Systematic Model-based Design Assurance and Property-based Fault Injection for Safety Critical Digital Systems

With advances in sensing, wireless communications, computing, control, and automation technologies, we are witnessing the rapid uptake of Cyber-Physical Systems across many applications including connected vehicles, healthcare, energy, manufacturing, smart homes etc. Many of these applications are safety-critical in nature and they depend on the correct and safe execution of software and hardware that are intrinsically subject to faults. These faults can be design faults (Software Faults, Specification faults, etc.) or physically occurring faults (hardware failures, Single-event-upsets, etc.). Both types of faults must be addressed during the design and development of these critical systems. Several safety-critical industries have widely adopted Model-Based Engineering paradigms to manage the design assurance processes of these complex CPSs. This thesis studies the application of IEC 61508 compliant model-based design assurance methodology on a representative safety-critical digital architecture targeted for the Nuclear power generation facilities. The study presents detailed experiences and results to demonstrate the benefits of Model testing in finding design flaws and its relevance to subsequent verification steps in the workflow. Additionally, to study the impact of physical faults on the digital architecture we develop a novel property-based fault injection method that overcomes few deficiencies of traditional fault injection methods. The model-based fault injection approach presented here guarantees high efficiency and near-exhaustive input/state/fault space coverage, by utilizing formal model checking principles to identify fault activation conditions and prove the fault tolerance features. The fault injection framework facilitates automated integration of fault saboteurs throughout the model to enable exhaustive fault location coverage in the model

Dependable Embedded Systems

This Open Access book introduces readers to many new techniques for enhancing and optimizing reliability in embedded systems, which have emerged particularly within the last five years. This book introduces the most prominent reliability concerns from today’s points of view and roughly recapitulates the progress in the community so far. Unlike other books that focus on a single abstraction level such circuit level or system level alone, the focus of this book is to deal with the different reliability challenges across different levels starting from the physical level all the way to the system level (cross-layer approaches). The book aims at demonstrating how new hardware/software co-design solution can be proposed to ef-fectively mitigate reliability degradation such as transistor aging, processor variation, temperature effects, soft errors, etc. Provides readers with latest insights into novel, cross-layer methods and models with respect to dependability of embedded systems; Describes cross-layer approaches that can leverage reliability through techniques that are pro-actively designed with respect to techniques at other layers; Explains run-time adaptation and concepts/means of self-organization, in order to achieve error resiliency in complex, future many core systems

Astrophysical Modeling of Time-Domain Surveys

The goal of this work is to develop and apply algorithmic approaches for astrophysical modeling of time- domain surveys. Such approaches are necessary to exploit ongoing and future all-sky time-domain surveys. I focus on quantifying and characterizing source variability based on sparsely and irregularly sampled, non-simultaneous multi-band light curves, with an application to the Pan-STARRS1 (PS1) 3 pi survey: variability amplitudes and timescales are estimated via light curve structure functions. Using PS1 3 pi data on the SDSS "Stripe 82" area whose classification is available, a supervised machine-learning classifier is trained to identify QSOs and RR Lyrae based on their variability and mean colors. This leads to quite complete and pure variability-selected samples of QSO and RR Lyrae (away from the Galactic disk), that are unmatched in their combination of area, depth and fidelity. The sample entails: 4.8 x 10^4 likely RR Lyrae in the Galactic halo, and 3.7 x 10^6 likely QSO. The resulting map of RR Lyrae candidates across 3/4 of the sky reveals targets to 130 kpc, with distances precise to 3%. In particular, the sample leads to an unprecedented map of distance and width of Sagittarius stream, as traced by RR Lyrae. Furthermore, the role of PS1 3 pi as pilot survey for the upcoming LSST survey is discussed