Towa ds he Quali y Imp o emen o Web Applica ions by
Neu oscience Techniques
F. J. Domínguez-Mayo1, G. Kub yk2, M. J. Escalona1, G. Denhiè e2, M. Mejias1 and C. Tijus2
1Compu e Languages and Sys ems depa men , Uni e si y o Se ille, Se ille, Spain
2Equipe CHA (Cogni ions Humaine e A i icielle), LUTIN, Uni e si é Pa is 8, Pa is, F ance
Keywo ds: Use -Cen e ed Design, Web Applica ions, Neu oscience, Requi emen s Enginee ing, Quali y.
Abs ac : Use -cen e ed design no only equi es designe s o analyse and an icipa e how use s a e likely o use a Web
applica ion, bu also o alida e hei assump ions wi h ega d o use beha iou in eal en i onmen s.
Cogni i e neu oscience, o i s pa , add esses he ques ions o how psychological unc ions a e p oduced by
neu al ci cui y. The eme gence o powe ul new measu emen echniques
allows neu oscien is s and psychologis s o add ess abs ac ques ions such as how human cogni ion and
emo ion a e mapped o speci ic neu al subs a es. This pape ocus on he alida ion o use -cen e ed
designs and equi emen s o Web applica ions by neu oscience echniques and sugges he use o hese
echniques o achie e e icien and e ec i eness alida ed designs by eal beha io o po en ial use s.
1 INTRODUCTION
Neu oscience is a he e ogeneous ield, consis ing o
many and a ious sub-disciplines (e.g., Cogni i e
Psychology, Beha io al Neu oscience, and
Beha io al Gene ics). In o de o ou unde s anding
o he b ain o con inue o deepen, i is necessa y
ha hese sub-disciplines a e able o sha e da a and
indings in a meaning ul way;
Neu oeconomics (Ka ma ka , 2011) is an
in e disciplina y ield ha seeks o explain
human decision making, he abili y o p ocess
mul iple al e na i es and o choose an op imal
cou se o ac ion. I s udies how economic beha io
can shape ou unde s anding o he b ain, and how
neu oscien i ic disco e ies can cons ain and guide
models o economics. Beha io al economics
(Ka ma ka , 2011) eme ged o accoun o hese
anomalies by in eg a ing social, cogni i e, and
emo ional ac o s in unde s anding economic
decisions. Neu oeconomics adds ano he laye by
using neu oscien i ic me hods in unde s anding he
in e play be ween economic beha io and neu al
mechanisms. By using ools om a ious ields,
some schola s claim ha neu oeconomics o e s a
mo e in eg a i e way o unde s anding decision
making. Mo e speci ic o ou pu poses is
Neu oin o ma ics (Adee and Sally, 2008) which is a
esea ch ield conce ned wi h he o ganiza ion o
neu oscience da a by he applica ion o
compu a ional models and analy ical ools. These
a eas o esea ch a e impo an o he in eg a ion
and analysis o inc easingly la ge- olume, high-
dimensional, and ine-g ain expe imen al da a.
Neu oin o ma icians p o ide compu a ional ools,
ma hema ical models, and c ea e in e ope able
da abases o clinicians and esea ch scien is s.
The e a e h ee main di ec ions whe e
neu oin o ma ics has o be applied (INCF, 2013):
 The de elopmen o ools and da abases o
managemen and sha ing o neu oscience da a a
all le els o analysis,
 The de elopmen o ools o analyzing and
modeling neu oscience da a,
 The de elopmen o compu a ional models o he
ne ous sys em and neu al p ocesses.
Neu oma ke ing is a new ield o ma ke ing
esea ch ha s udies cus ome s' senso imo o ,
cogni i e, and a ec i e esponse o ma ke ing
s imuli. In ac , ma ke ing ield is ela ed o quali y
wi h he s a egic idea ha we ha e o assu e ha he
so wa e p oduc is accep ed by he cus ome . So,
we can use all hese echniques and c oss hem wi h
neu oin o ma ics o achie e he quali y imp o emen
o Web applic ions and Web applica ions
de elopmen p ocess. Ac ually, neu oma ke ing
esea ch aised in e es o bo h academic and
business side. In ac , ce ain companies, pa icula ly
337
Domínguez-Mayo F., Kub yk G., Escalona M., Denhiè e G., Mejías M. and Tijus C..
