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+%!TEX root = ../hdrmain.tex
+
+\chapter{Engineering of interactive systems}
+ \epigraph{\lorem}{Auteur}
+
+\begin{Abstract}
+Modeling the behavior of both an interactive system and its users is challenging because of their fundamental different nature.
+ In his action theory, Norman presents how an agent interacting with world objects thanks to the seven stages of action.
+ The actions the agent performs on the object, and the way she perceives its behavior depends on factors such as affordances or her knowledge about this object or similar ones.
+ While this model is efficient at describing how users perceive interactive systems, it does not explain how systems interact with users because world objects are seen as black boxes.
+ We present the seven stages of reaction, which mirrored the seven stages of action that describe the behavior of reactive systems.
+ We discuss the similarities and differences of the two models, how they combine, as well as implications for the design of interactive systems.
+\end{Abstract}
+
+\section{7 stages model}
+
+
+Studying interactive system is a complex task because it requires knowledge on a wide range of areas.
+It spans from human sciences such as psychology, biology or sociology, to technical sciences such as computer science, electronics, mechanics, automatics or mathematics.
+All these experts need a common ground for studying interactive systems together.
+
+\begin{idee}
+In the paper we mentioned the usefulness of this model for several audiences. We will elaborate more on the objectives for HCI researchers and practitioners.
+Our model provides a framework for describing the software and hardware parts of an interactive system. We will describe it along three dimensions Beaudouin Lafon proposed to evaluate interaction models~\cite{mbl04} descriptive, evaluative and generative.
+
+\begin{itemize}
+\item Descriptive power. Many research papers do not describe critical information such as transfer functions, input\&output mappings, actuator response, …. Our model is a systematic structure for describing interactive systems. Such a description enables highlighting useful implementation details. Benefits include replicability, and highlighting potential undesired side effects in psychophysical experiments for instance.
+\item Evaluative power. Implementing hardware+software interactive systems is a particular difficult task. Many of these, including published research prototypes, have implementation issues that could be avoided with using a systematic approach. For example input systems have jitter because they do not use filtering. Many vibrotactile systems give poor feedback because they have a high inertia. Describing interactive systems with this common framework would make it easier to compare their implementation, and identify implementation issues.
+\item Generative power. The description of interactive systems with a common framework also has the advantage of inspiring alternative designs, new combination of designs and transgressive uses of technology.
+\end{itemize}
+\end{idee}
+
+\begin{idee}
+Reviewers questioned the similarity with past research due to insufficient positioning in the paper. Past research they mention on toolkits and tasks models essentially focus on the application, input phrase or encoding stages of our model. However, in the HCI community we observe a notable rise of custom hardware for the design of interactive systems in the past decade. Our model covers both the software and hardware parts of interactive systems, as a whole.
+\end{idee}
+
+Computing models such as $\lambda$-calculus~\cite{church32} or Turing machines~\cite{turing38} focus on solving numerical problem, and overlook the interaction machines have with their environment.
+While people daily interact with a world full of interactive devices, machines constantly interact with the world full of humans.
+Because of that, Goldin and Wegner showed that interaction is a more general model of computing that Turing-complete models~\cite{goldin08}.
+
+Many human behavior models are used in HCI, and there is an active community working on this.
+With GOMS~\cite{card83} and Keystroke~\cite{card80} we can predict the time it takes for a person to use a keyboard or a pointer for example, including mental activities.
+Fitts' Law is extensively used for modeling pointing~\cite{mackenzie92}, and the steering law for modeling how users follow a path~\cite{accot97}.
+However such models are specialized to specific tasks, therefore not generic enough for describing entire interactive systems.
+
+Norman's action theory is a more general description of how people interact with the world, in particular interactive systems~\cite{norman02}.
+Figure~\ref{fig:sevenstages} depicts the seven stages of actions he uses to describe his theory.
+The person starts with a goal in her mind.
+Then she successively forms intentions, specify and execute actions on the world.
+As a consequence, the state of the world changes, and the person perceive these changes.
+Then she interprets this state and evaluate the consequence of her actions on the world.
+%The way people interact with the world highly depends on actions enabled by shared properties between a user and an object,
+While this model is efficient at describing how people interact with interactive devices, the machines themselves are seen as black boxes.
+%However interactive systems have a process to interact with the world.
+
+%The seven stages of action as described by Norman is a direct application of Gibson's perception/action coupling~\cite{gibson50}.
+%Human beings act on the world to perceive it.
+%The way they interpret it depends on the action they performed to explore it.
+%O'Regan describes this interaction as the sensorimotor cycle~\cite{oregan01a}.
+%It is a continuous cycle of actions and perceptions, that shape our understanding of the world around us.
+%This phenomenon is the building block of the direct manipulation paradigm~\cite{schneiderman83}.
