Samin Ishtiaq

The semantics of power and ARM multiprocessor machine code

We develop a rigorous semantics for Power and ARM multiprocessor programs, including their relaxed memory model and the behaviour of reasonable fragments of their instruction sets. The semantics is mechanised in the HOL proof assistant. This should provide a good basis for informal reasoning and formal verification of low-level code for these weakly consistent architectures, and, together with our x86 semantics, for the design and compilation of high-level concurrent languages.

SLAYER: memory safety for systems-level code

SLAyer is a program analysis tool designed to automatically prove memory safety of industrial systems code. In this paper we describe SLAyers implementation, and its application to Windows device drivers. This paper accompanies the first release of SLAYER.

Semantic analysis of pointer aliasing, allocation and disposal in Hoare logic

Bornat has recently described an approach to reasoning about pointers, building on work of Morris. Here we describe a semantics that validates the approach, and use it to help devise axioms for operations that allocate and dispose of memory.

A Relevant Analysis of Natural Deduction

Linear and other relevant logics have been studied widely in mathematical, philosophical and computational logic. We describe a logical framework, RLF, for defining natural deduction presentations of such logics. RLF consists in a language togeth er, in a manner similar to that of Harper, Honsell and Plotkin’s LF, with a representation mec hanism: the language of RLF is the λΛ-calculus; the representation mechanism is judgements-as -type , developed for relevant logics. The λΛ-calculus type theory is a first-order dependent type theory with two kinds of dependent function spaces: a linear one and an intuitionistic one. We study a natural deduction presentation of the type theory and establish the required p oof-theoretic meta-theory. The RLF framework is a conservative extension of LF. We show that RLF uniformly encodes (fragments of) intuitionistic linear logic, Curry’sλI -calculus and ML with references. We describe the Curry-Howard-de Bruijn correspondence of t heλΛ-calculus with a structural fragment of O’Hearn and Pym’s logic BI of bunched implicatio ns. We show that a categorical semantics of the λΛ-calculus is given by Kripke resource models, which are a monoid-indexed set of Kripke functors. The index ing monoid is seen as providing an account of resource consumption. The models can be seen as a indexed formulation of categorical models of Read’s bunches. We also study a Gentzenized version of the λΛ-calculus, and prove a cut-elimination theorem for it. Submitted for the degree of Doctor of Philosophy Queen Mary and Westfield College University of London April, 1999

BMA: visual tool for modeling and analyzing biological networks

BioModel Analyzer (bma) is a tool for modeling and analyzing biological networks. Designed with a lightweight graphical user interface, the tool facilitates usage for biologists with no previous knowledge in programming or formal methods. The current implementation analyzes systems to establish stabilization. The results of the analysis--whether they be proofs or counterexamples--are represented visually. This paper describes the approach to modeling used in bma and also notes soon-to-be-released extensions to the tool.

T2: Temporal Property Verification

We present the open-source tool T2, the first public release from the TERMINATOR projecti??[9]. T2 has been extended over the past decade to support automatic temporal-logic proving techniques and to handle a general class of user-provided liveness and safety properties. Input can be provided in a native format and in C, via the support of the LLVM compiler framework. We briefly discuss T2s architecture, its underlying techniques, and conclude with an experimental illustration of its competitiveness and directions for future extensions.

SeLoger: a tool for graph-based reasoning in separation logic

This paper introduces the tool SeLoger, which is a reasoner for satisfiability and entailment in a fragment of separation logic with pointers and linked lists. SeLoger builds upon and extends graph-based algorithms that have recently been introduced in order to settle both decision problems in polynomial time. Running SeLoger on standard benchmarks shows that the tool outperforms current state-of-the-art tools by orders of magnitude.

"Share and Enjoy"""": Publishing Useful and Usable Scientific Models

The reproduction and replication of reported scientific results is a hot topic within the academic community. The retraction of numerous studies from a wide range of disciplines, from climate science to bioscience, has drawn the focus of many commentators, but there exists a wider socio-cultural problem that pervades the scientific community. Sharing code, data and models often requires extra effort, this is currently seen as a significant overhead that may not be worth the time investment. Automated systems, which allow easy reproduction of results, offer the potential to incentives a culture change and drive the adoption of new techniques to improve the efficiency of scientific exploration. In this paper, we discuss the value of improved access and sharing of the two key types of results arising from work done in the computational sciences: models and algorithms. We propose the development of an integrated cloud-based system underpinning computational science, linking together software and data repositories, tool chains, workflows and outputs, providing a seamless automated infrastructure for the verification and validation of scientific models and in particular, performance benchmarks.

Finding Instability in Biological Models

The stability of biological models is an important test for establishing their soundness and accuracy. Stability in biological systems represents the ability of a robust system to always return to homeostasis. In recent work, modular approaches for proving stability have been found to be swift and scalable. If stability is however not proved, the currently available techniques apply an exhaustive search through the unstable state space to find loops. This search is frequently prohibitively computationally expensive, limiting its usefulness. Here we present a new modular approach eliminating the need for an exhaustive search for loops. Using models of biological systems we show that the technique finds loops significantly faster than brute force approaches. Furthermore, for a subset of stable systems which are resistant to modular proofs, we observe a speed up of up to 3 orders of magnitude as the exhaustive searches for loops which cause instability are avoided. With our new procedure we are able to prove instability and stability in a number of realistic biological models, including adaptation in bacterial chemotaxis, the lambda phage lysogeny/lysis switch, voltage gated channel opening and cAMP oscillations in the slime mold Dictyostelium discoideum. This new approach will support the development of new tools for biomedicine.

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.