Towa ds he Quali y Imp o emen o Web Applica ions by Neu oscience Techniques.
DOI: 10.5220/0005040303370344
In P oceedings o he 9 h In e na ional Con e ence on So wa e Enginee ing and Applica ions (ICSOFT-EA-2014), pages 337-344
ISBN: 978-989-758-036-9
Copy igh c
2014 SCITEPRESS (Science and Technology Publica ions, Lda.)
hose wi h la ge-scale goals, ha e in es ed in hei
own labo a o ies, science pe sonnel and / o
pa ne ships wi h academia (Ka ma ka , 2011).
Then, Neu oscience is cu en ly an in e disciplina y
science ha collabo a es wi h o he ields like
economics, ma ke ing o in o ma ics. This science
could be use ul o be applied o quali y imp o emen
o Web applica ions and Web applica ions
de elopmen p ocess. Rega ding quali y, we mean
ha he Web applica ion mus ul ill all equi emen s
ha cus ome s eally demand. In addi ion, i is e y
impo an o con ol ha he so wa e de elopmen
p ocess is he mos adequa e o so wa e de elope s
o design he so wa e p oduc ha we a e looking
o ou cus ome s. Thus, neu oscience applies o
achie e quali y imp o emen in Web applica ions
and Web applica ions de elopmen p ocesses.
As ega ds quali y, i is a ele an aspec o
conside in he so wa e enginee ing con ex . The e
a e se e al di e en de ini ions in he li e a u e like,
o example, con o mance o use expec a ions,
which is o en desc ibed as he “ i ness o pu pose”
o a piece o so wa e. Ano he de ini ion o quali y
ela ed o so wa e quali y measu es conce ns he
high quali y o so wa e design (quali y o design)
and he high le el so wa e con o ms o ha design
(quali y o con o mance). In ac , ega ding quali y,
we basically ocus on quali y o he so wa e p oduc
o quali y o he so wa e de elopmen p ocess. On
he one hand, quali y o so wa e p oduc eally
means ha he so wa e p oduc mee s all
equi emen s and needs ha cus ome s demand. On
he o he hand, i is e y impo an o con ol he
so wa e de elopmen p ocess o pe o m he
so wa e p oduc e ec i ely and comple e all
cus ome s’ needs. Then, o implemen cus ome ’s
equi emen s is a key aspec o cus ome s o accep
so wa e p oduc s.
No mally, good e e ences om sa is ied
cus ome s enable business g ow h in mos
companies. A so wa e de elopmen company ha is
esponsi e o eques ing and demons a ing a "can
do" a i ude will gain compe i i e ad an ages. In
gene al, hese bene i s a e ob ained om medium o
long- e m pe iods. In e nal bene i s, including cos
educ ions om imp o ed quali y le els, a e o en
achie ed much as e . P oduc ion cos s can be
educed when p oduc ion p ocesses a e s eamlined
o when hei e ec i eness inc eases. This can be
achie ed h ough an imp o ed p ocess con ol ha
educes he undesi able p oduc ion o unable pa s.
Sho ened machine se up imes and immedia e
a ailabili y o comple e p oduc ion in o ma ion can
u he imp o e p oduc i i y. Quali y p o essionals
ha e s udied aluable imp o emen echniques ha
lead o educe p oduc ion cos s h ough quali y
imp o emen s.
This pape comp ises he ollowing sec ions.
A e his in oduc ion, Sec ion II analyzes some
ela ed wo ks and concep s ound in he li e a u e.
Then, Sec ion III p oposes he NDT me hodology o
cap u e and de ine Web applica ion equi emen s and
psychological/emo ional expe iences o be expec ed
by use s. NDT is a Model-D i en Web de elopmen
app oach o he de elopmen o Web applica ions
which is mainly ocused on equi emen s. Sec ion IV
p oposes QuEF o he de ini ion o a Quali y Model
om he equi emen s and psychological/emo ional
expe iences de ined by he NDT me hodology. QuEF
p o ides empla es and me hods o de ine he Quali y
Model and de ines a li e cycle o he Quali y Model
ha ensu es he quali y con inual imp o emen o he
model. Then, Sec ion V explains how his Quali y
Model can be alida ed by neu oscience echniques.
