Early Usability Evaluation in Model Driven Framework
Lassaad Ben Ammar and Adel Mahfoudhi
University of Sfax, ENIS, CES Laboratory, Soukra km 3,5, B.P. 1173-3000, Sfax, Tunisia
Keywords:
MDE, User Interface, Early Usability Evaluation, Metrics.
Abstract:
Usability evaluation play a key role in the user interfaces development process. It is a crucial part that con-
strains the success of an interactive application. Usability evaluation is usually conducted by end users or
experts after the generation of the user interfaces. Therefore, the ability to go back and makes major changes
to the design is greatly reduced.
Recently, user interfaces engineering is moving towards Model Driven Development (MDD) process. The
conceptual models have become a primary artifact in the development process. Therefore, evaluating the us-
ability from the conceptual models would be a significant advantage with regard to saving time and resources.
The present paper proposes a model-based usability evaluation method which allows designers to focus on
the usability engineering from the conceptual models. The evaluation can be automated taking as input the
conceptual model that represent the system abstractly.
1 INTRODUCTION
The evaluation of user interfaces is a recognized prob-
lem and well explored in literature (Grislin and Kol-
ski, 1996). Several methods, techniques, tools and
criteria have been proposed to ensure the usability of
the user interfaces. However, usability evaluation is
usually conducted at the last stage of the development
process by end users or experts. At this stage, the abil-
ity to go back and makes major changes in the design
is greatly reduced.
In the last decade, the user interfaces engineer-
ing is moving towards Model Driven Development
(MDD) process. In this context, the Model Driven
Engineering (MDE) (Favre, 2004) proved quite ap-
propriate. This approach tends to develop user inter-
faces through the definition of models and their trans-
formations to a less abstract level to the code in the
target platform. A renowned work in this context is
the Cameleon project (Calvary et al., 2001). It pro-
vides a unifying reference framework for the user in-
terface development taken into consideration the con-
text of use. Such user interfaces are namely multi-
target. As drawback, this framework ignore usabil-
ity engineering and consider usability as a natural by-
product property of whatever approach being used.
Therefore, there is a need to extend the Cameleon
framework in order to promotes usability as a first
class entity in the development process.
The main objective of this paper is to proposes an ex-
tension of the Cameleon framework by considering
the usability engineering as a part of the development
process. We opted for the Cameleon framework since
it presents a unifying framework for the development
of multi-target user interface. The evaluation of the
usability can be conducted from the conceptual mod-
els.
We structure the remainder of this paper as follows.
While Section 2 presents an outline of the usabil-
ity models quoted in the literature, Section 3 pro-
vides a description of our proposed usability evalu-
ation method. A case study is presented in Section 4
in order to show the usefulness of our proposal to the
uncovering of potential usability problems. Finally,
Section 5 presents the conclusion and provides per-
spectives for future research work.
2 RELATED WORKS
Usability evaluation is often defined as methodolo-
gies for measuring the usability aspects of a user in-
terface and identifying specific problems (Nielsen,
1993). There exist several methods targeting the us-
ability evaluation of user interfaces. In this section,
we focus our interest in the analysis of model-based
methods since our main motivation is to integrate us-
ability issues into a model driven development ap-
23
Ben Ammar L. and Mahfoudhi A..
Early Usability Evaluation in Model Driven Framework.
DOI: 10.5220/0004411200230030
In Proceedings of the 15th International Conference on Enterprise Information Systems (ICEIS-2013), pages 23-30
ISBN: 978-989-8565-61-7
Copyright
c
2013 SCITEPRESS (Science and Technology Publications, Lda.)
proach.
The usability evaluation has attracted the atten-
tion of both Human Computer Interaction (HCI) com-
munity and Software Engineering (SE) communities.
The SE community proposed a quality model in the
ISO/IEC 9126-1 standard (ISO, 2001). In this model,
usability is decomposed into Learnability, Under-
standability, Operability, Attractiveness and Compli-
ance. However, the HCI community has shown in the
ISO/IEC 9241-11 standard (ISO, 1998) how usability
can be measured in term of Efficiency, Effectiveness
and User Satisfaction. Although both standards are
useful, they are too abstract and need to be extended
or adapted in order to be applied in a specific domain.
