Formal Availability Analysis using Theorem Proving

Availability analysis is used to assess the possible failures and their restoration process for a given system. This analysis involves the calculation of instantaneous and steady-state availabilities of the individual system components and the usage of this information along with the commonly used availability modeling techniques, such as Availability Block Diagrams (ABD) and Fault Trees (FTs) to determine the system-level availability. Traditionally, availability analyses are conducted using paper-and-pencil methods and simulation tools but they cannot ascertain absolute correctness due to their inaccuracy limitations. As a complementary approach, we propose to use the higher-order-logic theorem prover HOL4 to conduct the availability analysis of safety-critical systems. For this purpose, we present a higher-order-logic formalization of instantaneous and steady-state availability, ABD configurations and generic unavailability FT gates. For illustration purposes, these formalizations are utilized to conduct formal availability analysis of a satellite solar array, which is used as the main source of power for the Dong Fang Hong-3 (DFH-3) satellite.Comment: 16 pages. arXiv admin note: text overlap with arXiv:1505.0264

Formalization of Discrete-time Markov Chains in HOL

Markov chains are extensively used in the modeling and analysis of engineering and scientific problems which can be expressed as random processes with the memoryless property. Usually, paper-and-pencil proofs, simulation or computer algebra software are used to analyze Markovian models. However, these techniques either are not scalable or do not guarantee accurate results, which are vital in safety-critical systems. To improve the accuracy of the analysis, probabilistic model checking has been recently proposed to formally analyze Markovian systems. However, model checking suffers from the inherent state-explosion problem and thus has a very limited scope in terms of analyzing Markovian models.\newline \indent In order to overcome the above mentioned limitations, this thesis advocates the usage of higher-order-logic theorem proving for conducting the analysis of Markov chains. We present the higher-order-logic formalization of Discrete-time Markov Chains with finite number of discrete states. We also verify some of their most widely used properties using a theorem prover. These foundations allow us to formally express and reason about Markov chains within the sound core of a theorem prover and thus attain precise results. Moreover, by building upon these foundational results, this thesis also presents the formalization of classified discrete-time Markov chains and hidden Markov chains in higher-order logic. These are widely used concepts in the analysis of Markovian models and thus allow us to tackle the formal analysis of a wide range of engineering and scientific systems. For illustration purposes, the thesis also presents some applications including a binary communication channel, the automatic mail quality measurement (AMQM) protocol, a DNA sequence, a least recently used (LRU) stack model and the birth-death process

Formal Reasoning About Finite-State Discrete-Time Markov Chains in HOL

Markov chains are extensively used in modeling different aspects of engineering and scientific systems, such as performance of algorithms and reliability of systems. Different techniques have been developed for analyzing Markovian models, for example, Markov Chain Monte Carlo based simulation, Markov Analyzer, and more recently probabilistic model-checking. However, these techniques either do not guarantee accurate analysis or are not scalable. Higher-order-logic theorem proving is a formal method that has the ability to overcome the above mentioned limitations. However, it is not mature enough to handle all sorts of Markovian models. In this paper, we propose a formalization of Discrete-Time Markov Chain (DTMC) that facilitates formal reasoning about time-homogeneous finite-state discrete-time Markov chain. In particular, we provide a formal verification on some of its important properties, such as joint probabilities, Chapman-Kolmogorov equation, reversibility property, using higher-order logic. To demonstrate the usefulness of our work, we analyze two applications: a simplified binary communication channel and the Automatic Mail Quality Measurement protocol

Formalization of Continuous Time Markov Chains with Applications in Queueing Theory

The performance analysis of engineering systems have become very critical due to their usage in safety and mission critical domains such as military and biomedical devices. Such an analysis is often carried out based on the Markovian (or Markov Chains based) models of underlying software and hardware components. Furthermore, some important properties can only be captured by queueing theory which involves Markov Chains with continuous time behavior. Classically, the analysis of such models has been performed using paper-and-pencil based proofs and computer simulation, both of which cannot provide perfectly accurate results due to the error-prone nature of manual proofs and the non-exhaustive nature of simulation. Recently, model checking based formal methods have also been used to analyze Markovian and queuing systems. However, such an approach is only applicable for small systems and cannot certify generic properties due to the sate-space explosion problem. In this thesis, we propose to use higher-order-logic theorem proving as a complementary approach to conduct the formal analysis of queueing systems. To this aim, we present the higher-order-logic formalization of the Poisson process which is the foremost step to model queueing systems. We also verify some of its classical properties such as exponentially distributed inter-arrival time, memoryless property and independent and stationary increments. Moreover, we used the formalization of the Poisson process to model and verify the error probability of a generic optical communication system. Then we present the formalization of Continuous-Time Markov Chains along with the Birth-Death process. Lastly, we demonstrate the utilization of our developed infrastructure by presenting the formalization of an M/M/1 queue which is widely used to model telecommunication systems. We also formally verified the generic result about the average waiting time for any given queue