+%\fixme{Describe seven stages of action~\cite{norman02}.}
+
+\begin{figure}[htb]
+\centering
+\definecolor{cellred}{rgb} {0.98,0.17,0.15}
+
+\newcommand{\stage}[2]{
+ \node[minimum width=2.5cm, minimum height=1.0cm,fill=cellred, text=white,text width=2cm, align=center, rounded corners=2ex, outer sep=0](#1) {#2};
+}
+\begin{tikzpicture}
+ \small
+ \matrix[row sep=3mm, column sep=2mm,inner sep=0, node distance=0, outer sep=5mm] (cells) {
+ & \stage{goal}{Goal} & \\
+ \stage{intention}{Intention} & & \stage{evaluation}{Evaluation} \\
+ \stage{specification}{Specification actions} & & \stage{interpretation}{Interpretation} \\
+ \stage{execution}{Execution actions} & & \stage{perception}{Perception} \\
+ };
+ \node[anchor=north, minimum width=8.6cm,minimum height=.8cm,fill=black!10](world) at (cells.south) {World};
+ \draw [->, -stealth', thick]
+ (perception) edge (interpretation)
+ (interpretation) edge (evaluation)
+ (evaluation) edge[out=90, in=0] (goal)
+ (goal) edge[out=180, in=90] (intention)
+ (intention) edge (specification)
+ (specification) edge (execution);
+ \draw [->, -stealth', thick, dashed, draw=black!50, fill=black!50]
+ (perception|-world.north) edge (perception.south)
+ (execution) to (execution|-world.north);
+ \node[anchor=south, minimum width=2.6cm, rotate=90, outer sep=5mm](gulfexecution) at (specification.west) {Gulf of execution};
+ \draw [->, -stealth', thick,transform canvas={xshift=1em}]
+ (gulfexecution.east |- intention.north) to (gulfexecution.east |- execution.south);
+ \node[anchor=south, minimum width=2.6cm, rotate=270, outer sep=5mm](gulfevaluation) at (interpretation.east) {Gulf of evaluation};
+ \draw [->, -stealth', thick,transform canvas={xshift=-1em}]
+ (gulfevaluation.west |- perception.south) to (gulfevaluation.west |- evaluation.north);
+% \node[anchor=south, minimum width=2.6cm, rotate=90, thick,draw=black!20,fill=black!20] at (n.north west) {Implementation};
+% \node[anchor=south, minimum height=0.6cm, minimum width=6cm, thick, draw=black!20,fill=black!20] at (nd.north east) {Computing affordance};
+\end{tikzpicture}
+\caption{Norman's seven stages of action~\protect\cite{norman02}. It describes how people interact with their environment.}
+ \label{fig:sevenstages}
+\end{figure}
+
+
+We present the seven stages of reaction, a model of interactive systems behavior inspired by Normal's seven stages of action.
+Similarly to the designeering approach~\cite{huot13}, it advocates for the consideration of implementation aspects of interacting systems as a complement to user-centered design methods.
+Our model describes both the software and hardware part of interactive systems, and how it interacts with its environment.
+%We discuss how they work, how they interact with their environment, and how they evolve.
+After describing the model, we discuss its combination with Norman's model, and its implications to the design of interactive systems.
+
+
+\subsection{Seven stages of reaction}
+
+Interactive systems globally work in a similar way than humans.
+They sense the world, and they act on it.
+%However, we can identify a major difference in most cases.
+%While people generally have the initiative, the loop in the seven stages of action starts with a goal, interactive systems tend to react to the environment.
+%They get information from the world, interpret it, and act on the world in return.
+%Despite the tremendous progress of computers the past decades, they can still process a tiny part of
+%\loremipsum
+We describe below the \defword{seven stages of reaction} based on Norman's seven stages of action (Figure~\ref{fig:mysevenstages}).
+The model is upside down, because it starts with an input chain (on the left), a software part that interprets the inputs and produces outputs (on the right).
+%After reviewing the seven stages of reaction, we will discuss the pitfalls it reveals, and we will compare them with the seven stages of action.
+
+\begin{idee}
+The stages of our model are functional slicing of system parts by input/output: peripherals (sensing/Physical effect), driver (event/command), toolkit (phrase/encoding), and the application binds both sides with interaction techniques. Hence it not only covers the application, but also the full input and output chains.
+\end{idee}
+
+\begin{idee}
+Criticisms to Norman's model are not necessarily relevant since they focus on the human side. In our submission we get inspiration from this model to build a compatible model to describe the system behavior. We only discuss the human side on how it interacts with the system. But any variation of Norman's model should be compatible with our own.
