15,739 research outputs found
Metamodel Instance Generation: A systematic literature review
Modelling and thus metamodelling have become increasingly important in
Software Engineering through the use of Model Driven Engineering. In this paper
we present a systematic literature review of instance generation techniques for
metamodels, i.e. the process of automatically generating models from a given
metamodel. We start by presenting a set of research questions that our review
is intended to answer. We then identify the main topics that are related to
metamodel instance generation techniques, and use these to initiate our
literature search. This search resulted in the identification of 34 key papers
in the area, and each of these is reviewed here and discussed in detail. The
outcome is that we are able to identify a knowledge gap in this field, and we
offer suggestions as to some potential directions for future research.Comment: 25 page
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Disruptive Innovations and Disruptive Assurance: Assuring Machine Learning and Autonomy
Autonomous and machine learning-based systems are disruptive innovations and thus require a corresponding disruptive assurance strategy. We offer an overview of a framework based on claims, arguments, and evidence aimed at addressing these systems and use it to identify specific gaps, challenges, and potential solutions
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Towards Identifying and closing Gaps in Assurance of autonomous Road vehicleS - a collection of Technical Notes Part 2
This report provides an introduction and overview of the Technical Topic Notes (TTNs) produced in the Towards Identifying and closing Gaps in Assurance of autonomous Road vehicleS (Tigars) project. These notes aim to support the development and evaluation of autonomous vehicles. Part 1 addresses: Assurance-overview and issues, Resilience and Safety Requirements, Open Systems Perspective and Formal Verification and Static Analysis of ML Systems. This report is Part 2 and discusses: Simulation and Dynamic Testing, Defence in Depth and Diversity, Security-Informed Safety Analysis, Standards and Guidelines
Towards Identifying and closing Gaps in Assurance of autonomous Road vehicleS - a collection of Technical Notes Part 1
This report provides an introduction and overview of the Technical Topic Notes (TTNs) produced in the Towards Identifying and closing Gaps in Assurance of autonomous Road vehicleS (Tigars) project. These notes aim to support the development and evaluation of autonomous vehicles. Part 1 addresses: Assurance-overview and issues, Resilience and Safety Requirements, Open Systems Perspective and Formal Verification and Static Analysis of ML Systems. Part 2: Simulation and Dynamic Testing, Defence in Depth and Diversity, Security-Informed Safety Analysis, Standards and Guidelines
Approximate probabilistic verification of hybrid systems
Hybrid systems whose mode dynamics are governed by non-linear ordinary
differential equations (ODEs) are often a natural model for biological
processes. However such models are difficult to analyze. To address this, we
develop a probabilistic analysis method by approximating the mode transitions
as stochastic events. We assume that the probability of making a mode
transition is proportional to the measure of the set of pairs of time points
and value states at which the mode transition is enabled. To ensure a sound
mathematical basis, we impose a natural continuity property on the non-linear
ODEs. We also assume that the states of the system are observed at discrete
time points but that the mode transitions may take place at any time between
two successive discrete time points. This leads to a discrete time Markov chain
as a probabilistic approximation of the hybrid system. We then show that for
BLTL (bounded linear time temporal logic) specifications the hybrid system
meets a specification iff its Markov chain approximation meets the same
specification with probability . Based on this, we formulate a sequential
hypothesis testing procedure for verifying -approximately- that the Markov
chain meets a BLTL specification with high probability. Our case studies on
cardiac cell dynamics and the circadian rhythm indicate that our scheme can be
applied in a number of realistic settings
Self-resilient production systems : framework for design synthesis of multi-station assembly systems
Product design changes are inevitable in the current trend of time-based competition where
product models such as automotive bodies and aircraft fuselages are frequently upgraded and cause
assembly process design changes. In recent years, several studies in engineering change
management and reconfigurable systems have been conducted to address the challenges of frequent
product and process design changes. However, the results of these studies are limited in their
applications due to shortcomings in three aspects which are: (i) They rely heavily on past records
which might only be a few relevant cases and insufficient to perform a reliable analysis; (ii) They
focus mainly on managing design changes in product architecture instead of both product and
process architecture; and (iii) They consider design changes at a station-level instead of a multistation
level.
To address the aforementioned challenges, this thesis proposes three interrelated research
areas to simulate the design adjustments of the existing process architecture. These research areas
involve: (i) the methodologies to model the existing process architecture design in order to use the
developed models as assembly response functions for assessing Key Performance Indices (KPIs);
(ii) the KPIs to assess quality, cost, and design complexity of the existing process architecture
design which are used when making decisions to change the existing process architecture design;
and (iii) the methodology to change the process architecture design to new optimal design solutions
at a multi-station level.
In the first research area, the methodology in modeling the functional dependence of
process variables within the process architecture design are presented as well as the relations from
process variables and product architecture design. To understand the engineering change
propagation chain among process variables within the process architecture design, a functional
dependence model is introduced to represent the design dependency among process variables by
cascading relationships from customer requirements, product architecture, process architecture, and
design tasks to optimise process variable design. This model is used to estimate the level of process
variable design change propagation in the existing process architecture design
Next, process yield, cost, and complexity indices are introduced and used as KPIs in this
thesis to measure product quality, cost in changing the current process design, and dependency of
process variables (i.e, change propagation), respectively. The process yield and complexity indices
are obtained by using the Stream-of-Variation (SOVA) model and functional dependence model,
respectively. The costing KPI is obtained by determining the cost in optimizing tolerances of
process variables. The implication of the costing KPI on the overall cost in changing process
architecture design is also discussed. These three comprehensive indices are used to support
decision-making when redesigning the existing process architecture.
Finally, the framework driven by functional optimisation is proposed to adjust the existing
process architecture to meet the engineering change requirements. The framework provides a
platform to integrate and analyze several individual design synthesis tasks which are necessary to
optimise the multi-stage assembly processes such as tolerance of process variables, fixture layouts,
or part-to-part joints. The developed framework based on transversal of hypergraph and task
connectivity matrix which lead to the optimal sequence of these design tasks. In order to enhance
visibility on the dependencies and hierarchy of design tasks, Design Structure Matrix and Task
Flow Chain are also adopted. Three scenarios of engineering changes in industrial automotive
design are used to illustrate the application of the proposed redesign methodology. The thesis
concludes that it is not necessary to optimise all functional designs of process variables to
accommodate the engineering changes. The selection of only relevant functional designs is
sufficient, but the design optimisation of the process variables has to be conducted at the system
level with consideration of dependency between selected functional designs
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