Some initiatives to extend both standards are pro-
posed over the last few years. (Seffah et al., 2006)
analyzed existing standards and surveys in order to
detect their limits and complementarities. Moreover,
the authors unify all these standards into a single con-
solidated model called Quality in Use Integrated Mea-
surement QUIM. The QUIM model includes metrics
that are based on the system code as well as on the
generated interface. This makes the application of the
QUIM to a model driven development process diffi-
cult.
(Abrahão and Insfrán, 2006) proposed an exten-
sion of the ISO/IEC 9126-1 usability model. The
added feature is intended to measure the user interface
usability at an early stage of a model driven develop-
ment process. The model contains subjective mea-
surement which raises the question about its applica-
bility at the intermediate artifacts. Besides, it lacks of
any detail about how various attributes are measured
and interpreted. An extension of this model is pre-
sented in (Fernandez et al., 2009).
The usability of a multi-platform user interface
generated with an MDE approach is evaluated in
(Aquino et al., 2010). The evaluation is conducted in
term of effectiveness, efficiency and user satisfaction.
The usability evaluation is based on the experiments
with end-users. This dependency is incompatible with
an early usability evaluation.
(Panach et al., 2011) proposes an early usability
measurement method. The usability evaluation is car-
ried out early in the development process since the
conceptual model. The main limitation of this pro-
posal is that metrics are specific to the OO-method
(Gómez et al., 2001). Therefore, they cannot be ap-
plied to other method, which is a disadvantage. They
need some adaptation in order to be used (adopted) in
other similar methods.
The analysis of the related works allows us to un-
derline some limitations. The system implementa-
tion is always a requirement to perform the evalua-
tion. Besides, the majority of the existing proposals
lack of guidelines about how usability attributes and
metrics are measured and interpreted. Regardless of
the approach, none takes into account the variation
of context elements during their process activities and
the influence it brings to the selection of the most rel-
evant attributes and metrics. Considering these limi-
tations, it becomes clear that usability evaluation in a
multi-target user interface development process is still
an immature area and many more research works are
needed. In order to covers this need, we propose to in-
tegrate usability issues into the Cameleon framework.
The goals of our proposal are: 1) the evaluation pro-
cess must be carried out quickly in the development
process and independently of the system implementa-
tion, 2) the evaluation must be done in an automation
way. The proposed method is intended to evaluate he
usability from the conceptual model. For that reason,
we propose a usability model wherein usability met-
rics are based on the conceptual primitives. Metrics
are extracted from existing usability guidelines such
as (Bastien and Scapin, 1993), (M. Leavit, 2006) and
(Panach et al., 2011) with respect to the following re-
quirements: 1) possibility to be quantified based on
conceptual primitives and 2) relation with one of the
context of use elements (user, platform, environment).
3 PROPOSED USABILITY
EVALUATION METHOD
3.1 Overview
The Cameleon framework provides a user interface
development process which defines four essential lev-
els of abstraction: Task & Domain, Abstract User
Interface (AUI), Concrete User Interface (CUI) and
Final User Interface (FUI). The development process
takes as input the conceptual models in order to gen-
erate the final executable user interface. In this frame-
work, the conceptual models covers the AUI and the
CUI levels. The CUI model is the most affected by
usability. Therefore, we opted to perform the evalu-
ation from this level. To do that, we proposes a set
of usability attributes which can be quantified from
by means of metrics which are based on the concep-
tual primitives of this model. The usability evaluation
module take as input the CUI model and the usability
model. As outcome, it provides a set of specific us-
ability problems. Problems are related to the concep-
tual primitives that are affected by it. These problems
are used to suggest some recommendationsin order to
correct the previous stages or the transformation rules
ICEIS2013-15thInternationalConferenceonEnterpriseInformationSystems
24
Figure 1: The proposed Usability Measurement Method.
(see Fig.1).
The proposed usability model extend that pre-
sented in the ISO/IEC 9126-1 standard. In such model
usability is decomposed into five sub-characteristics
that are defined as follows:
Learnability: the capability of the software prod-
uct to enable the user to learn its application.
