Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userRESID: A Practical Stochastic Model for Software Reliability
150
0
0.0
(
0
)
Authors
Arnab Chakraborty
Ask ChatGPT about the research
No Arabic abstract
A new approach called RESID is proposed in this paper for estimating reliability of a software allowing for imperfect debugging. Unlike earlier approaches based on counting number of bugs or modelling inter-failure time gaps, RESID focuses on the probability of bugginess of different parts of a program buggy. This perspective allows an easy way to incorporate the structure of the software under test, as well as imperfect debugging. One main design objective behind RESID is ease of implementation in practical scenarios.
rate research
Read More
We consider a network consisting of $n$ components (links or nodes) and assume that the network has two states, up and down. We further suppose that the network is subject to shocks that appear according to a counting process and that each shock may lead to the component failures. Under some assumptions on the shock occurrences, we present a new variant of the notion of signature which we call it t-signature. Then t-signature based mixture representations for the reliability function of the network are obtained. Several stochastic properties of the network lifetime are investigated. In particular, under the assumption that the number of failures at each shock follows a binomial distribution and the process of shocks is non-homogeneous Poisson process, explicit form of the network reliability is derived and its aging properties are explored. Several examples are also provided
Software debloating is an emerging field of study aimed at improving the security and performance of software by removing excess library code and features that are not needed by the end user (called bloat). Software bloat is pervasive, and several debloating techniques have been proposed to address this problem. While these techniques are effective at reducing bloat, they are not practical for the average user, risk creating unsound programs and introducing vulnerabilities, and are not well suited for debloating complex software such as network protocol implementations. In this paper, we propose CARVE, a simple yet effective security-focused debloating technique that overcomes these limitations. CARVE employs static source code annotation to map software features source code, eliminating the need for advanced software analysis during debloating and reducing the overall level of technical sophistication required by the user. CARVE surpasses existing techniques by introducing debloating with replacement, a technique capable of preserving software interoperability and mitigating the risk of creating an unsound program or introducing a vulnerability. We evaluate CARVE in 12 debloating scenarios and demonstrate security and performance improvements that meet or exceed those of existing techniques.
Software defined networking (SDN) has been adopted to enforce the security of large-scale and complex networks because of its programmable, abstract, centralized intelligent control and global and real-time traffic view. However, the current SDN-based security enforcement mechanisms require network managers to fully understand the underlying configurations of network. Facing the increasingly complex and huge SDN networks, we urgently need a novel security policy management mechanism which can be completely transparent to any underlying information. That is it can permit network managers to define upper-level security policies without containing any underlying information of network, and by means of model transformation system, these upper-level security policies can be transformed into their corresponding lower-level policies containing underlying information automatically. Moreover, it should ensure system model updated by the generated lower-level policies can hold all of security properties defined in upper-level policies. Based on these insights, we propose a security policy model transformation and verification approach for SDN in this paper. We first present the formal definition of a security policy model (SPM) which can be used to specify the security policies used in SDN. Then, we propose a model transformation system based on SDN system model and mapping rules, which can enable network managers to convert SPM model into corresponding underlying network configuration policies automatically, i.e., flow table model (FTM). In order to verify SDN system model updated by the generated FTM models can hold the security properties defined in SPM models, we design a security policy verification system based on model checking. Finally, we utilize a comprehensive case to illustrate the feasibility of the proposed approach.
This paper presents novel extensions and applications of the UPPAAL-SMC model checker. The extensions allow for statistical model checking of stochastic hybrid systems. We show how our race-based stochastic semantics extends to networks of hybrid systems, and indicate the integration technique applied for implementing this semantics in the UPPAAL-SMC simulation engine. We report on two applications of the resulting tool-set coming from systems biology and energy aware buildings.
Functional Magnetic Resonance Imaging (fMRI) maps cerebral activation in response to stimuli but this activation is often difficult to detect, especially in low-signal contexts and single-subject studies. Accurate activation detection can be guided by the fact that very few voxels are, in reality, truly activated and that activated voxels are spatially localized, but it is challenging to incorporate both these facts. We provide a computationally feasible and methodologically sound model-based approach, implemented in the R package MixfMRI, that bounds the a priori expected proportion of activated voxels while also incorporating spatial context. Results on simulation experiments for different levels of activation detection difficulty are uniformly encouraging. The value of the methodology in low-signal and single-subject fMRI studies is illustrated on a sports imagination experiment. Concurrently, we also extend the potential use of fMRI as a clinical tool to, for example, detect awareness and improve treatment in individual patients in persistent vegetative state, such as traumatic brain injury survivors.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
