332 lines
13 KiB
TeX
332 lines
13 KiB
TeX
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%
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% strucure
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%
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% introduce concept, mapping s/w to FMMD
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%
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% yourdon data flow. Show transform bubbles and process for converting to a hierarchy of functiona calls
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% show h/w at the bottom, and s/w on top.
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% describe where s/w h/w interface occurs
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%
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% Talk about pre and post coonditions of contract s/w
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% get some nice refs on contract s/w
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% Now make the distinction that
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% pre condition violations are like componnt fault modes, and that a software function is
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% like a {\fg}. Now show that an analysed s/w function is a {\dc} where the
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% symptoms of failure are failed post conditions.
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% now take a simple example, temp sensing
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% and design it top down.
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% interface to digitial I/O and an ADC
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\ifthenelse {\boolean{paper}}
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{
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\begin{abstract}
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This paper
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%
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describes a methodology (Failure Mode Modular De-Composition - FMMD) that using a common notation
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models failure mode behaviour in software, electronic and mechanical
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domains. The methodology therefore can model integrated
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software/electrical/mechanical systems. This paper concentrates
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on the software modelling, begining with
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a discussion on general software stucture, afferent. transform and effenet
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data flow, and then the hierarchical call tree nature of software.
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Software functions are then described from a failure mode perspective
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integrating concepts from FMEA analysis, and the concepts of pre and post conditions.
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The paper then shows how FMMD models from electrical and mechanical
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domains can be seamlessly integrated with the software failure mode models.
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With a methodology that provides a common notation for these three domians
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complete and connected failure mode modelling can be applied to
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real time systems, such as safety critical smart devices and
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embedded industrial control machinery.
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\end{abstract}
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}
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{
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\section{Introduction}
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This chapter
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%
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describes a methodology (Failure Mode Modular De-Composition - FMMD) that using a common notation
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models failure mode behaviour in software, electronic and mechanical
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domains. The methodology therefore can model integrated
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software/electrical/mechanical systems. This paper concentrates
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on the software modelling, begining with
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a discussion on general software stucture, afferent. transform and effenet
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data flow, and then the hierarchical call tree nature of software.
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Software functions are then described from a failure mode perspective
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integrating concepts from FMEA analysis, and the concepts of pre and post conditions.
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The paper then shows how FMMD models from electrical and mechanical
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domains can be seamlessly integrated with the software failure mode models.
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With a methodology that provides a common notation for these three domians
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complete and connected failure mode modelling can be applied to
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real time systems, such as safety critical smart devices and
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embedded industrial control machinery.
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}
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\ifthenelse {\boolean{paper}}
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{
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\section{Basic Concepts Of FMMD}
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\paragraph{Creating an fault hierarchy}
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%%- bias this to software...
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The main idea of the FMMD methodology is to build a hierarchy of fault behaviour
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component models from the part
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level up to highest system levels.
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In order to perform FMMD analysis, which is a bottom up ethodology, the first stage is to choose
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components that interact and naturally form {\fgs}. The initial {\fgs} are thus collections of base parts.
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%These parts all have associated fault modes. A module is a set fault~modes.
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From the point of view of fault analysis, we are not interested in the components themselves, but in the ways in which they can fail.
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For software we already have the hierarchy, thanks to the nature of the `call tree'
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in procedural languages.
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In terms of software, we can consider the data transformations and functions used/called by a function to be the components.
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The functions called will have known failure modes (i.e. they can fail their post conditions).
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For this study a {\fg} will mean a collection of components.
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In order to determine the symptoms or failure modes of a {\fg},
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we need to consider all failure modes of its components.
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By analysing the fault behaviour of a `{\fg}' with respect these failure modes
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we can derive a new set of possible failure modes.
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Thus we can consider how a software function will react to the failure modes of the functions it calls.
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%
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This new set of faults is the set of derived faults from the perspective of the {\fg}, and is thus at a higher level of
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fault~mode abstraction. Thus we can say that the {\fg} as an entity, can fail in a number of well defined ways.
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In other words we have taken a {\fg}, and analysed how it can fail according to the failure modes of its parts.
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These new failure~modes are derived failure modes.
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%The ways in which the module can fail now becomes a new set of fault modes, the fault~modes
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%being derived from the {\fg}.
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We can now create a new `{\dc}' which has
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the failure symptoms of the {\fg} as its set of failure modes.
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We thus consider that our software function can fail in a number of given ways.
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This new {\dc} is at a higher failure mode abstraction
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level than the {\bcs}.
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} % ifdef papaer
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{
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}
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\ifthenelse {\boolean{paper}}
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{
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Reference the symptom abstraction paper here
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}
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{
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This analysis and symptom collection process is described in detail in the Symptom extraction (see chapter \ref{symptomex}).
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}
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\section{ Modern Devices }
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From the automobile to the microwave oven, we increasingly rely on
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embedded computing, controlling electro mechanical
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devices etc etc etc
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\section{ Data Flow Modelling }
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A computer system can be considered to simply process data, and data flow modelling
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exists in various forms.~\cite{yourdon}~\cite{sommerville}
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Essentially data flow modelling starts with a context diagram, where
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the inputs and outputs to a process are identified.
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These inputs and outputs connect to a process `bubble'
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representing the computing, or data transformation.
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Data flow diagrams (DFDs) are directed graphs~\cite{embupsys}[pp.120].
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The arcs represent data flow, and the bubbles
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represent procedures that transform data.
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A `bubble' can be further
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decomposed, or zoomed into, to a more detailed
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DFD which shows the subprocedures and data flows within it.
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EXAMPLE CONTEXT DIAGRAM
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The data input to the system is afferent data flow, the data actually processed is
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known as transform data and the data output is termed `efferent' flow.