+\end{idee}
+
+\begin{figure}[htb]
+\centering
+\definecolor{cellblue}{rgb} {0.17,0.60,0.99}
+
+\newcommand{\stage}[2]{
+ \node[minimum width=2.5cm, minimum height=1.0cm,fill=cellblue, text=white,text width=2cm, align=center, rounded corners=2ex, outer sep=0](#1) {#2};
+}
+\begin{tikzpicture}
+ \small
+ \matrix[row sep=3mm, column sep=2mm,inner sep=0, node distance=0, outer sep=5mm] (cells) {
+ \stage{sensing}{Sensing} & & \stage{physical}{Physical effect} \\
+ \stage{events}{Input Events} & & \stage{command}{Command} \\
+ \stage{phrase}{Input phrase} & & \stage{encoding}{Encoding} \\
+ & \stage{application}{Application} & \\
+ };
+ \node[anchor=south, minimum width=8.6cm,minimum height=.8cm,fill=black!10](world) at (cells.north) {World};
+ \draw [->, -stealth', thick]
+ (sensing) edge (events)
+ (events) edge (phrase)
+ (phrase) edge[out=270, in=180] (application)
+ (application) edge[out=0, in=270] (encoding)
+ (encoding) edge (command)
+ (command) edge (physical);
+ \draw [->, -stealth', thick, dashed, draw=black!50, fill=black!50]
+ (sensing|-world.south) edge (sensing.north)
+ (physical) to (physical|-world.south);
+ \node[anchor=south, minimum width=2.6cm, rotate=90, outer sep=5mm](funnelevaluation) at (events.west) {Funnel of evaluation};
+ \draw [->, -stealth', thick,transform canvas={xshift=1em}]
+ (funnelevaluation.east |- sensing.north) to (funnelevaluation.east |- phrase.south);
+ \node[anchor=south, minimum width=2.6cm, rotate=270, outer sep=5mm](funnelexecution) at (command.east) {Funnel of evaluation};
+ \draw [->, -stealth', thick,transform canvas={xshift=-1em}]
+ (funnelexecution.west |- encoding.south) to (funnelexecution.west |- physical.north);
+% \node[anchor=south, minimum width=2.6cm, rotate=90, thick,draw=black!20,fill=black!20] at (n.north west) {Implementation};
+% \node[anchor=south, minimum height=0.6cm, minimum width=6cm, thick, draw=black!20,fill=black!20] at (nd.north east) {Computing affordance};
+\end{tikzpicture}
+\caption[Seven stages of interactive computation]{The seven stages of interactive computation, adapted from Norman's seven stages of action. It describes how interactive systems interact with their environment.}
+\label{fig:mysevenstages}
+\end{figure}
+
+\subsubsection{Input chain}
+
+The input stage is the mirror of the evaluation part of the seven stages of action.
+It comprises three stages that explain how interactive systems get informations from the environment.
+%world, and in particular the user.
+
+\paragraph{Sensing}
+
+The input chain begins with the \emph{sensing} stage.
+It mainly consists in hardware, sensors and their driving electronics, that measure physical properties of the environment.
+User movements is the favorite kind of information for interactive systems, but it can be various other information such as light~\cite{sonne17}, temperature~\cite{sarsenbayeva17}, moisture~~\cite{jia18}, vibrations~\cite{casiez17}.
+There is also an important software part that consists in encoding~\cite{song11}, filtering~\cite{casiez12} and transmitting the data.
+
+\paragraph{Input events}
+
+The low level stages of the system transform sensed information into \emph{input events}.
+It takes into account predefined information, such as calibration or transfer functions~\cite{casiez11a}.
+Raw capacitance values are transformed into contact points~\cite{lee85}.
+Body skeletons are computed from depth images~\cite{shotton11}.
+At this stage we notice that the infinite richness of the world is reduced to a relatively small number of digits.
+%Let's discuss the simple example of a keypress on a keyboard.
+%The only information in the digital world is whether a key is pressed or not. There is no information about the finger that pressed it, the speed of the finger or its trajectory.
+%There is neither the possibility if a finger is hovering the key, if several fingers are pressing it, or even if it was pressed with the nose.
+
+\paragraph{Input phrases}
+
+Input events are treated as tokens, or lexical units.
+They are interpreted as \emph{input phrases} with grammars or finite automatons~\cite{appert06} or more complex algorithms~\cite{wobbrock07}.
+They form the building blocks of \defword{interaction techniques}, also called modalities~\cite{nigay93}.
+A click, a drag \& drop or a pinch gesture are examples of interaction techniques.
+The combination of modalities, called multimodality~\cite{coutaz95}, expands the possible inputs.
+The joint use of a digal pen and multitouch on a interactive surface is such an example~\cite{hinckley10}.
+%Multimodality is the combination of several modalities.
+%\cite{oviatt99}.
+
+\subsubsection{Application}
+
+The \emph{application} layer is specialized for assisting users in their tasks.
+It executes actions as a result of input phrases, and produce outputs to give users feedback, and the result of their actions.
+The architecture of this stage is further detailed in models such as PAC~\cite{coutaz87}, Arch~\cite{arch92} or MVC~\cite{reenskaug79a}.