Concluding he pape is Sec ion VI by s a ing some
lea ned lessons and ongoing wo k.
2 RELATED WORKS AND
CONCEPTS
As a as quali y in Web applica ions based on
neu oscience is conce ned, lo s o pape s desc ibe
he necessi y o assu ing quali y and con olling he
de elopmen p ocess o hese Web applica ions o
so wa e p oduc s.
Ba salou (Ba salou, 2012) explains ha he
human concep ual sys em con ains people's
knowledge o he wo ld. The concep ual sys em
ep esen s componen s o expe ience, such as
knowledge abou se ings, objec s, people, ac ions,
e en s, men al s a es, p ope ies and ela ions, a he
han con aining holis ic images o expe ience.
Componen ial knowledge in he concep ual sys em
suppo s a wide a ie y o simple cogni i e
ope a ions including ca ego iza ion, in e ence,
ep esen a ion o p oposi ions and p oduc i e
c ea ion o no el concep ualiza ions.
Wang and Pa el (Wang and Pa el, 2009) explo e
he basic p ope ies o so wa e and look o he
cogni i e compu e ounda ions o so wa e
enginee ing. They explain ha he na u e o so wa e
is cha ac e ized by compu e , beha io al,
ma hema ical and cogni i e p ope ies. The au ho s
iden i y a se o undamen al cogni i e cons ain s o
so wa e enginee ing, such as in angibili y,
complexi y, inde e minacy, di e si y,
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polymo phism, inexp essi eness, inexplici
embodimen and unquan i iable quali y measu es.
Ho man (Ho man, 2009) examines non- echnical
aspec s o so wa e quali y pe cep ion and p oposes
u he esea ch ac i i ies on his subjec . Cogni i e
science, psychology, mic oeconomics and o he
human-o ien ed sciences do analyze human
beha io , cogni ion and decision-making p ocesses.
The e o e, his pape ecommends ha he
p o essional p oduc pe cep ion should be analyzed
as a so wa e p oduc .
Jean-Michel Hoc e iews he s a e-o - he-a o
cogni i e coope a ion in Hoc (Hoc, 2009) o ex end
an indi idual cogni i e a chi ec u e and handle hese
si ua ions, by combining p i a e and coope a i e
ac i i ies ha a e highly ask-o ien ed. In Hoc (Hoc,
2009), coope a ion is ackled as he managemen o
in e e ence be ween indi idual ac i i ies o
acili a e he eam membe s' sub- asks and he eam's
common ask, i any. This e iew o he li e a u e is
a s ep owa ds inding ou a heo e ical app oach ha
could be ele an o e alua e coope a ion and design
assis ance in di e se domains.
Zay se e al. (Zay se and Mo ison, 2012)
iden i y mul iple a eas whe e con inuous in eg a ion
can be employed o u he inc ease he quali y o
neu oin o ma ics p ojec s by imp o ing
de elopmen p ac ices and inco po a ing app op ia e
de elopmen ools. Finally, hey discuss wha
measu es can be aken o lowe he ba ie o
de elope s o neu oin o ma ics applica ions o adop
his use ul echnique.
As ega ds in e na ional s anda ds o so wa e
p oduc s quali y, ISO/IEC 25000:2005 (ISO/IEC
25000:2005, 2014) p o ides guidance on he use o
he new se ies o In e na ional S anda ds named
So wa e P oduc Quali y Requi emen s and
E alua ion (SQuaRE). This guide aims o o e a
gene al o e iew o SQuaRE con en s, common
e e ence models and de ini ions, as well as he
ela ionship among he documen s, allowing use s o
his guide o be e unde s and hese se ies o
In e na ional S anda ds, acco ding o hei pu pose
o use.
