A Relevant Analysis of Natural Deduction

Submitted for the degree of Doctor of Philosoph

Prenex Separation Logic with One Selector Field

International audienceWe show that infinite satisfiability can be reduced to finite satisfiabil-ity for all prenex formulas of Separation Logic with k ≥ 1 selector fields (SL k). This fact entails the decidability of the finite and infinite satisfiability problems for the class of prenex formulas of SL 1 , by reduction to the first-order theory of a single unary function symbol and an arbitrary number of unary predicate symbols. We also prove that the complexity of this fragment is not elementary recursive, by reduction from the first-order theory of one unary function symbol. Finally, we prove that the Bernays-Schönfinkel-Ramsey fragment of prenex SL 1 formulas with quantifier prefix in the language ∃ * ∀ * is PSPACE-complete

Drug target optimization in chronic myeloid leukemia using innovative computational platform.

Chronic Myeloid Leukemia (CML) represents a paradigm for the wider cancer field. Despite the fact that tyrosine kinase inhibitors have established targeted molecular therapy in CML, patients often face the risk of developing drug resistance, caused by mutations and/or activation of alternative cellular pathways. To optimize drug development, one needs to systematically test all possible combinations of drug targets within the genetic network that regulates the disease. The BioModelAnalyzer (BMA) is a user-friendly computational tool that allows us to do exactly that. We used BMA to build a CML network-model composed of 54 nodes linked by 104 interactions that encapsulates experimental data collected from 160 publications. While previous studies were limited by their focus on a single pathway or cellular process, our executable model allowed us to probe dynamic interactions between multiple pathways and cellular outcomes, suggest new combinatorial therapeutic targets, and highlight previously unexplored sensitivities to Interleukin-3.We would like to thank the members of the Fisher laboratory, in particular to Gavin Smyth and Caroline Dahl for their help with the BMA development, and Alex Hajnal for valuable comments on the manuscript and insightful discussions. Research in BG laboratory is supported by the Medical Research Council, Leukaemia and Lymphoma Research, The Leukemia and Lymphoma Society, Microsoft Research and core support grants by the Wellcome Trust to the Cambridge Institute for Medical Research and Wellcome Trust-MRC Cambridge Stem Cell Institute.This is the final published version. It was originally published in Scientific Reports 5: 8190. DOI: 10.1038/srep08190

Iterative Compression of End-to-End ASR Model using AutoML

Increasing demand for on-device Automatic Speech Recognition (ASR) systems has resulted in renewed interests in developing automatic model compression techniques. Past research have shown that AutoML-based Low Rank Factorization (LRF) technique, when applied to an end-to-end Encoder-Attention-Decoder style ASR model, can achieve a speedup of up to 3.7x, outperforming laborious manual rank-selection approaches. However, we show that current AutoML-based search techniques only work up to a certain compression level, beyond which they fail to produce compressed models with acceptable word error rates (WER). In this work, we propose an iterative AutoML-based LRF approach that achieves over 5x compression without degrading the WER, thereby advancing the state-of-the-art in ASR compression

Bringing LTL Model Checking to Biologists

Abstract The BioModelAnalyzer (BMA) is a web based tool for the development of discrete models of biological systems. Through a graphical user interface, it allows rapid development of complex models of gene and protein interaction networks and stability analysis without requiring users to be proficient computer programmers. Whilst stability is a useful specification for testing many systems, testing temporal specifications in BMA presently requires the user to perform simulations. Here we describe the LTL module, which includes a graphical and natural language interfaces to testing LTL queries. The graphical interface allows for graphical construction of the queries and presents results visually in keeping with the current style of BMA. The Natural language interface complements the graphical interface by allowing a gentler introduction to formal logic and exposing educational resources

Bringing LTL Model Checking to Biologists

Abstract The BioModelAnalyzer (BMA) is a web based tool for the development of discrete models of biological systems. Through a graphical user interface, it allows rapid development of complex models of gene and protein interaction networks and stability analysis without requiring users to be proficient computer programmers. Whilst stability is a useful specification for testing many systems, testing temporal specifications in BMA presently requires the user to perform simulations. Here we describe the LTL module, which includes a graphical and natural language interfaces to testing LTL queries. The graphical interface allows for graphical construction of the queries and presents results visually in keeping with the current style of BMA. The Natural language interface complements the graphical interface by allowing a gentler introduction to formal logic and exposing educational resources

Everest: Towards a Verified, Drop-in Replacement of HTTPS

The HTTPS ecosystem is the foundation on which Internet security is built. At the heart of this ecosystem is the Transport Layer Security (TLS) protocol, which in turn uses the X.509 public-key infrastructure and numerous cryptographic constructions and algorithms. Unfortunately, this ecosystem is extremely brittle, with headline-grabbing attacks and emergency patches many times a year. We describe our ongoing efforts in Everest (The Everest VERified End-to-end Secure Transport) a project that aims to build and deploy a verified version of TLS and other components of HTTPS, replacing the current infrastructure with proven, secure software. Aiming both at full verification and usability, we conduct high-level code-based, game-playing proofs of security on cryptographic implementations that yield efficient, deployable code, at the level of C and assembly. Concretely, we use F*, a dependently typed language for programming, meta-programming, and proving at a high level, while relying on low-level DSLs embedded within F* for programming low-level components when necessary for performance and, sometimes, side-channel resistance. To compose the pieces, we compile all our code to source-like C and assembly, suitable for deployment and integration with existing code bases, as well as audit by independent security experts. Our main results so far include (1) the design of Low*, a subset of F* designed for C-like imperative programming but with high-level verification support, and KreMLin, a compiler that extracts Low* programs to C; (2) an implementation of the TLS-1.3 record layer in Low*, together with a proof of its concrete cryptographic security; (3) Vale, a new DSL for verified assembly language, and several optimized cryptographic primitives proven functionally correct and side-channel resistant. In an early deployment, all our verified software is integrated and deployed within libcurl, a widely used library of networking protocols