+These architectures define several layers between the user, seen through widgets, and the computer, seen through a functional core (or abstraction, model).
+
+% meta algorithm that chooses whether there are algorithms to run, which algorithms to run, and with which parameters.
+% It occurs typically when a command is selected, or an object is being manipulated.
+
+% Every computer system has at some point an effect on the world.
+% We extend the notion of dead code to not only code that is never executed, but also code which result has no effect whatsoever on the physical world.
+% Even a routing algorithm will at some point transmit data to a computer which will display it or print it in any way.
+% % Quantic information : stored in computer memory. Will it be observed?
+% Bringing a piece of information to the physical world requires several steps.
+
+%Software architecture models such as further detail this stage.
+
+\subsubsection{Output chain}
+
+The output chain mirrors the action part on the seven stages of action.
+It describes the way interactive systems act on the world.
+In the following we will use haptic interfaces as an example, because of the diversity of actuation mechanisms.
+However the model applies to any output modality.
+
+\paragraph{Encoding}
+
+First of all the systems must \emph{encode} the piece on information.
+It takes into account multiple parameters, as described by Bernsen's design space~\cite{bernsen93a}, or Bertin in the case of vision~\cite{bertin83}.
+At this stage, the application decides how an object or a piece of information will be represented in the physical world.
+%A visual encoding can be an icon, or a text~\cite{bernsen93a}.
+Audio encodings can be sounds~\cite{gaver93} or melodies~\cite{brewster93}.
+Various haptic encodings include vibrations~\cite{brewster04}, forces~\cite{maclean03a,pietrzak05a} or textures~\cite{pietrzak09}.
+Force feedback typically compute a force vector a a result of a force model that depend on the device position~\cite{zilles95}.
+%Proxy\cite{ruspini97}
+
+%Effectors can produce light (like screens), sounds, vibrations, forces, …
+
+\paragraph{Commands}
+
+Output devices have driving electronics which require specific \emph{commands}.
+For example force feedback devices commonly use DC motors.
+The output force depends on the voltage it receives.
+High force device require strong motors, therefore high voltage.
+Consequently, haptic devices need precise amplifiers.
+When these amplifiers do not have a linear response, the command has to be adjusted.
+%\fixme{closed loop}
+
+\paragraph{Physical effect}
+
+The command send to the device produces a \emph{physical effect}.
+These can be light, sounds, vibrations or forces for instance.
+The user feels these effects though his senses.
+Many external factors may disturb this effect.
+The vibration transmitted by a vibrotactile actuator to the skin of a user depends on how it is attached~\cite{yao10}, or how the users holds the device.
+The way a user sees an object displayed on a screen may be affected by ambient light or distance.
+
+
+\fixme{\subsection{Pitfalls}}
+
+With this model, we demonstrate that solving a problem with a interactive system is not only a matter of algorithmic computation.
+Sensing phenomenons of the environment, and producing effects on it resulting of the results of algorithmic computation is subject to non trivial issues.
+Algorithms can only observe the shadow of the physical world, under the light of input and output streams.
+They are like prisoners from a digital Plato's cave.
+Therefore, addressing interaction problems require a broader view than just observing algorithms.
+It requires identifying information the system needs, and how to convey a result efficiently.
+Norman's gulf of evaluation and gulf of execution are mirrored with a \defword{funnel of evaluation} and a \defword{funnel of execution} in this effect.
+
+\paragraph{Funnel of evaluation}
+
+The funnel of evaluation depicts the fact that the input stages reduce the world into few bits.
+A good design of the input chain senses the right phenomenons, at an appropriate amplitude, with a sufficient spatial and temporal resolution, and with little distortions.
+These information must me combined correctly to form a meaningful sequence of inputs.
+For example, the \emph{Midas touch} problem is a usual issue with 3D gestural interaction~\cite{gupta17}.
+Since the sensors observes all the users movements, there is no obvious segmentation.
+The system has no way to know if you move your hand to interact with the system, or for scratching your nose.
+At the opposite, occlusion prevents vision-based gesture sensors from getting position information for hidden objects.
+In these situations, we can grow the funnel of evaluation by adding segmentation gestures, and using multiple cameras.
+
+\paragraph{Funnel of execution}
+
+The funnel of execution is symmetrical.
+The software part of the system displays parts of its data and state in an intelligible way for users.
+The way data is shown to the user can have a huge impact on how he interacts with it~\cite{zhang94}.
+Therefore the encoding part is crucial, and it is a first filter for reducing the internal complexity of the system.
+The specifications of the output device is a second filter.
+There is a limitation of force, color, brightness, frequency, etc. each device can produce in theory.
+There is also a limit of precision, that greatly depends on amplifiers and digital to analog converters (DAC).
+Last the physical effect can be inconsistent for the same command.
+Some haptic devices can behave differently depending on ambient temperature, finger moisture, cleanliness, etc.
+
+\subsection{Interaction between users and systems}
+
+The purpose of interactive systems is to assist users in their activities.