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The next stage in the process is to consider the transform, or computing bubble.
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Each stream of input data is taken to transform `bubbles' that
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process the data and pass it on to other bubles which process the data to be sent out.
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%%- Hereby the Data flow diagrams (DFDs) are directed graphs.
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%%- The arcs represent data, and the nodes (circles or bubbles)
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%%- represent processes that transform the data. A process can be further
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%%- decomposed to a more detailed DFD which shows the subprocesses and data flows within it.
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This process can continue zooming into each `bubble' until the transformation processes they
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represent are simple enough to implement as functions in a programming language.
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The next stage, is to pick a transform bubble somewhere in the middle
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of these diagrams and assign it as the `main' \cite{kandr} or start
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function.
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As a design methodology, ignoring real time constraints, this is a very good way
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of analysiing a problem and getting a good software structure.
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What is interesting though is that this naturally determines a hierarchy
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where the hardware, the sensors and actuators in an embedded system,
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naturally fall to the lowest point in the software hierarchy.
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n fact because we use electronics to measure mechanical devices,
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we can establish a hierarchy of the three domians
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in terms of software.
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That is to say Software at the top of the hierarchy, Electronics below it, and mechanical
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systems below electronics.
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%%-s is the process of identifying, modeling and documenting how data moves around an information system.
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%%- Data Flow Modeling examines processes (activities that transform data from one form to another), data stores (the
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%%- holding areas for data), external entities (what sends data into a system or receives data from a system),
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%%- and data flows (routes by which data can flow).
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%%-Discuss afferent efferent flow, how h/w naturally goes at the bottem end
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%%-of the software structure.
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Establish this general structure
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SW
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ELEC
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MECH
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\section{ Software structure}
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All software has a natural hierarchy or call tree structure.
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The first called function will call others and the hierarchy
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will be controlled by a call stack.
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\section{FMEA applied to s/w}
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%tref navy Msc
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Failure Mode Effects analysis can be applied to software.
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We can treat a software function as a component.
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It has a set of failure modes, or outputs that
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can be incorrect. In contract programming these correspond to the post-conditions for the function.
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The parameters passed to the function, or return values from functions it calls,
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can be considered the pre-conditions.
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Because of the hierichical nature of software functions
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we can consider functions from the FMMD perspective as
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{\dcs}.
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The failure modes of the {\dc} are where failures
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in post conditions occur.
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The failure modes to consider for a function, or pre-condition
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failures, are the parameters passed to it and any values
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it uses (external data or values from function calls that it makes).
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Recursion potentially complicates this, however
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functions are banned for high integrity levels
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of most standards in the field of embedded computing.
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EN61508\cite{en61508} specifically bans recursive
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calls for SIL 2 on higher. Some microcontroller families~\cite{PIC18}
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make classic recursion impossible, by using memory mapping for
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parameters as opposed to a general purpose stack.
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\paragraph{Design Constraint: FMMD and recursive function calls}
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FMMD will not support recursion in its modelling of software.
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Now need a simple example C program, where I have functions
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with pre and post conditions and show these as an fmmd hierarchy
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really nice touch would be to have the pre and post conditions
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as comments and then to automatically process them into an FMMD analysis tool
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All the functions it calls are components
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that are used to build it.
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\section{Failure Modes and functions}
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Describe functions, how pre conditions map to
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input failure modes and post conditions to
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failure mode symptoms.
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Traditionally written as a form of guard.
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Here we are interested in the ways the functions can fail.
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They can fail if given the wrong data, or there can be a mistake in the code
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which causes an incorrect output.
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\section{ Applying Software to the FMMD Hierarchy}
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Follow the natural call function hierarchy, model the
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flow of failure modes and symptom collection as before.
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\section{interfacing Software to Hardware}
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\subsection{The medium on which software executes}
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Software, is an abstract formal representation of the procedures
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and mathematical processing to achieve a goal. For it to run
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in the `real~world', it has to run on some form of
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processor. Typically this will, in the case of embedded safety critical
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applications, be on some form of micro-controller.
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Modern micro controllers are highly intgerated devices.
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A typical low cost micro-controller will
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have at least the following functional modiules intgrated into it:
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\begin{itemize}
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\item Analogue to Digital Converter (ADC),
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\item Universal Asynchronous Receiver Transmitter (UART),
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\item Serial Peripheral Interface (SPI), a synchronous serial data link used to transfer data between chips on a PCB ,
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\item Controller Area Network (CAN) an industrailly hardened shhort messaging serial bus,
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\item Capture Compare PWM CCP (counters, timers and pulse width modulation output),
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\item interrupt triggering facilities
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\item digital I/O.
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\end{itemize}
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Need to consider the failure modes of all these components.
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For ADC we also need to consider the MUX and how it interfaces with general I/O
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pins.
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this later makes the example where we test the ADC and the MUX by
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forcing logical values onto the I/O pins the ADC reads.
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%% Super bbc micro all on one 28 pin chip
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Obviously were a microcontroller to fail internally,
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it could fail and not affect any of its other modules.
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Should a failure occur in an unused module, the
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application would never detect it.
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This means that we could easily have more than one
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failure at any given time.
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This means that were we to try to place a microcontroller into a failure model,
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apart from being unwieldingly large, it would
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disobey the unintary state failure mode constraint of FMMD (see section \ref{unitarystate}).
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\paragraph{The need to de-compose highly integrated components}
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\paragraph{Consider module activation within highly integrated component as a soource of failure}
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\subsection{Context of firmware in a small System}
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Nature of this is sensors and actuators.
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Describe.
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Example of failure modes of a hardware element being
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integrated into s/w
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Use prev example of milli-volt amp with check resistor.
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\section{Software Example Analysed using FMMD}
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