Journal of Software Engineering and Applications, 2011, 4, 700-709
doi:10.4 23 6/jse a .20 11 .4 12 08 2 Pu blishe d Onli ne December 2011 (http://www.SciRP.org/journal/jsea)
Cop yright © 2011 Sci Res. JSEA
Agile Practices: An Assessment of Perception of
Value of Professionals on the Quality Criteria in
Performance of Projects
Mariana de Azevedo Santos1*, Paulo Henrique de Souza Bermejo1, Marcelo Silva de Oliveira2,
Adriano O l í m pio Ton e l li1
1Computer Science Department, Federal University of Lavras, Lavras, Brasil; 2Mathematical Sciences Department, Federal Univer-
sity of Lavras, Lavras, Brasil.
Email: *mariana@bsi.ufla.br
Received November 1st, 2011; revised November 25th, 2011; accepted December 8th, 2011.
ABSTRACT
Deliver high quality software in accordance with deadlines has become a major challenge for the software industry and
more organizations adopt agile practices as a mean to achieve quality in their products. This paper analyzes, through a
survey, the perception of software professionals, working in different fronts of the development process, the relationship
between the use of agile practices and quality of software products. The result shows agile practices that can contribute
to quality in three aspects: bigger involvement of the staff, agile management of the requirements proposed and code
developed.
Keywords: Agile Methodologies, Agile Practices, Perception of Value, Factor Analysis, Software Engineering
1. Introduction
Several scientific and popular publications show that the
use of agile methods is growing among organizations which
work in g in s oftwa re d evelopmen t [ 1 ].
Consolidated in the 2000s through the creation of the
Agile Manifesto [2], these methodologies incorporate dis-
tinguished principles from tra ditional approaches to soft-
ware development, such as iterative and conceptual sim-
plicity, aiming at the development and delivery of func-
tiona l software quickly, inte nsive collaboration client, high
quality, lower costs and dynamism in the face of constant
changes in the project [3,4].
By emphasizing such principles, the use of agile me-
thodologies are increasingly attracting more interest to or-
ganizations seeking for more dynamic approaches to so-
lutions to common problems and challenges of software
development projects, such as constantly changing user
requirements, schedules control, communication and coo-
peration with the customer, continuous control of requi-
rements, functional testing and delivery of the software
product [4-7].
Driven by the growing acceptance and adoption, stud-
ies have sought to understand, from empirical evidence,
the impacts caused by agile methodologies in software
development project.
Accordingly, topics studied include the simplification
and improvement of team communication with the adop-
tion of the XP methodology [8], easing the scope of the
project with Agile [9], qualitative increase in communi-
cation and commitment, cooperation and adaptability of
professionals involved in development projects [5].
Regarding the contributions of agile methods on qua-
lity of software products, works such as Chow and Cao [10]
and Lee and Xia [11] have highlighted factors that may
contribute to quality assurance.
Amo ng the feat ure s and a ttri bute s stud ied b y Cho w and
Cao [10], the dynamic environment, the choice of an ap-
propriate process management techniques and use of agile
methods as factors that positively influence the creation
of software products with quality.
Lee and Xia [11 ] sugge st tha t the exte nt and ef ficie nc y
of response time impact the performance of the agility of
software development in different ways: the efficiency in
response positively affects the co mpletion on time, on bu-
dget co mpletion and qualit y of so ftwar e feature s while th e
amplitude response only positively affects the quality of
software features.
Resu lts such as th os e obtai n ed [10,11] can be s t ren g thened
by focusing on topics of agile identified as fundamental to
Agile Practices: An Assessment of Perception of Value of Professionals on the 701
Quality Criteria in Performance of Projects
the quality of software products, including knowledge sha-
ring, active participation of stakeholders, self-organizing
teams, and staff training [12].
Although good results have been found in practice, li-
ttle is known about which are the main agile practices ado-
pted to ensure this benefits in quality of software projects
using agile methodologies.
Overall, the available studies focus on analyzing fac-
tors and attributes is related to agile principles and not on
the applicability of practices [4].
To contribute to filling this gap on the applicability of
agile practices for quality assurance, this paper aims to
analyze, from the perceived value of various stakeholders
in the process of software development, the relationship
between the use of agile practices and quality of software
products.
2. Justificative
Deliver high qualit y software in accordance with the sche -
dule and scope has become a major challenge for the soft-
ware industry and many alternatives has been adopted by
develop ment teams in a n attempt to reduce efforts to ful-
fill its goals for the client, the user and the project team
their own [13,14].
Among the most widely adopted alternatives, increase-
ingly these professionals are using agile practices as a
means to achieve quality of the final product in an attempt
to solve problems that reference the development phase
of the software intended [4,15].
This search is justified by the characteristics of the ag-
ile software development, which requires innovation and
highly responsive, aligning the client’s strengths and skill
of the development team to find the right balance be-
tween product quality and agility of the processes [16].
This growth can be corroborated by the results of the
research of Charette [17], where projects using agile me-
thods in comparison with considered traditional method-
ologies, obtained better results for the timeliness, quality
and costs.
In additio n to C harette [17 ], several st udies ha ve inve st-
tigated how the principles, values and practices of agile
methods are perceived and used b y practitioners using as
a parameter the performance criteria and size of projects.
However, from these various studies about agile as [5,
8-12,18] , little is known about which main practices ado -
pted and which effects are produced on the quality of pro-
jects and software products.
Another i mportant po int raised is the limita tion of t hese
studies to evaluate projects using specific methodologies
and more popular, such as XP and Scrum. The magnitude
and diversity of practices and agile methodologies it’s
disregarded in most of the studies.