+We can model the interaction of a user with a system by simply plugging the seven stages of action to the seven stages of reaction.
+The seven stages of reaction is a detailed view of the “world” stage in Norman's model.
+The connection between both occurs when the user manipulates an input device, and when she feels the physical effects of output devices~\cite{lederman96}.
+We can improve interaction not only by studying the two models separately, but also by studying their connections, similarities and differences.
+%This is typically what we study in HCI as we design new input devices with original sensing technologies~\cite{fellion17}, but also when we design new output devices with cutting-edge actuators%~\cite{frisson17,potier12,potier16}.
+
+Users and interactive systems are both modeled with an internal running loop (Figure~\ref{fig:loops}).
+The cycles of actions and perceptions that help us exploring the world is the \defword{sensorimotor loop}~\cite{oregan01a}.
+The seven stages of action is an instance of this phenomenon.
+Both models follow Gibson's theory, according to which exploratory movements are part of our understanding of the sensations we felt as a result of them~\cite{gibson50}.
+With this phenomenon, users can control interactive systems continuously~\cite{gupta16}.
+It enables fast and incremental adjustments, which are two of the building blocks of \defword{direct manipulation}~\cite{schneiderman83}.
+In order to make it happen, the interactive system must also respond in real time.
+This means its \defword{execution loop} must be fast, and with low latency\cite{casiez17}.
+
+\begin{figure}[htb]
+\centering
+\definecolor{cellred}{rgb} {0.98,0.17,0.15}
+\definecolor{cellblue}{rgb} {0.17,0.60,0.99}
+
+\newcommand{\labelcell}[2]{
+\node[minimum width=3cm, minimum height=1.0cm,text width=1.7cm, align=center, outer sep=0](#1) {#2};
+}
+\newcommand{\bluecell}[2]{
+ \node[minimum width=2.5cm, minimum height=1.0cm,fill=cellblue, text=white,text width=2cm, align=center, rounded corners=2ex, outer sep=0](#1) {#2};
+}
+\newcommand{\redcell}[2]{
+ \node[minimum width=2.5cm, minimum height=1.0cm,fill=cellred, text=white,text width=2cm, align=center, rounded corners=2ex, outer sep=0](#1) {#2};
+}
+\begin{tikzpicture}
+ \small
+ \matrix[row sep=3mm, column sep=0,inner sep=0, node distance=0, outer sep=5mm] (cells) {
+ & \labelcell{perception}{Perception} & \labelcell{output}{Output} & \\
+ \redcell{user}{User} & \labelcell{sensorimotor}{Sensorimotor loop} & \labelcell{execution}{Execution loop} & \bluecell{system}{System}\\
+ & \labelcell{action}{Action} & \labelcell{input}{Input} & \\
+ };
+ \draw [->, -stealth', thick]
+ (sensorimotor.north east) edge[bend right] (user.north)
+ (user.south) edge[bend right] (sensorimotor.south east)
+ (execution.south west) edge[bend right] (system.south)
+ (system.north) to[bend right] (execution.north west);
+ \draw [ultra thick, draw=black!20, fill=black!50]
+ (perception.north east) edge (action.south east);
+\end{tikzpicture}
+\caption{The similarity of a user and a system interacting with each other.}
+\label{fig:loops}
+\end{figure}
+
+\subsubsection{Initiative}
+
+In Norman's model, the first stage is the user's goal.
+This means in this extended model that the user has the initiative, and the system reacts to her actions.
+This is generally a desired property in user-centered designed systems.
+We depict this case in Figure~\ref{fig:extendedaction}-a.
+However we can also imagine the case in which the system has the initiative as illustrated on Figure~\ref{fig:extendedaction}-b.
+Following Beaudouin-Lafon's interaction paradigms~\cite{mbl04}, the first case is the computer-as-a-tool paradigm.
+The second case corresponds to the computer-as-a-partner paradigm.
+There is a third paradigm named computer-as-a-medium, which corresponds to the case of several users interacting with each other through computers (Figure~\ref{fig:extendedaction}-c).
+In this case the two users have the initiative, and the system reacts to both.
+
+In many cases, interactive systems are not binary though.
+They sometimes behave like tools, and sometimes like partners.
+There is a continuum between the tool and the partner paradigms.
+Systems in between are what Horvitz calls Mixed-initiative User Interfaces~\cite{horvitz99}.
+He describes factors to consider for the design of automated systems.
+Most of them are related to issues concerning the inference of users' goals.
+Other studies show that high controllability must be favored over automation accuracy~\cite{roy19}.
+Whether the user or the system has the initiative, we must keep in sight that the overall objective is to empower the user so that she can succeed in performing her activities.
+Designing interactive systems consists in combining users and machines strengths to compensate their weaknesses in order to empower users.
