% long). Respiratory support was predominantly non-invasive (53% NCPAP, 40% HFNC, and 6% NIPPV). The aggregate SpO2 exposure levels were 67% (IQR: 55–82) in the target range, 5.4% (IQR: 2.0–10) with SpO2 < 80%, and 1.2% (IQR: 0.4–3.1) with SpO2 > 98%. There were no differences in the target range time between the SpO2 averaging time settings. There were differences at the SpO2 extremes (p ≤ 0.001). The medium and long averaging were both lower than the short, with the difference larger than predicted. Multivariate analysis revealed that these findings were independent of subject, ventilation mode, target range, and overall stability.ConclusionsThis A-FiO2 algorithm is effective regardless of the SpO2 averaging time setting. There is an advantage to the longer settings, which suggest an interaction with the controller

Shortening QBF Proofs with Dependency Schemes

We provide the first proof complexity results for QBF dependency calculi. By showing that the reflexive resolution path dependency scheme admits exponentially shorter Q-resolution proofs on a known family of instances, we answer a question first posed by Slivovsky and Szeider in 2014 [30]. Further, we conceive a method of QBF solving in which dependency recomputation is utilised as a form of inprocessing. Formalising this notion, we introduce a new calculus in which a dependency scheme is applied dynamically. We demonstrate the further potential of this approach beyond that of the existing static system with an exponential separation

Less is more: Antibiotics at the beginning of life

Antibiotic exposure at the beginning of life can lead to increased antimicrobial resistance and perturbations of the developing microbiome. Early-life microbiome disruption increases the risks of developing chronic diseases later in life. Fear of missing evolving neonatal sepsis is the key driver for antibiotic overtreatment early in life. Bias (a systemic deviation towards overtreatment) and noise (a random scatter) affect the decision-making process. In this perspective, we advocate for a factual approach quantifying the burden of treatment in relation to the burden of disease balancing antimicrobial stewardship and effective sepsis management