3 A MODEL-DRIVEN WEB
DEVELOPMENT
METHODOLOGY BASED ON
WEB REQUIREMENTS
TREATMENT
NDT (Na iga ional De elopmen Techniques)
(Escalona and A agón, 2008), is a me hodological
app oach o ien ed o he Web Enginee ing. Web
Enginee ing is a speci ic line in he So wa e
Enginee ing ha o e s speci ic models and
echniques o deal wi h he special cha ac e is ics o
Web sys ems. In he las yea s, se e al web
app oaches we e de ined: OOHDM, UWE, WebML
o OOHa e only some examples. Howe e ,
compa a i e s udies concluded ha hese app oaches
a e mainly ocussed on analysis and design phases
and he e is an impo an gap in Web equi emen s
ea men .
NDT is o ien ed o co e his gap. Thus, i is
mainly ocussed on he equi emen s and he analysis
phases, al hough in i s las e sions i co e s he hole
li e cycle. I is an app oach de ined in he Model
D i en pa adigm and i o e s a sui able and easy
me hodological en i onmen . The mos impo an
cha ac e is ics o his app oach a e:
 I o e s a iendly in e ace o he inal use in
he equi emen s phase.
 I is based on a se o MOF me amodels ha a e
anspa en o he de elopmen eam. These
me amodels a e he base o NDT de elopmen
p ocess.
 I ollows he aceabili y o he equi emen s
om hei de ini ion un il hei analysis, o e ing
a sys ema ic p ocess based on o mal
ans o ma ions de ined by QVT ha p oceeds
un il implemen a ion.
 NDT is comple ely UML based, so i is
compa ible wi h o he app oaches such as
Mé ica.
NDT is being applied in se e al eal p ojec s. I
was a e y applied me hodology in eal en i onmen
wi h e y good esul s. Al hough NDT was ini ially
suppo ed by NDT-Tool, oday i is no used and i is
no being e iewed. In any case, in NDT-
Tool sec ion in o ma ion abou his ool can be
ound.
Today, NDT has e ol ed o be used in p ac ical
en i onmen s, and is now one o he bes
me hodological p oposals add essing he
de elopmen o many so wa e p ojec s, speci ically
p ojec s aimed a he web. IWT2 o e s a sui e o
suppo ools ha apply he NDT me hodology o
you so wa e p ojec . This oolki is dis ibu ed
unde he name NDT-Sui e (Ga cía-Ga cía e Al,
2012). Thus, wi h he NDT me hodology no only is
necessa y o speci y use equi emen s bu
psychological/emo ional expe iences o be expec ed
by use s.
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4 A FRAMEWORK TO MANAGE
QUALITY OF WEB
APPLICATIONS
Once Web applica ion equi emen s and
psychological/emo ional expe iences o be expec ed
by use s is well de ined, i is necessa y o assu e he
quali y con inual imp o emen o hese concep s on
Web applica ions. Besides, i is necessa y o de ine a
quali y model based on hese equi emen s ha mus
be alida ed a e wa ds by neu oscience echniques.
QuEF (Quali y E alua ion F amewo k)
(Dominguez-Mayo e al., 2012a; Dominguez-Mayo
e al., 2012b) is a amewo k o manage quali y o
any p oduc o p ocess, which aims o en o ce
quali y and con inuous quali y imp o emen o Web
applica ions and so wa e de elopmen p ocess by
means o de ining a quali y model. QuEF is a
amewo k o manage quali y o en i ies (p oduc s,
p ocesses, se ices, o ganiza ions, e c.) in any
con ex and domains. In p e ious wo ks, his
amewo k was used o manage quali y o Model-
D i en Web de elopmen me hodologies
(Dominguez-Mayo e al., 2012b). QuEF has been
adap ed o designe s o any p oduc s and p ocesses
o analyze, e alua e, con ol and inc ease he quali y
and imp o e hei design and esul s. In addi ion,
his amewo k can be also used o consume s o
iden i y he mos sui able p oduc o p ocess o
hem and decide which one will be used depend on
hei p ojec scope.