+
+\begin{idee}
+Regarding related work on AI, while the paper does mention these topics, it is not the focus on this submission. There is certainly more to say on this, but it would require a proper paper. The Intervention UI paradigm is relevant to our model though, and will be discussed in the Initiative paragraph, where we already discuss Horvitz's mixed initiatives. It is a form of Beaudouin Lafon's partner paradigm, and integrates well in our model (Figure 4b).
+\end{idee}
+
+\begin{figure}[htb]
+\centering
+\definecolor{cellred}{rgb} {0.98,0.17,0.15}
+\definecolor{cellblue}{rgb} {0.17,0.60,0.99}
+
+\newcommand{\labelcell}[2]{
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+}
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+ \node[minimum width=4cm, minimum height=1mm,fill=black!10, align=center, outer sep=0](#1) {};
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+\begin{tikzpicture}[align=center,outer sep=5mm]
+ \small
+ \matrix[anchor=south, row sep=3mm, column sep=2mm,inner sep=0, node distance=0] (cells) at (0,0.3) {
+ \redcell{user}{User} & \bluecell{system2}{System}\\
+ \barcell{thebar} & \barcell{thebar2}\\
+ \bluecell{system}{System} & \redcell{user2}{User}\\
+ \redcell{user3}{User} & \redcell{user4}{User}\\
+ };
+ \node[anchor=south, minimum width=8.6cm,minimum height=1mm, inner sep=0,fill=black!10, outer sep=0](thebar3) at (0,0.35) {};
+ \node[anchor=north, minimum width=8.6cm, minimum height=.8cm,fill=cellblue, text=white, align=center, rounded corners=2ex, outer sep=0](system3) at (0,0) {System};
+ % fig a
+ \node[anchor=south west] at (-4.9,1.4) {a)};
+ \draw [->, -stealth', thick]
+ (user.west) edge[bend right] ([xshift=-50]thebar.north)
+ ([xshift=-50]thebar.south) edge[bend right] (system.west)
+ (system.east) edge[bend right] ([xshift=50]thebar.south)
+ ([xshift=50]thebar.north) to[bend right] (user.east);
+ %fig b
+ \node[anchor=south west] at (-0.4,1.4) {b)};
+ \draw [->, -stealth', thick]
+ (system2.west) edge[bend right] ([xshift=-50]thebar2.north)
+ ([xshift=-50]thebar2.south) edge[bend right] (user2.west)
+ (user2.east) edge[bend right] ([xshift=50]thebar2.south)
+ ([xshift=50]thebar2.north) to[bend right] (system2.east);
+ %fig c
+ \node[anchor=south west] at (-4.9,0.7) {c)};
+ \draw [->, -stealth', thick]
+ (user3.west) edge[bend right] ([xshift=-110]thebar3.north)
+ ([xshift=-110]thebar3.south) edge ([xshift=-110]system3.north)
+ ([xshift=-5]system3.north) edge ([xshift=-5]thebar3.south)
+ ([xshift=-5]thebar3.north) to[bend right] (user3.east);
+
+ \draw [->, -stealth', thick]
+ (user4.west) edge[bend right] ([xshift=5]thebar3.north)
+ ([xshift=5]thebar3.south) edge ([xshift=5]system3.north)
+ ([xshift=110]system3.north) edge ([xshift=110]thebar3.south)
+ ([xshift=110]thebar3.north) to[bend right] (user4.east);
+
+\end{tikzpicture}
+\caption{Combinations of Norman's seven stages of action~\protect\cite{norman02} with the above 7 stages of computation. The three combinations represent Beaudouin-Lafon's three paradigms~\protect\cite{mbl04}: a) computer-as-a-tool; b) computer-as-a-partner; c) computer-as-a-medium. The agent(s) at the top have the initiative, while the agent at the bottom react to the other agents.}
+\label{fig:extendedaction}
+\end{figure}
+
+%: user delegates, then the system releases the control.
+
+%The interaction between a user and an interactive system is represented Figure~\ref{fig:extendedaction}.
+%The user's actions are connected to the system sensors of the input devices, and the physical effects produced by the output devices are connected to the user's sensory organs.
+
+\subsubsection{Computing affordance}
+
+The seven stages of actions are closely related to the notion of \emph{affordance}~\cite{gibson77}.
+An affordance is a property between a person an an object that enables this person to perform a set of physical actions on this object.
+%These properties are advertised by \emph{signifiers}.
+For example the $2 cm^2$ embossed surface of a button affords pressing it with a finger.
+The way we grasp an interactive device affords different actions we can perform on it~\cite{fellion17}.
+%The way users interact with an object such as an interactive system depends on affordances.
+The combination of affordances, past experiences and other knowledge enables users to create a mental model of an interactive system.
+%The user has a mental model of how the system works, which he created with past experience and knowledge of similar systems.
+%In the best case, the user can confirm or complete his mental model with further exploration through these 7 stages.
+Thanks to this, we can use systems we have never seen before.
