27 research outputs found
Lazy Decomposition for Distributed Decision Procedures
The increasing popularity of automated tools for software and hardware
verification puts ever increasing demands on the underlying decision
procedures. This paper presents a framework for distributed decision procedures
(for first-order problems) based on Craig interpolation. Formulas are
distributed in a lazy fashion, i.e., without the use of costly decomposition
algorithms. Potential models which are shown to be incorrect are reconciled
through the use of Craig interpolants. Experimental results on challenging
propositional satisfiability problems indicate that our method is able to
outperform traditional solving techniques even without the use of additional
resources.Comment: In Proceedings PDMC 2011, arXiv:1111.006
SCNS: a graphical tool for reconstructing executable regulatory networks from single-cell genomic data.
Background
Reconstruction of executable mechanistic models from single-cell gene expression data represents a powerful approach to understanding developmental and disease processes. New ambitious efforts like the Human Cell Atlas will soon lead to an explosion of data with potential for uncovering and understanding the regulatory networks which underlie the behaviour of all human cells. In order to take advantage of this data, however, there is a need for general-purpose, user-friendly and efficient computational tools that can be readily used by biologists who do not have specialist computer science knowledge.
Results
The Single Cell Network Synthesis toolkit (SCNS) is a general-purpose computational tool for the reconstruction and analysis of executable models from single-cell gene expression data. Through a graphical user interface, SCNS takes single-cell qPCR or RNA-sequencing data taken across a time course, and searches for logical rules that drive transitions from early cell states towards late cell states. Because the resulting reconstructed models are executable, they can be used to make predictions about the effect of specific gene perturbations on the generation of specific lineages.
Conclusions
SCNS should be of broad interest to the growing number of researchers working in single-cell genomics and will help further facilitate the generation of valuable mechanistic insights into developmental, homeostatic and disease processes.Research in the Gottgens lab is supported by infrastructure support funding from the Wellcome Trust to the Wellcome Trust and MRC Cambridge Stem Cell Institute. Steven Woodhouse is a postdoctoral researcher supported by Microsoft Researc
Ranking function synthesis for bit-vector relations
Abstract. Ranking function synthesis is a key aspect to the success of modern termination provers for imperative programs. While it is wellknown how to generate linear ranking functions for relations over (mathematical) integers or rationals, efficient synthesis of ranking functions for machine-level integers (bit-vectors) is an open problem. This is particularly relevant for the verification of low-level code. We propose several novel algorithms to generate ranking functions for relations over machine integers: a complete method based on a reduction to Presburger arithmetic, and a template-matching approach for predefined classes of ranking functions based on reduction to SAT-and QBF-solving. The utility of our algorithms is demonstrated on examples drawn from Windows device drivers
Confidential Consortium Framework: Secure Multiparty Applications with Confidentiality, Integrity, and High Availability
Confidentiality, integrity protection, and high availability, abbreviated to
CIA, are essential properties for trustworthy data systems. The rise of cloud
computing and the growing demand for multiparty applications however means that
building modern CIA systems is more challenging than ever. In response, we
present the Confidential Consortium Framework (CCF), a general-purpose
foundation for developing secure stateful CIA applications. CCF combines
centralized compute with decentralized trust, supporting deployment on
untrusted cloud infrastructure and transparent governance by mutually untrusted
parties. CCF leverages hardware-based trusted execution environments for
remotely verifiable confidentiality and code integrity. This is coupled with
state machine replication backed by an auditable immutable ledger for data
integrity and high availability. CCF enables each service to bring its own
application logic, custom multiparty governance model, and deployment scenario,
decoupling the operators of nodes from the consortium that governs them. CCF is
open-source and available now at https://github.com/microsoft/CCF.Comment: 16 pages, 9 figures. To appear in the Proceedings of the VLDB
Endowment, Volume 1
Approximations for Model Construction
We consider the problem of efficiently computing models for satisfiable constraints, in the presence of complex background theories such as floating-point arithmetic. Model construction has various applications, for instance the automatic generation of test inputs. It is well-known that naive encoding of constraints into simpler theories (for instance, bit-vectors or propositional logic) can lead to a drastic increase in size, and be unsatisfactory in terms of memory and runtime needed for model construction. We define a framework for systematic application of approximations in order to speed up model construction. Our method is more general than previous techniques in the sense that approximations that are neither under- nor over-approximations can be used, and shows promising results in practice.UPMAR