This amewo k desc ibes empla es and
me hods o de ine a speci ic quali y model o he
domain unde s udy. I also o e s a me hod in o de
o ins an ia e he quali y model, e alua e i and
calcula e p e e ences o hei elemen s. Besides, he
amewo k includes he de ini ion o a se o phases
o en o ce he quali y con inual imp o emen o he
quali y model. This is he mos impo an aspec ha
all he quali y managemen is cen alized on he
quali y model.
The Quali y Model ep esen s he co e o he
amewo k and hequali y managemen e ol es
a ound i . We p opose a Quali y Model me amodel
consis ing in a simpli ica ion and adap a ion o ISO
s anda ds. Pa icula ly, ISO/IEC 15939:2007 de ines
a measu emen p ocess applicable o sys em and
so wa e enginee ing and managemen disciplines.
The p ocess is desc ibed h ough a model ha
de ines he ac i i ies o he measu emen p ocess
ha a e equi ed o adequa ely speci y wha
measu emen in o ma ion is equi ed, how he
measu es and analysis esul s a e o be applied, and
how o de e mine i he analysis esul s a e alid.
The measu emen p ocess is lexible, ailo able, and
adap able o he needs o di e en use s. ISO/IEC
15939 (ISO/IEC 15939:2007 2012) so ha he
model ins an ia ion can be mo e lexible and
p ac ical. The main objec i e concludes ha quali y
managemen becomes s a egically ac i e.
The e o e, all he s a egic asse s ha e o be
iden i ied and i is necessa y o ca y ou cap u e,
de ini ion and alida ion o he Quali y Model ha
will be used o quali y managemen . The Quali y
Model con ains: Fea u es and Sub-Fea u es (bo h a e
ca ego ies o an en i y’s p ope ies). A Fea u e is a
highe -le el ca ego y o he domain desc ip ion o
an en i y, while a Sub-Fea u e is a lowe -le el
ca ego y. A P ope y poin s ou he deg ee o which
a Sub-Fea u e is measu ed. In simple e ms, a
P ope y is used o measu ing Sub-Fea u es. Below,
di e en le els o P ope ies and Quali y
Cha ac e is ics a e explained.
 Fea u e (FT-<Le el 1>): I is a gene al concep
o an en i y, a se o p ope ies, bu a highe -le el
concep o an en i y’s cha ac e iza ion ha
desc ibes i b oadly. A Fea u e has a se o Sub-
Fea u es.
 Sub-Fea u e (FT-<Le el 0>): I is a speci ic
concep o an en i y. I is a se o P ope ies, bu
a lowe -le el concep o an en i y’s
cha ac e iza ion. I is used o ca ego ize he
P ope ies o he en i y in wo le els (Fea u e and
Sub-Fea u e).
 P ope y: A P ope y is used o desc ibing and
analyzing he Sub-Fea u es o an en i y.
As explained be o e, Quali y Cha ac e is ics
(hie a chical by Quali y Cha ac e is ics (o QC-
<Le el 1>) and Quali y Sub-Cha ac e is ics (o QC-
<Le el 0>) a e he quali y aspec s oge he wi h
hese P ope ies ha ha e o be assu ed on an en i y.
Subsequen ly, as shown in igu e 1, he au ho
would de ine he ela ions be ween hese P ope ies
and Quali y Cha ac e is ics o iden i y how each
Sub-Fea u e in each Quali y Sub-Cha ac e is ic is
in luenced. These associa ion links would ep esen
dependencies be ween P ope ies and Quali y
Cha ac e is ics. They would show Quali y
Cha ac e is ics ha a e a ec ed by Sub-Fea u es o
a eas o he en i y ha would be signi ican ly
a ec ed i i changed. Associa ion links may be
based on p o en and eal-wo ld expe ience.
 P ope ies a e he desc ip i e en i onmen in
which he quali y managemen is going o be
pe o med.
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P ope y
Sub-Fea u e
Fea u e
Quali y
Cha ac e is ic
Quali y
Sub-Cha ac e is ic
P ope ies
Quali y Cha ac e is ics Quali y Me amodel
1..*
1..*
1..*
1..*
1..*
Figu e 1: Quali y Me amodel.