Understandability: the capability of the software
product to enable the user to understand whether
the software is suitable, and how it can be used for
particular tasks and conditions of use.
Operability: the capability of the software product
to enable the user to operate and control it.
Attractiveness: the capability of the software
product to be attractive to the user.
Compliance: The capability of the software prod-
uct to adhere to standards, conventions, style
guides or regulations relating to usability.
Since the sub-characteristics have been described ab-
stractly, we have analyzed some usability guide-
lines presented in the literature ((Bastien and Scapin,
1993), (M. Leavit, 2006), (Panach et al., 2011)) in
order to extract and adapt more detailed usability at-
tributes. Next Sub-Section shows our proposal to de-
compose the former sub-characteristics into measur-
able attributes.
3.2 Attribute Specification
The Learnability can be measured in terms of Prompt-
ing, Predictability and Informative Feedback. The
Prompting refers to the means available to advise, ori-
ent, inform, instruct, and guide the users throughout
their interactions with a computer. The Predictability
refers to the ease with which a user can predict his
future action. The Informative Feedback concerns the
response of the system to the user action. Learnabil-
ity attributes are closely related to the user character-
istics. They can be considered as essential in order to
guarantee a high level of user satisfaction.
In order to be able to measure the Understandabil-
ity sub-characteristic, we propose four measurable at-
tributes. The first attribute is the Information Den-
sity which is the degree in which the system will dis-
play/demand the information to/from the user in each
interface. The Brevity focus on the reduction of the
level of cognitive efforts of the user (number of ac-
tion steps). The short term memory capacity is lim-
ited. Consequently, shorter entries reduce consider-
ably the probability of making errors. Besides, the
Navigability pertains to the ease with which a user
can move around in the application. Finally, Message
Concision concerns the use of few words while keep-
ing expressiveness in the error message. The under-
standability attributes are closely related to the plat-
form features. For example, the screen size has strong
influences to the information density, the navigability
and the brevity attributes.
Operability includes attributes that facilitate the
user’s control and operation of the system. We pro-
pose the following attributes: User Operation Can-
cellability, the possibility to cancel action without
harmful effect to the normal operation; User Oper-
ation Undoability, the proportion of actions that can
be undone without harmful effect to the normal op-
eration; Explicit user action, the system should per-
form only actions requested by user; Error Preven-
tion, available means to detect and prevent data en-
try errors, command errors, or actions with destruc-
tive consequences. Interactive systems should al-
low a high level of control to users especially those
with a low level of experience. Hence, user interface
is obliged to present interface components allowing
such control. The screen size of the platform being
used can affect this control when it does not allow
displaying button like undo, cancel, validate, etc.
The Attractiveness sub-characteristic includes the at-
tributes of software product that are related to the aes-
thetic design to make it attractive to user. We argue
that some aspect of attractiveness can be measured
with regard to the Font Style Uniformity and Color
Uniformity. The Consistency measure the maintain-
ing of the design choice to similar contexts. The user
preferences in term of color or font style are related
to the attractiveness attributes. It should be noted that
some environment features (e.g. indoor/outdoor, lu-
minosity level) affect the choice of the color in order
to obtain a good contrast which give more clear infor-
mation.
Fig.2 shows an overview of our proposal for at-
tributes specification.
EarlyUsabilityEvaluationinModelDrivenFramework
25
Figure 2: The Proposed Usability Model.
3.3 Metric Definition
In order to be able to measure the internal attributes
proposed in the previous Section, we need to define
the metrics required to measure each one. It should
be noted that metrics are intended to measure the in-
ternal usability from the conceptual models that is
why they are founded based on the conceptual primi-
tives of the method presented in (Bouchelligua et al.,
2010). Even though the metrics are specified to this
method, the concept of each one can be applied to any
MDE method with similar conceptual primitives. The
main reason of the choice of the method presented in
(Bouchelligua et al., 2010) is that this method is com-
pliant to the Cameleon framework and use the BPMN
notation to describe the user interface models. The
BPMN notation is based on the Petri networks which
allows the validation of metrics. In what follows, we
list the definition of some examples of these metrics.
