Technical foundations introduction software reliability and system reliability the operational profile software reliability modelling survey model evaluation and recalibration techniques practices and experiences best current practice of SRE software reliability measurement experience measurement-based analysis of software reliability software fault and failure classification techniques trend analysis in validation and maintenance software reliability and field data analysis software reliability process assessment emerging techniques software reliability prediction metrics software reliability and testing fault-tolerant SRE software reliability using fault trees software reliability process simulation neural networks and software reliability. Appendices: software reliability tools software failure data set repository.

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Handbook of software reliability engineering

This paper is about better engineering of cyber-physical systems (CPSs) through better models. Deterministic models have historically proven extremely useful and arguably form the kingpin of the industrial revolution and the digital and information technology revolutions. Key deterministic models that have proven successful include differential equations, synchronous digital logic and single-threaded imperative programs. Cyber-physical systems, however, combine these models in such a way that determinism is not preserved. Two projects show that deterministic CPS models with faithful physical realizations are possible and practical. The first project is PRET, which shows that the timing precision of synchronous digital logic can be practically made available at the software level of abstraction. The second project is Ptides (programming temporally-integrated distributed embedded systems), which shows that deterministic models for distributed cyber-physical systems have practical faithful realizations. These projects are existence proofs that deterministic CPS models are possible and practical.

The past, present and future of cyber-physical systems: a focus on models.

We present a mathematical programming-based method for model predictive control of discrete-time cyber-physical systems subject to signal temporal logic (STL) specifications. We describe the use of STL to specify a wide range of properties of these systems, including safety, response and bounded liveness. For synthesis, we encode STL specifications as mixed integer-linear constraints on the system variables in the optimization problem at each step of a model predictive control framework. We present experimental results for controller synthesis for building energy and climate control.

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Model predictive control with signal temporal logic specifications

We present a counterexample-guided inductive synthesis approach to controller synthesis for cyber-physical systems subject to signal temporal logic (STL) specifications, operating in potentially adversarial nondeterministic environments. We encode STL specifications as mixed integer-linear constraints on the variables of a discrete-time model of the system and environment dynamics, and solve a series of optimization problems to yield a satisfying control sequence. We demonstrate how the scheme can be used in a receding horizon fashion to fulfill properties over unbounded horizons, and present experimental results for reactive controller synthesis for case studies in building climate control and autonomous driving.

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Reactive synthesis from signal temporal logic specifications

This paper studies the codesign optimization approach to determine how to optimally adapt automatic control of an intelligent electric vehicle to driving styles. A cyber-physical system (CPS)-based framework is proposed for codesign optimization of the plant and controller parameters for an automated electric vehicle, in view of vehicle's dynamic performance, drivability, and energy along with different driving styles. System description, requirements, constraints, optimization objectives, and methodology are investigated. Driving style recognition algorithm is developed using unsupervised machine learning and validated via vehicle experiments. Adaptive control algorithms are designed for three driving styles with different protocol selections. Performance exploration method is presented. Parameter optimizations are implemented based on the defined objective functions. Test results show that an automated vehicle with optimized plant and controller can perform its tasks well under aggressive, moderate, and conservative driving styles, further improving the overall performance. The results validate the feasibility and effectiveness of the proposed CPS-based codesign optimization approach.

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Driving-Style-Based Codesign Optimization of an Automated Electric Vehicle: A Cyber-Physical System Approach

In an aircraft electric power system, one or more supervisory control units actuate a set of electromechanical switches to dynamically distribute power from generators to loads, while satisfying safety, reliability, and real-time performance requirements. To reduce expensive redesign steps, this control problem is generally addressed by minor incremental changes on top of consolidated solutions. A more systematic approach is hindered by a lack of rigorous design methodologies that allow estimating the impact of earlier design decisions on the final implementation. To achieve an optimal implementation that satisfies a set of requirements, we propose a platform-based methodology for electric power system design, which enables independent implementation of system topology (i.e., interconnection among elements) and control protocol by using a compositional approach. In our flow, design space exploration is carried out as a sequence of refinement steps from the initial specification toward a final implementation by mapping higher level behavioral and performance models into a set of either existing or virtual library components at the lower level of abstraction. Specifications are first expressed using the formalisms of linear temporal logic, signal temporal logic, and arithmetic constraints on Boolean variables. To reason about different requirements, we use specialized analysis and synthesis frameworks and formulate assume guarantee contracts at the articulation points in the design flow. We show the effectiveness of our approach on a proof-of-concept electric power system design.

A Contract-Based Methodology for Aircraft Electric Power System Design

We propose a methodology for architecture exploration for Cyber-Physical Systems (CPS) based on an iterative, optimization-based approach, where a discrete architecture selection engine is placed in a loop with a continuous sizing engine. The discrete optimization routine proposes a candidate architecture to the sizing engine. The sizing routine optimizes over the continuous parameters using simulation to evaluate the physical models and to monitor the requirements. To decrease the number of simulations, we show how balance equations and conservation laws can be leveraged to prune the discrete space, thus achieving significant reduction in the overall runtime. We demonstrate the effectiveness of our methodology on an industrial case study, namely an aircraft environmental control system, showing more than one order of magnitude reduction in optimization time.

https://escholarship.org/content/qt7zm568c6/qt7zm568c6.pdf?t=o8evoh

A Mixed Discrete-Continuous Optimization Scheme for Cyber-Physical System Architecture Exploration

We introduce a platform-based design methodology that addresses the complexity and heterogeneity of cyber-physical systems by using assume-guarantee contracts to formalize the design process and enable realization of control protocols in a hierarchical and compositional manner. Given the architecture of the physical plant to be controlled, the design is carried out as a sequence of refinement steps from an initial specification to a final implementation, including synthesis from requirements and mapping of higher-level functional and non-functional models into a set of candidate solutions built out of a library of components at the lower level. Initial top-level requirements are captured as contracts and expressed using linear temporal logic (LTL) and signal temporal logic (STL) formulas to enable requirement analysis and early detection of inconsistencies. Requirements are then refined into a controller architecture by combining reactive synthesis steps from LTL specifications with simulation-based design space exploration steps. We demonstrate our approach on the design of embedded controllers for aircraft electric power distribution.

Contract-based design of control protocols for safety-critical cyber-physical systems

In an aircraft electric power system (EPS), a supervisory control unit must actuate a set of switches to distribute power from generators to loads, while satisfying safety, reliability and real-time performance requirements To reduce expensive re-design steps in current design methodologies, such a control problem is generally addressed based on minor incremental changes on top of consolidated solutions, since it is difficult to estimate the impact of earlier design decisions on the final implementation In this paper, we introduce a methodology for the design space exploration and virtual prototyping of EPS supervisory control protocols, following the platform-based design (PBD) paradigm Moreover, we describe the modeling infrastructure that supports the methodology In PBD, design space exploration is carried out as a sequence of refinement steps from the initial specification towards a final implementation, by mapping higher-level behavioral models into a set of library components at a lower level of abstraction In our flow, the system specification is captured using SysML requirement and structure diagrams State-machine diagrams enable verification of the control protocol at a high level of abstraction, while lowerlevel hybrid models, implemented in Simulink, are used to verify properties related to physical quantities, such as time, voltage and current values The effectiveness of our approach is illustrated on a prototype EPS control protocol design

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John B. Finn

Papers

A Contract-Based Methodology for Aircraft Electric Power System Design

A Mixed Discrete-Continuous Optimization Scheme for Cyber-Physical System Architecture Exploration

Contract-based design of control protocols for safety-critical cyber-physical systems

Platform-Based Design Methodology and Modeling for Aircraft Electric Power Systems.