+If the system follows standard usability guidelines~\cite{nielsen90}, the user can explore it further to complete her mental model.
+However the user model can differ from the design model.
+In this situation, the user's action can lead to results he did not expect.
+%The discrepancy between the user model and the design model reveals usability issues.
+These are generally usability issues that designers should fix.
+
+Similarly, interactive systems get information from the environment and act on it based on its programmed behavior.
+The equivalent of the user's mental model here is a set of assumptions that are crystallized in the system's program.
+It strongly limits what the system can perceive from the world, and the actions it can perform in it.
+%On top of that, what we can observe with the seven stages of reaction is that at each stage the result may differ from what the designer would like to achieve.
+%There can be noise in the sensed signal, differences between the command and the output signal or between the output signal and the physical effect.
+%Sensors may fail at sensing the intended phenomenon, and the physical effects produced by the interactive system can be altered by something in its environment.
+Wegner models interactive computation with input and output streams, which allow interaction machines to react continuously with their environment~\cite{wegner99}.
+He demonstrated that Turing machines cannot reproduce this behavior, and refuted the strong Church-Turing thesis because of this~\cite{goldin08}.
+Indeed, computability only concerns the computation of mathematical functions~\cite{turing38}.
+It cannot capture the essence of continuous streams of actions and reactions with an uncontrolled environment.
+Therefore we need a more general notion of “what interactive systems can do” than just computability.
+
+% Therefore we claim that this notion is more general than computability~\cite{turing38}.
+% The notion of computability is essentially algorithmic by nature.
+% One of the essential properties of algorithms is that their output have a specified relation to the inputs~\cite{knuth68}.
+% This property prevents algorithms to explore an open world, with unexpected objects with unknown behavior.
+% Interaction is a better paradigm in such situations, because interactive systems are connected to the outside world with input and output streams~\cite{wegner99}.
+
+We define the notion of \emph{computing affordance} as a behavior an interactive system can have with people or objects in their environment.
+It takes into account both its program and its sensing and actuating capabilities.
+They can either be desired or not desired, and can either happen or not with the interactive system implementation (Table~\ref{table:computingaffordance}).
+\emph{Existing features} are desired behaviors that can be the result of the interactive system implementation.
+It means appropriate sensing and actuating chains are working properly, and the program uses it in the intended way.
+\emph{Missing features} are desired behaviors that the interactive system cannot reproduce.
+It can be because it was not implemented, or because the implementation does not behave as intended.
+Indeed there can be noise in the sensed signal, differences between the command and the output signal or between the output signal and the physical effect.
+Sensors may fail at sensing the intended phenomenon, and the physical effects produced by the interactive system can be altered by something in its environment.
+\emph{Unwanted behavior} is a not desired behavior that can happen with the interactive system implementation.
+They can be the result of a malfunction, or an unpredicted side effect of another behavior.
+Finally, \emph{Not required features} are not desired behaviors that cannot occur with the interactive system implementation.
+
+\begin{idee}
+We will clarify our term “computing affordance”. We make a distinction with affordance defined by Gibson (and Norman, Gaver extensions) because systems have interactions with the environment, not only with humans. The overall idea is to bridge theoretical computing models with ours. Like others (\cite{gibson50}, Hornbæk and Oulasvirta discuss others), we extend the Church-Turing thesis beyond computing of mathematical functions. Our approach is an anthropomorphic vision of systems that interact with an unpredictable environment. We view the system as a combination of hardware and software, that correspond to the human body and cognition. According to Gibson, our understanding of our environment is not a cognitive process alone, but a relation between our body and our cognition. Our model applies this principle to computation. This require computation to refer to “a behaviour an interaction system can have with people or objects in their environment” rather than just computing mathematical functions. The term “computing affordance” binds this extended notion of computing with affordance.
+\end{idee}
+
+% there is not there is
+%info perceived false affordance perceived affordance
+%info not perceived correct reject hidden affordance
+
+% there is not there is
+%info perceived feature required existing feature
+%info not perceived feature not required missing feature
+
+\begin{table}[htb]
+\caption{Computing affordance are either desired or not. Either their implementation permits it or not.}
+\label{table:computingaffordance}
+\newcommand{\cell}[1]{
+ \node[minimum width=3cm, minimum height=2cm,draw=black!20,thin,text width=2cm, align=center] {
+ #1
+ };
+}
+\newcommand{\topcell}[2]{
+ \node[minimum width=3cm, minimum height=1cm,draw=black!20,thin,fill=black!10,text width=2cm, align=center](#1) {
+ #2
+ };
+}
+\newcommand{\leftcell}[2]{
+ \node[minimum width=2cm, minimum height=2cm,draw=black!20,thin,fill=black!10,text width=2cm, align=center](#1) {
+ #2
+ };
+}
+\centering
+\begin{tikzpicture}
+ \matrix[row sep=0mm, column sep=0mm,inner sep=0, node distance=0] (cells) {
+ & \topcell{nd}{Not desired} & \topcell{d}{Desired} \\
+ \leftcell{y}{Yes} & \cell{Unwanted behavior} & \cell{Existing feature} \\
+ \leftcell{n}{No} & \cell{Not required feature} & \cell{Missing feature}\\
+ };
+ \node[anchor=south, minimum width=4cm, rotate=90, thick,draw=black!20,fill=black!20] at (n.north west) {Implementation};
+ \node[anchor=south, minimum height=0.6cm, minimum width=6cm, thick, draw=black!20,fill=black!20] at (nd.north east) {Computing affordance};
+\end{tikzpicture}
+\end{table}
+
+%Engineers and designers build systems with the capabilities they desire, following the seven stages of reaction.