Information Density. The average of field edit per
UI.
ID1 =
n
i=1
xi/
n
i=1
yi. (1)
x (UIFieldEdit), y (UIWindow).
The maximum number of elements per UI.
ID2 =
n
i=1
xi. (2)
x (UIField).
Brevity. We propose the number of step required to
accomplish a goal or a task from a well designated
context.
BR = distance(x,y). (3)
x,y (UIWindow), distance(x,y) returns the distance
between x and y.
Navigability. The average of navigation elements
per UI.
NB =
n
i=1
xi/
n
i=1
yi. (4)
x (UIFieldNavigation), y (UIWindow).
Message Concision. Since the quality of the mes-
sage is a subjective measure, we propose the number
of word as an internal metric to measure the quality
of the message. The number of word in a message
MC =
n
i=1
xi. (5)
x (word in UIDialogBox).
Error Prevention. To prevent user against error
while entering data, we propose to use a drop down
list instead of text field when the input element have
a set of accepted values.
ERP =
n
i=1
dropdownlist(x)/n. (6)
x (UIFieldIn with limited values), dropdownlist re-
turn the number of UIDropDownList.
3.4 Indicator Definition
The metrics defined previously provides a numerical
value that need to have a meaning in order to be in-
terpreted. The mechanism of indicator is restored in
order to reach such goal. It consists in the attribu-
tion of qualitative values to each numerical one. Such
qualitative values can be summarized in: Very Good
(VG), Good (G), Medium (M), Bad (B) and Very Bad
(VB). For each qualitative value, we assign a numer-
ical range. The ranges are defined build on some us-
ability guidelines and heuristics described in the liter-
ature. Next, we detail the numeric ranges associated
with some metrics in order to be considered as a Very
Good value.
Information Density: several usability guidelines
recommend minimizing the density of a user in-
terface (M. Leavit, 2006). We define a maximum
number of elements per user interface to keep
a good equilibrium between information density
and white space: 15 input elements (ID1), 10 ac-
tion elements (ID2), 7 navigation elements (ID3),
and 20 elements in total (ID4) (Panach et al.,
2011).
Brevity: some research studies have demonstrated
that the human memory has the capacity to retain
a maximum number of 3 scenarios (Lacob, 2003).
Each task or goals requiring more than 3 steps
(counted in keystrokes) to be reached decreases
usability (Minimal Action MA).
ICEIS2013-15thInternationalConferenceonEnterpriseInformationSystems
26
Navigability: some studies have demonstrated
that the first level navigational target (Navigation
Breadth NB) should not exceed 7 (Murata et al.,
2001).
Message Concision: since the quality of the mes-
sage can be evaluated only by the end-user, the
number of the word in a message is proposed as an
internal metrics to assess message quality (Word
Number WN). A maximum of 15 words is recom-
mended in a message (Panach et al., 2011).
Error Prevention: The system must provide mech-
anisms to keep the user from making mistakes
(Bastien and Scapin, 1993). One way to avoid
mistakes is the use of ListBoxes for enumerated
values. (Panach et al., 2011) recommend at least
90% of enumerated values must be shown in a
ListBox to improve usability (ERP).
Metrics which are extracted from the proposition of
(Panach et al., 2011), they are extracted with their
ranges of values. in fact, this ranges are empirically
validated. For the others metrics, the ranges of values
to consider the numeric value as Very Good are taken
into consideration in order to estimate the value to be
considered as Very Bad. The Medium, Bad and Good
values are equitably distributed once we have the two
extremes. The Table 1 shows the list of indicators that
we have been defined.
3.5 Automatic Usability Evaluation
Process
Conducting the usability measurement manually is a
tedious task. That is why we propose to automatize
this process by implementing it as a model transfor-
mation process. The model transformation process re-
quires two model as input (the user interface model
and the usability model) and provides as outcome a
usability report which contains the detected usability
problem. In the model transformation literature, the
definition of the meta-model
1
is a prerequisite in or-
der to use a model.
