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Misconceptions of chance are not limited to naive subjects. A study of the statistical intuitions of experienced research psychologists revealed a lingering belief in what might be called the "law of small numbers," according to which even small samples are highly representative of the populations from which they are drawn. The responses of these investigators reflected the expectation that a valid hypothesis about a population will be represented by a statistically significant result in a sample—with little regard for its size. As a consequence the researchers put too much faith in the results of small samples and grossly overestimated the replicability of such results. In the actual conduct of research, this bias leads to the selection of samples of inadequate size and to overinterpretation of findings.

Belief in the law of small numbers

The amount of software in cars grows exponentially. Driving forces of this development are the availability of cheaper and more powerful hardware, as well as the demand for innovation through new functionality. The rapidly growing significance of software and software-based functionality is at the root of various challenges in the automotive industries. These concern their organization, definition of key competencies, processes, methods, tools, models, product structures, division of labor, logistics, maintenance, and long-term strategies. This paper pinpoints the idiosyncrasies of the domain, characterizes the essentials of automotive software, and discusses the challenges of automotive software engineering

https://mediatum.ub.tum.de/doc/1251761/file.pdf

Engineering Automotive Software

In the last decade, a large number of different software component models have been developed, with different aims and using different principles and technologies. This has resulted in a number of models which have many similarities, but also principal differences, and in many cases unclear concepts. Component-based development has not succeeded in providing standard principles, as has, for example, object-oriented development. In order to increase the understanding of the concepts and to differentiate component models more easily, this paper identifies, discusses, and characterizes fundamental principles of component models and provides a Component Model Classification Framework based on these principles. Further, the paper classifies a large number of component models using this framework.

A Classification Framework for Software Component Models

All Access to FAILURE MODE AND EFFECTS ANALYSIS FMEA PDF. Free Download FAILURE MODE AND EFFECTS ANALYSIS FMEA PDF or Read FAILURE MODE AND EFFECTS ANALYSIS FMEA PDF on The Most Popular Online PDFLAB. Only Register an Account to DownloadFAILURE MODE AND EFFECTS ANALYSIS FMEA PDF. Online PDF Related to FAILURE MODE AND EFFECTS ANALYSIS FMEA . Get Access FAILURE MODE AND EFFECTS ANALYSIS FMEA PDF and Download FAILURE MODE AND EFFECTS ANALYSIS FMEA PDF for Free.

Failure Mode and Effects Analysis (FMEA)

In this paper we present a component model for development of distributed real-time systems. The model is developed to support development of embedded control systems for ground vehicles. The model aims at supporting three important activities in real-time development, (i) design, (ii) analysis and (iii) synthesis. These activities emphasise different and sometimes conflicting requirements that need to be balanced. For example, developers desire freedom in designing to solve complex tasks, analysis tools require the design to be formal enough for analysis and synthesis need to be efficient for low run-time footprint. We have considered industrial requirements for these activities and developed the RubusCMv3 component model. The model has been developed in close cooperation with industrial partners and it is currently being evaluated on real systems.

The Rubus component model for resource constrained real-time systems

This paper will show how advanced embedded realtime systems, with functionality ranging from time-triggered control functionality to event-triggered user interaction, can be made more efficient. Efficient with respect to development effort as well as run-time resource utilization. This is achieved by using a hybrid, static and dynamic, scheduling strategy. The approach is applicable even for hard real-time systems since tight response time guarantees can be given by the response time analysis method for tasks with offsets. An industrial case study will demonstrate how this approach enables more efficient use of computational resources, resulting in a cheaper or more competitive product since more functionality can be fitted into legacy, resource constrained, hardware.

Efficient Development of Real-Time Systems Using Hybrid Scheduling.

This paper presents a novel method to determine the maximum stack memory used in preemptive, shared stack, real-time systems. We provide a general and exact problem formulation applicable for any preemptive system model based on dynamic (run-time) properties. We also show how to safely approximate the exact stack usage by using static (compile time) information about the system model and the underlying run-time system on a relevant and commercially available system model: A hybrid, statically and dynamically, scheduled system. Comprehensive evaluations show that our technique significantly reduces the amount of stack memory needed compared to existing analysis techniques. For typical task sets a decrease in the order of 70% is typical.

/pdf/determining-maximum-stack-usage-in-preemptive-shared-stack-4zrkqhj4i4.pdf

Determining Maximum Stack Usage in Preemptive Shared Stack Systems

In this paper, we aim at capturing the industrial viewpoint of today's and future requirements in development of embedded real-time systems. We do this by interviewing ten senior designers at four Swedish companies, developing embedded applications in the vehicle domain. This study shows that reliability and safety are the main properties in focus during development. It also shows that the amount of functionality has been increasing in the examined systems. Still the present requirements are fulfilled using considerably homogenous development methods. The study also shows that, in the future, there will be even stronger requirements on dependability and control performance at the same time as requirements on more softer and resource demanding functionality will continue to increase. Consequently, the complexity will increase, and with diverging requirements, more heterogeneous development methods are called for to fulfil all application specific requirements.

/pdf/present-and-future-requirements-in-developing-industrial-4zcvbmwnfa.pdf

Present and future requirements in developing industrial embedded real-time systems - interviews with designers in the vehicle domain

The paper presents two novel methods to bound the stack memory used in preemptive, shared stack, real-time systems. The first method is based on branch-and-bound search for possible preemption patterns, and the second one approximates the first in polynomial time. The work extends previous methods by considering a more general task-model, in which all tasks can share the same stack. In addition, the new methods account for precedence and offset relations. Thus, the methods give tight bounds for a large set of realistic systems. The methods have been implemented and a comprehensive evaluation, comparing our new methods against each other and against existing methods, is presented. The evaluation shows that our exact method can significantly reduce the amount of stack memory needed.

Kaj Hänninen

Papers

The Rubus component model for resource constrained real-time systems

Efficient Development of Real-Time Systems Using Hybrid Scheduling.

Determining Maximum Stack Usage in Preemptive Shared Stack Systems

Present and future requirements in developing industrial embedded real-time systems - interviews with designers in the vehicle domain

Bounding Shared-Stack Usage in Systems with Offsets and Precedences