+%However the behavior of the system can be different, because of something unpredicted in the environment, or just because of a software or hardware malfunction.
+
+
+\subsubsection{Evolution}
+
+The discrepancy between the the system behavior and the design model is complementary to the discrepancy between the user's model and the designer's model revealed by Norman's model.
+They both contribute to the evolution of the interactive system.
+
+There are two scales of evolutions for humans.
+The first one is the evolution of mankind as a species.
+Every generation evolve thanks to genetics, society and culture to name a few.
+The second one is the evolution of every individual during their whole life.
+They learn about the world, but they also train their capacities.
+Even though there is of course a limit to this training, it is a key capability that enables people to adapt to their environment.
+
+Interactive systems can evolve at similar scales.
+They first evolve through software and hardware updates.
+These updates remove unwanted behaviors, and implement or fix missing features.
+Following principles such as reification, polymorphism and reuse facilitates such evolutions~\cite{mbl00a}.
+The set of desired behaviors actually evolves as well.
+First, users adapt to the interactive systems' behavior and get used to it.
+Second, practice stimulates new ideas of desired behavior.
+Therefore users and systems evolve together.
+This phenomenon is known as coevolution~\cite{mackay90}.
+While training makes users interact more efficiently, the benefits are greater when interactions techniques support training~\cite{cockburn14}.
+
+The evolution of interactive systems during their execution is still in its infancy.
+For example Pharo applications support the modification and debugging of their own code during their execution~\cite{black10}.
+Neural networks enables programs to evolve their behavior with supervised or unsupervised learning~\cite{mcculloch43}.
+Recent advances in deep learning facilitated this learning phase, making this technique more practical~\cite{lecun15}.
+For example robots can learn how to interact with an object with a curiosity behavior~\cite{laversannefinot18}.
+
+The validation of the behavior of an interactive system is an essential part of the evolution process.
+Thanks to it, behaviors can be categorized according to Table~\ref{table:computingaffordance}.
+There are several tools to prove programs with rational methods~\cite{chlipala13}.
+With these tools we can verify that the code is a correct implementation of an algorithm.
+Proving the behavior with rational methods of neural networks is a current challenge in machine learning.
+Similarly to interactive systems, they seem to be more suited for empirical evaluations.
+
+\subsection{Conclusion}
+
+Designing and implementing an interactive system is hard because it connects sensory, cognitive, software and hardware components.
+Mismatches between intended and actual behaviors can happen at any stage of the process.
+We presented a model of interactive systems behavior.
+It is an adaptation to Norman's action theory, which makes it easier to combine both model to describe the full phenomenon.
+
+
+Depending on their background, readers will find different things in this paper.
+Experts in human factors will get an insight on the implementation aspects of interactive devices.
+%It must not limit their creativity,
+Engineers will get a better insight on how implementation issues affect usability.
+It is also a checklist for designers, makers and practitioners when they are designing, implementing, upgrading or fixing interactive systems.
+
+In our future work, we will generalize the notion of computability.
+We conjecture that interactive systems suffer from a similar incompleteness phenomenon than formal systems~\cite{godel31}.
+
+\begin{idee}
+Our model certainly has limitations. It does not take into account sociological aspects, and more generally it does not discuss the design process (the Rode ref is awesome by the way). In its current form it focuses on functional and engineering aspects. We are interested in the question of the design and evolution of interactive systems though. It definitely involves more than engineering matters. \cite{huot13} is an interesting first answer. Our long term objective is to study the incompleteness nature of interactive systems, and it involves addressing these questions. However we consider this subject is out of the scope of the current submission.
+\end{idee}
+
+\section{Descriptive Case study (Printgets)}
+\begin{idee}
+The objectives and purpose of our model will be much clearer with an additional case study. We propose describing a vibrotactile system with capacitive input, within our framework. We will describe how implementation steps fit in our model: calibration, interpolation, filtering, thresholds, hysteresis, event fusion, output models, signal computing and physical response to command.
+\end{idee}
+\cite{frisson17}
+
+\section{analytic? Case study (Latency)}
+\cite{casiez17}