Concerning the usability model, the proposed
meta-model is composed of hierarchy with four lev-
els:
Sub-characteristic: A set of abstract concept used
to define usability.
Attribute: An entity which can be ensured during
the model transformation process.
1
A meta-model is a language that can express models.
It defines the concepts and relationships between concepts
required for the expression of the model.
Metric: A set of metric used to quantify an at-
tribute.
Indicator: qualitative value assigned to each set of
values used to rank metric to give meaning.
Figure 3: Usability Meta-Model.
With regard to the usability report, we propose a sim-
ple meta-model which explain the usability problem
using the following scheme: the description of the
usability problem, the related attribute is the sub-
characteristic and attribute in the model that are af-
fected by the usability problem, the level of the de-
tected problem and the recommendation to solve such
problem.
Fig. 4 shows the proposed usability report meta-
model.
Figure 4: Usability Report Meta-Model.
It should be noted that the use of internal usability
attributes and metrics which are based on the concep-
tual models is recommended as an appealing way to
predict the usability perceived by end-users (Panach
et al., 2011). However, the validity of the proposed
method need to be tested empirically.
EarlyUsabilityEvaluationinModelDrivenFramework
27
Table 1: Proposed indicators.
Metric VG G M B VB
ID1 15 15ID120 20ID125 25ID130 ID130
ID2 10 10ID213 13ID216 16ID219 ID219
MA 2 2MA4 4MA5 5MA6 MA6
NB 7 5NB10 10NB13 13NB16 NB16
WN 15 15WN20 20WN25 25WN30 WN30
4 AN ILLUSTRATIVE CASE
STUDY
This section investigates a case study in order to il-
lustrate the applicability of our proposal. The pur-
pose is to show the usefulness of our proposal in the
assessment of the user interface usability. The re-
search question addressed by this case study is: Does
the proposal contribute to uncover usability problem
since the conceptual model?
The object of the case study is a Tourist Guide
System (TGS). The scenario is adapted from (Hariri,
2008). The mayor’s office of a touristic town decides
to provide visitors a tourist guide system. The system
allows the visitors to choose the visit type (tourism,
shopping, work, etc.). During the visit, the TGS of-
fers tourists several choices of visit traverses, indicate
the paths to follow and provides informationabout the
nearby points of interests. Tourists can use the system
to find places (restaurant, hotel, etc.) and know the
itineraries of visits. The system will run on terminals
of visitors (laptop, PDA, mobile phone, etc.). There-
fore, the user interface must adapt to the context of
use. For example, the computing devices being used,
the tourist language, preference, etc. It should be able
also to bring a feeling of comfort and ease of use in
order to increase the satisfaction degree.
Since the tourist guide system is large, we focus
our interests in the generation of the concrete user
interface for the «Search itinerary» task. We sup-
pose to have the abstract user interface from Fig 5
as a result of the transformation of the task model
«Search itinerary» following the model transforma-
tion explained in details in (Bouchelliguaet al., 2010).
The result of the transformation is an XML file which
is in accordance with the AUI metamodel (left part
of Fig. 5). To better clear up the user interface lay-
out, we develop an editor with the Graphical Model-
ing framework (GMF) of eclipse. The sketch of the
user interface presented by the editor is shown in the
right part of Fig. 5.
The abstract user interface contains a UIGroup
called «Search itinerary» which gives access to two
UIUnitSuit called «Enter Coordinates» and «Result».
Figure 5: Abstract User Interface.
The «Enter Cordinates» container gives access to
specify the starting point and the destination point.
The tourist should choose the category (Address,
Landmark, Station) before specifying the starting or
the destination point. The validation of the coordi-
nates allows tourist to choice the planning (Pedes-
trian, Cyclable, Vehicule, Metro, Train, Bus). Af-
ter that, the TGS system shows the list of possible
itineraries. The TGS system can shows the list in a
map.
Figure 6: Concrete User Interface.
An ordinary transformation which takes as input
the abstract user interface model allows producing the
concrete user interface model of Fig. 6. It should be
noted that this transformation was done taken into ac-
ICEIS2013-15thInternationalConferenceonEnterpriseInformationSystems
28
count a context of use defined by the analyst. The
context is the following: a laptop as an interactive de-
vice (normal screen size), an Englishman as a tourist
with a low level of experience.