Foundational (co)datatypes and (co)recursion for higher-order logic

We describe a line of work that started in 2011 towards enriching Isabelle/HOL's language with coinductive datatypes, which allow infinite values, and with a more expressive notion of inductive datatype than previously supported by any system based on higher-order logic. These (co)datatypes are complemented by definitional principles for (co)recursive functions and reasoning principles for (co)induction. In contrast with other systems offering codatatypes, no additional axioms or logic extensions are necessary with our approach

Probabilistic Analysis of Wireless Systems Using Theorem Proving

Probabilistic techniques play a major role in the design and analysis of wirelesssystems as they contain a significant amount of random or unpredictable components. Traditionally, computer simulation techniques are used to perform probabilisticanalysis of wirelesssystems but they provide inaccurate results and usually require enormous amount of CPU time in order to attain reasonable estimates. To overcome these limitations, we propose to use a higher-order-logic theorem prover (HOL) for the analysis of wirelesssystems. The paper presents a concise description of the formal foundations required to conduct the analysis of a wirelesssystem in a theorem prover, such as the higher-order-logic modeling of random variables and the verification of their corresponding probabilistic and statistical properties in a theorem prover. In order to illustrate the utilization and effectiveness of the proposed idea for handling real-world wirelesssystemanalysis problems, we present an analysis of the automated repeat request (ARQ) mechanism at the logic link control (LLC) layer of the General Packet Radio Service (GPRS), which is a packet oriented mobile data service available to the users of Global System for Mobile Communications (GSM)

Formalization of Measure Theory and Lebesgue Integration for Probabilistic Analysis in HOL

Dynamic systems that exhibit probabilistic behavior represent a large class of man-made systems such as communication networks, air traffic control, and other mission-critical systems. Evaluation of quantitative issues like performance and dependability of these systems is of paramount importance. In this paper, we propose a generalized methodology to formally reason about probabilistic systems within a theorem prover. We present a formalization of measure theory in the HOL theorem prover and use it to formalize basic concepts from the theory of probability. We also use the Lebesgue integration to formalize statistical properties of random variables. To illustrate the practical effectiveness of our methodology, we formally prove classical results from the theories of probability and information and use them in a data compression application in HOL

Information-Theoretic Analysis using Theorem Proving

Information theory is widely used for analyzing a wide range of scientific and engineering problems, including cryptography, neurobiology, quantum computing, plagiarism detection and other forms of data analysis. Despite the safety-critical nature of some of these applications, most of the information-theoretic analysis is done using informal techniques, mainly computer simulation and paper-and-pencil analysis, and thus cannot be completely relied upon. The unreliable nature of the produced results poses a serious problem in safety-critical applications and may result in heavy financial losses or even the loss of human life. In order to overcome the inaccuracy limitations of these techniques, this thesis proposes to conduct the analysis within the trusted kernel of a higher-order-logic (HOL) theorem prover. For this purpose, we provide HOL formalizations of the fundamental theories of measure, Lebesgue integration and probability and use them to formalize some of the most widely used information-theoretic principles. We use the Kullback-Leibler divergence as a unified measure of information which is in turn used to define the main measures of information like the Shannon entropy, mutual information and conditional mutual information. Furthermore, we introduce two new measures of information leakage, namely the information leakage degree and the conditional information leakage degree and compare them with existing measures. We illustrate the usefulness of the proposed framework by tackling various applications including the performance analysis of a communication encoder used in the proof of the Shannon source coding theorem, the quantitative analysis of privacy properties of a digital communications mixer and the one-time pad encryption system using information-theoretic measures