 Quali y Cha ac e is ics a e hose quali y aspec s
designe s mus ensu e in he se o P ope ies ha
a e o e ed o use s.
On he con a y, Quali y Cha ac e is ics and
Quali y Sub-Cha ac e is ics a e quali y aspec s
in luenced by an en i onmen desc ip ion o
P ope ies. In o he wo ds, Quali y Cha ac e is ic is
a highe -le el quali y aspec . Highe -le el a ibu es
a e called Quali y Cha ac e is ics and lowe -le el
a ibu es a e called Quali y Sub-Cha ac e is ics, in a
hie a chy o Quali y Cha ac e is ics. A MoI (Ma ix
o In luences) ela es P ope ies and Quali y
Cha ac e is ics P ope ies and Quali y
Cha ac e is ics a e o ganized in ows and columns;
P ope ies (hie a chical in Fea u es and Sub-
Fea u es) a e lis ed in ows and Quali y
Cha ac e is ics (hie a chical in Quali y
Cha ac e is ics and Sub-Cha ac e is ics) a e
ep esen ed in columns.
Fo ins ance, i a Web applica ion is going o be
e alua ed om he poin o iew o use s, all
equi emen s ha e o be de ined by he NDT
me hodology. As ega ds p ope ies, all Web
applica ions equi emen s ha e o be desc ibed like
unc ions o hei in e aces ha he Web applica ion
o e o use s. Once he p ope ies a e de ined,
quali y cha ac e is ics mus be de ined ollowing he
de ined s a egies o he speci ic con ex . Then, o
Web applica ions a e y impo an aspec is he
usabili y and unc ionali y o he applica ion. In ac ,
hese wo quali y cha ac e is ics a e based on ISO
25000 bu , in he end, all hese quali y
cha ac e is ics a e abs ac concep ha ha e o be
measu ed by some p ope ies o de ined me ics. So,
as ega ds usabili y quali y cha ac e is ic is
conce ned, o ob ain some alue om use s, we can
do hem some ques ions like:
 Does he use eel ha i is easy and e icien o
ge hings done wi h he Web applica ion?
 Does he use see he Web applica ion as isually
a ac i e?
 Does i eel pleasu able in hand? Does he Web
applica ion gi e me inspi a ion? O wow
expe iences?
 Is i easy o lea n?
As ega ds unc ionali y, we can also do some
ques ions o use s like:
Does he use pe cei e he unc ions in he Web
applica ion as use ul and i o he pu pose?
QuEF can be used om wo poin s o iew:
designe s’, who need o analyse, con ol, e alua e
and imp o e en i ies and consume s, who need o
compa e en i ies (depending on hei con ex ) o
decide he mos sui able one o hem. The main
di e ence wi h o he amewo ks is ha QuEF ocus
on he quali y model and he amewo k also de ines
a li e cycle in which all phases e ol e a ound he
quali y model. I is based on ITIL 3 bu wi h a big
di e ence which is ha is no ocused on se ices
bu on a quali y model. The same way o ITIL 3, i
is composed by i e phases o ensu e he quali y
con inual imp o emen o he quali y model. The
aim is o cen alize all e o s o he quali y
managemen on he quali y model. This means ha i
comp ises se e al phases which include di e en
objec i es and a e ac s:
 Quali y Model S a egy phase: This phase is a
s a egic ac i e ha ocuses on he de ini ion o a
s a egy o he quali y managemen . The pas , he
p esen and u u e iew elemen s o he quali y
model in he domain unde s udy a e undamen al
o achie e e ec i e and e icien quali y
managemen .
 Quali y Model Design phase: This phase is whe e
he quali y model is inally designed in e ms o
all s a egic ac i es in he p e ious phase. This
quali y model is he model used in he nex phase
o ope a ing o he quali y managemen .
 Quali y Model Ope a ion phase: In his phase he
quali y model is used o ca y ou he Quali y
managemen . So, he Analysis and E alua ion
managemen p ocesses a e pe o med wi hin his
phase.
 Quali y Model T ansi ion phase: I he domain o
con ex is changed o he appea ance o new
ends, hen his phase desc ibes he p ocesses
ha ca y ou he changes in he quali y model bu
wi hou a ec ing he Ope a ion phase.