In order to evaluate the concrete user interface, we
pursue a reduced version of the usability evaluation
process presented in (Ammar et al., 2012). The pur-
pose of the evaluation is to evaluate the usefulness of
the proposed model to discover the usability problems
presented in the evaluated artifact. The product part
to be evaluated is the concrete user interface model.
The selected attributes are the Information Density
and the Error Prevention. The metrics selected to
evaluate the former attributes are ID2 and ERP. The
indicators are those presented in Tab. 1.
The result of the evaluation is a usability report
model which contains the detected problems (see Fig.
7).
Figure 7: Usability Evaluation Process.
Usability problem N1: There is no means which
preventsthe user against error while entering data.
Related attribute: Operability / Error Prevention.
Level: VB
Recommendation: Each input element with lim-
ited values will be displayed in a dropdown list
to protect user against error while entering values
(e.g. typos).
Usability problem N2: There are enough elements
in the user interface which increase the informa-
tion density.
Related attribute: Understandability / Information
Density
Level:B
Recommendation: It is recommended to replace
panels with a window.
The second transformation to be conducted takes an
«iPAQ Hx2490 Pocket PC» as platform. The migra-
tion to such platform raises a new redistribution of
the user interface elements. The small screen size
(240x320) is not sufficient to display all information.
The number of the concrete component to be grouped
is limited to the maximum number of concepts that
can be manipulated (5 in the case of «iPAQ Hx2490
Pocket PC»). Therefore, the user interface elements
are redistributed on several windows. The redistri-
bution of interface elements on several windows will
bring more steps to reach the goal. It should be noted
that with a small screen size the Information Den-
sity and the Brevity are the most relevant usability
attributes. The problem is that these two attributes
have a contradictory impact. It is recommended to
distribute the concrete components on several screens
in order to obtain better Information Density. How-
ever, redistribute elements from one screen to several
will influence negatively the Brevity attributes.
Learned Lesson. The case study allow us to learn
more about the potentialities and limitations of our
proposal and how it can be improved. The proposed
method allows the detection of several usability prob-
lems since the early stage of the development process.
The evaluation process may be a means to discover
which usability attributes are directly supported by
the modeling primitives or to discover limitations in
the expressiveness of these artifacts. The ranks of in-
dicators are extracted from existing studies which do
not consider the context variation. Therefore, many
more experimentationsare needed in order to propose
a repository of indicators in several cases (medium
screen size, small screen size, large screen size). The
same things for other metrics which are influenced by
the context variation. Another important aspect which
must be studied is the contradictory affect of usabil-
ity attributes. For example, for computing platform
with small screen size the information density and the
brevity has a contradictor affect. Increasing the in-
formation density will decrease certainly the brevity
attribute. Finally, the case study was very useful for
us. We can state that the method presented in this pa-
per can be a building block of an MDE method that
generate a user interface taken into account the con-
text variation of use while respecting human factors.
5 CONCLUSIONS AND FUTURE
RESEARCH WORKS
This paper presents a method for integrating usabil-
ity issue as a part of a plastic user interface devel-
opment process. The proposed method extends the
EarlyUsabilityEvaluationinModelDrivenFramework
29
Cameleon reference framework by integrating usabil-
ity issues to the development process. The early us-
ability measurement has the objective to discover the
usability problems presented in the intermediate arti-
fact. Therefore, the present paper proposes a usability
model which decomposes the usability on measurable
attributes and metrics that are based on the conceptual
primitives. Metrics are extracted from existing usabil-
ity guidelines with respect to their relation with con-
text features (user characteristics, platform features,
etc.). Many details about how to measure and inter-
prets attributes are presented.
If compared to the existing proposals, our frame-
work presents three main advantages: 1) costs are
very low: internal usability evaluation reduce con-
siderably the development cost, 2) system does not
have to be implemented, 3) it provides a proper details
about how to measure attributes and interpret their
scores.