 Quali y Con inual Imp o emen phase: This
phase pe o ms all p ocesses o imp o e quali y
o all p ocesses in he li e cycle and he e y
same quali y model.
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Then, we p opose a p ocess o cap u e, de ine,
alida e and manage he quali y con inual
imp o emen s o Web applica ion equi emen s and
psychological/emo ional expe iences o be expec ed
by use s. This p ocess, as shown in igu e 2, is
based on a hypo he ical quali y model. This
hypo he ical quali y model is buil om he Web
applica ion equi emen s and psychological/
emo ional expe iences o be expec ed by use s ha
ha e been cap u ed and de ined by he NDT
me hodology. Then, his hypo he ical Quali y Model
mus be alida ed using bio eedback. The s eps
include he ollowing ac i i ies:
1. De ini ion o Web applica ion equi emen s
and psychological/emo ional expe iences o be
expec ed by use s ( his s ep is co e ed by he NDT
me hodology)
2. De ine he hypo he ical Quali y Model using
empla es and me hods o QuEF and en o ces he
quali y con inual imp o emen o he Quali y Model.
3. Neu oscience Resea ch o quali y e alua ion.
a. Measu emen o selec ed pa ame e s abou
bio eedback
b. Valida ion o hypo hesis by he e alua ion
o in o ma ion.
Figu e 2: P ocess o cap u e, de ine, alida e and o
manage he quali y con inual imp o emen s o
equi emen s.
5 THE QUALITY MODEL
VALIDATION BY USING
NEUROSCIENCE
TECHNIQUES
This way o e alua e quali y by psychological and
emo ional expe iences le us o exp ess new o he
abs ac e concep s (independen ly ha ISO
ecommend) like di ec ly he pe cep ion alue o he
Web applica ion o use s wi h ques ion like:
 Is he Web applica ion impo an o me? Wha is
i s alue o me?
The e is some cogni i e neu oscience esea ch
me hodology like S eady S a e Topog aphy
(abb e ia ed SST) which is a me hodology o
obse ing and measu ing human b ain ac i i y. This
me hodology has been p incipally used as a
comme cial applica ion in he ield o
neu oma ke ing and consume neu oscience. In his
case, he e is a ela ion be ween he quali y
assu ance o p oduc s and neu oma ke ing bu wi h
some di e ences. The main objec i e o
neu oma ke ing is o sell he p oduc while o he
quali y assu ance o p oduc s is ha he p oduc o
be accep ed by use s.
Figu e 3: Ac i i ies o alida e he hypo he ical quali y
model o Web applica ions and he de elopmen o Web
applica ions.
In addi ion, bio eedback may be used o he p ocess
o gaining g ea e awa eness o many physiological
unc ions p ima ily using ins umen s. Bio eedback
may be used o imp o e heal h, pe o mance, and
he physiological changes which o en occu in
conjunc ion wi h changes o hough s, emo ions, and
beha io . Some kown equipmen and echniques ha
can be used a e:
 Func ional magne ic esonance imaging o
unc ional MRI ( MRI) o measu e changes in
ac i i y in pa s o he b ain. I is an MRI
p ocedu e ha measu es b ain ac i i y by
de ec ing associa ed changes in blood low. This
echnique elies on he ac ha ce eb al blood
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low and neu onal ac i a ion a e coupled. When
an a ea o he b ain is in use, blood low o ha
egion also inc eases.)
 Elec oencephalog aphy (EEG) is he eco ding
o elec ical ac i i y along he scalp. EEG
measu es ol age luc ua ions esul ing om ionic
cu en lows wi hin he neu ons o he b ain.
EEGs can de ec changes o e milliseconds,
which is excellen conside ing an ac ion po en ial
akes app oxima ely 0.5-130 milliseconds o
p opaga e ac oss a single neu on, depending on
he ype o neu on. EEG measu es he b ain's
elec ical ac i i y di ec ly, while MRI eco d
changes in blood low. In ac , MRI a e indi ec
ma ke s o b ain elec ical ac i i y. Anyway,
EEG can be used simul aneously wi h MRI.