The continuity of our research work leads directly
to the implementation of the usability driven model
transformation. We have to investigate the relation-
ship between usability attributes and their contradic-
tory influence to the whole usability of the user inter-
face. An empirical evaluation of the early usability
measurement is recommended to clearly demonstrate
the coherence between values obtained by our pro-
posal and those perceived by end-user.
REFERENCES
(1998). ISO/IEC 9241. Ergonomic Requirements for Office
Work with Visual Display Terminals (VDTs). ISO/IEC.
(2001). ISO/IEC 9126. Software engineering Product
quality. ISO/IEC.
Abrahão, S. M. and Insfrán, E. (2006). Early usability eval-
uation in model driven architecture environments. In
QSIC, pages 287–294.
Ammar, L. B., Mahfoudhi, A., and Abid, M. (2012).
A usability evaluation process for plastic user inter-
face generated with an mde approach. In Software
Engineering Research and Practice, pages 323–329.
CSREA Press.
Aquino, N., Vanderdonckt, J., Condori-Fernández, N., Di-
este, O., and Pastor, O. (2010). Usability evalua-
tion of multi-device/platform user interfaces gener-
ated by model-driven engineering. In Proceedings
of the 2010 ACM-IEEE International Symposium on
Empirical Software Engineering and Measurement,
ESEM ’10, pages 30:1–30:10, New York, NY, USA.
ACM.
Bastien, J. C. and Scapin, D. L. (1993). Ergonomic crite-
ria for the evaluation of human-computer interfaces.
Technical Report RT-0156, INRIA.
Bouchelligua, W., Mahfoudhi, A., Mezhoudi, N., Dâassi,
O., and Abed, M. (2010). User interfaces modelling
of workflow information systems. In EOMAS, pages
143–163.
Calvary, G., Coutaz, J., and Thevenin, D. (2001). A unify-
ing reference framework for the development of plas-
tic user interfaces. In Proceedings of the 8th IFIP
International Conference on Engineering for Human-
Computer Interaction, EHCI ’01, pages 173–192,
London, UK, UK. Springer-Verlag.
Favre, J. M. (2004). Toward a Basic Theory to Model
Driven Engineering.
Fernandez, A., Insfran, E., and Abrahão, S. (2009). Inte-
grating a usability model into model-driven web de-
velopment processes. In Proceedings of the 10th In-
ternational Conference on Web Information Systems
Engineering, WISE ’09, pages 497–510, Berlin, Hei-
delberg. Springer-Verlag.
Gómez, J., Cachero, C., and Pastor, O. (2001). Con-
ceptual modeling of device-independent web applica-
tions. IEEE MultiMedia, 8(2):26–39.
Grislin, M. and Kolski, C. (1996). Human-machine in-
terface evaluation during the development of interac-
tives systems. TSI. Technique et science informatiques
ISSN 0752-4072 CODEN TTSIDJ, (3):265–296.
Hariri, M. (2008). Contribution à une méthode de concep-
tion et génération d’interface homme-machine plas-
tique.
Lacob, M. E. (2003). Readability and Usability Guidelines.
M. Leavit, B. S. (2006). Research Based Web Design &
Usability Guidelines.
Murata, M., Uchimoto, K., Ma, Q., and Isahara, H. (2001).
Magical number seven plus or minus two. In Proceed-
ings of the Second International Conference on Com-
putational Linguistics and Intelligent Text Processing,
pages 43–52, London, UK, UK. Springer-Verlag.
Nielsen, J. (1993). Usability Engineering. Morgan Kauf-
mann Publishers Inc., San Francisco, CA, USA.
Panach, J. I., Condori-Fernández, N., Vos, T. E. J., Aquino,
N., and Valverde, F. (2011). Early usability mea-
surement in model-driven development: Definition
and empirical evaluation. International Journal of
Software Engineering and Knowledge Engineering,
21(3):339–365.
Seffah, A., Donyaee, M., Kline, R. B., and Padda, H. K.
(2006). Usability measurement and metrics: A con-
solidated model. Software Quality Control, 14:159–
178.
ICEIS2013-15thInternationalConferenceonEnterpriseInformationSystems
30