 Hea a e, espi a o y a e and gal anic skin
esponse o lea n why consume s make he
decisions hey do, and wha pa o he b ain is
elling hem o do i . Hea a e e e s o he speed
o he hea bea , speci ically he numbe o
hea bea s pe uni o ime. The hea a e is
ypically exp essed as bea s pe minu e (bpm).
The hea a e can a y acco ding o he body's
physical needs, including he need o abso b
oxygen and exc e e ca bon dioxide.
Fo his case, a quali y model is going o be
de ined by p ope ies and quali y cha ac e is ics.
P ope ies a e going o ep esen all equi emen s
ha desc ibe a Web applica ion and quali y
cha ac e is ics a e going o ep esen psychological
and emo ional expe iences o Web applica ions by
use s as shown in igu e 3. Then, he goal o his
quali y managemen using QuEF is o iden i y and
assess, on one hand, how changing elemen s o Web
applica ions impac s on use s beha io . And, On he
o he hand, how changing elemen s o a Web
applica ions de elopmen p ocess impac s on
de elope s beha io . Thus, a quali y model is going
o be de ined as a se o p ope ies o Web
applica ions o a se o p ope ies o he
de elopmen p ocess o Web applica ions ha ha e
o be ela ed o psychological and emo ional
expe iences.
6 CONCLUSIONS AND FUTURE
WORKS
This pape p oposes a p ocess o cap u e, de ine,
alida e and manage he quali y con inual
imp o emen s o use equi emen s and
psychological/emo ional expe iences o be expec ed
by use s. I ocus on he alida ion o use -cen e ed
designs and equi emen s o Web applica ions by
neu oscience echniques and sugges he use o hese
echniques o achie e e icien and e ec i eness
alida ed designs by eal beha io o po en ial use s.
Fo he speci ica ion o equi emen s and
psychological/emo ional expe iences he NDT
me hodology is p oposed. NDT is a Model-D i en
Web de elopmen app oach o he de elopmen o
Web applica ions. In addi ion, a amewo k o
en o ce quali y and he quali y con inual
imp o emen o Web applica ions is p oposed.
QuEF is a amewo k o manage quali y o any
p oduc o p ocess. So, i can be applied o Web
applica ions. I is composed by i e phases o ensu e
he quali y con inual imp o emen o he quali y
model. The aim is o cen alize all e o s o he
quali y managemen on he quali y model. In
addi ion, he amewo k also de ines p o ocols and
me hods o pe o m each phase, so all p o ocols and
me hods a e sys ema ized.
The p oposed p ocess is based on a hypo he ical
quali y model. This hypo he ical quali y model is
buil om he equi emen s ha ha e been cap u ed
and de ined by he NDT me hodology and mus be
alida ed using bio eedback.
As a as Web applica ions de elopmen
p ocesses a e conce ned, we a e cu en ly wo king
in he imp o emen o he NDT me hodology and
he QuEF amewo k. Fu he mo e, a ool suppo is
also being implemen ed in o de o implemen his
solu ion in eal en i onmen s. So, we can ge quali y
managemen in an au oma ic way using QuEF,
au oma ing he quali y managemen o en i ies
(p oduc s, p ocesses, se ices, o ganiza ions, e c.) in
o de o educe cos s, minimize ime and imp o e
quali y o he quali y managemen p ocess.
ACKNOWLEDGEMENTS
This esea ch has been suppo ed by he MeGUS o
he Minis e io de Ciencia e Inno ación, by he
MERIMEE P ojec “P og amme MERIMEE de
collabo a ion en e ecoles doc o ales ançaises e
espagnoles”, by he NDTQ-F amewo k p ojec
(TIC-5789) o he Jun a de Andalucía, Spain and by
he FEDER o Eu opean Union o inancial suppo
ia he p ojec “THOT. P oyec o de inno ación de la
ges ión documen al aplicada a expedien es de
con a ación de se icios y ob as de in aes uc u as
de anspo e” o he “P og ama Ope a i o FEDER
de Andalucía 2007- 2013”.
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