Therefore, the investigation of the perceived value of
the users those agile practices in their software develop-
ment environment is presented as an appropriate object-
tive since the article proposes to seek understanding of
the impact and positive effect of the adoption of agile
practices in software projects as a way to get quality on
the final software product, filling the gap left by previous
studies.
3. Objective
This paper aims to analyze, from the perceived value of
various stakeholders in the process of software develop-
ment, the relationship between the use of agile practices
and quality of software products. For both the analysis of
results proposes answering the following question:
a) Which, of the main agile practices, are being used to
achieve quality on software products?
Thus, the investigation of the proposed question is to al-
low the id entification o f the agile pract ices most valued to
fulfill the quality criteria for s oftware produ cts devel oped.
4. Agile Methodologies
Agile methodologies are processes that support and im-
plement the philosophy of dynamism and agility in soft-
ware development [19].
They are constituted of a set of software development
and management practices that were consolidated in 2001
by 17 experienced experts in software development proc-
esses, establishing common values and principl es [20,21].
Based on these principles and values, was created the
Agile Alliance and the establishment of the Agile Mani-
festo. The key values proposed in the “Agile Manifesto”
are [2]:
Individuals and in teracti ons over processes and t ools.
Working software over comprehensive documenta-
tion.
Customer collaboration over contrac t negotiat ion.
Responding to change over following a plan.
The idea of the “Agile Manifesto” is to redefine the
priorities of a software project. Although there are proc-
esses and tools, documentation, negotiating contracts, them
are reduced and more objective. In short, this paradigm
allows the minimization of risks in the development and
management of so ftwar e pr oj ects.
Among the initials agile methodologies, previously cre-
ated of the Agile Manifesto, highlights the Extreme Pro-
gramming [22,23] for software development, Scrum [24]
for project management, Adaptive Software Development
[25], Feature Driven Development [26], Dynamic Sys-
tems Development Method [27] and Crystal Methodolo-
gies [28]. Later, Test Driven Development [29] was in-
corporated into the list of available methodologies.
Cop yright © 2011 Sci Res. JSEA
Agile Practices: An Assessment of Perception of Value of Professionals on the
Quality Criteria in Performance of Projects
Cop yright © 2011 Sci Res. JSEA
702
With several examples in the literature of agile meth-
odologies, in general, are based on the set of principles set
out in the Agile Manifesto. So even with a variety of agile
methodologies presented, they have similar values and prac-
tices applied to very similar contexts during the execu-
tion phases of a software project, as shown in Table 1.
5. Perception on Software Quality
The term quality represents the degree to which a set of
inherent characteristics of a product or process meets the
needs of a customer or user [30].
Kemerer and Paulk [31] still define the concept of qua-
lity as an important success factor to be considered in de-
veloping a product.
From the perspective of software, quality can be per-
ceived as a business objective, and for each aspect of the
life cycle of a product, there are various techniques and
tools to support the developers [21]. In this work, analy-
sis of the impact of agile practices on quality is presented
through the concept of perceived value of professionals
of software development.
In the literature, value is defined as an indicator of the
positive contribution of a service, process or product and
service as to compliance the desires and needs [32].
According [32], perceptions are based in opinions or
reasoned experiences from the impact of information re-
ceived and processed by individuals or social groups,
which may change or keep their opinions due to the effect
that the content analyzed represents on the same.
With the increasing complexity of software develop-
ment and market pressures, companies are seeking veri-
fication and validation practices which ensure greater va-
lue for a software product [15,33,34].
Among the main motivations for the development of
studies using parameters of perspective and perception of
value in Software Engineering is the creation of a unified
framework to better target investments in software and
the creation of stakeholder principles of conduct of cur-
rent situations of the “new Software En gineering” as cha n -
ging requirements, emerging requirements, globalized cu l-
ture of software development and quality assurance of sys-
tems [34].
Table 1. Table su mmary of ag ile practi ces an d the simila riti es of appli catio n thro ughout the stag es of a project ag ile sof tw are
development.
Agile methodologies practices
Project
phases XP Scrum ASD FDD DSDM Crystal TDD
Planning Increm ental design
Spike Solut ions Sprint Planning Adaptative cycleDevelop Overall
Model Study of busines s
objective Refine feat ures -
Requirements
Analysis CRC Cards
User Story Produ ct Back log
Sprint Backlog Mission
declaration Features lis t User story Visi on document -
Rules 10
minutes Build 2 - 4 weeks cycle - Developm ent by
features
Regular Builds
Pareto principle
80%/20%
Reversible
changes
Fixed iterations
Holisti c Diversity
Strategy Work rested
Teams Small teams
Pairs
Lead progra m m er
Small teams
Multi-disciplinary Multi-di scip linaryFeat ures t eams Small teams Several teams
working in parallel
Solo
Pairs
Small teams
Codification
Refactoring
Continuous integrati on
Pair pr o g r am m ing
Collective code
ownership
- Technical reviewIndividual
ownership code
Inspections
Implement ation of
the prototypes -
Pairing
Refactoring
Continuous
integration
Estimatives Planning games Sprint planning By mission By Features By
Features By Features -
Meetings Stand up meetings Stand up meetings
Sprint review Analysis focused
in customer Domain
Walkthrough Business review Workshop analysis -
Monitoring Project Velocity Burndown Chart
Kanban Milestones Milestones Milestones Milestones -
Tests Unit tests Screening
bugs - Integrated tests Integrated testsIntegrated tests Automated tests Test first
Releases Frequent Frequent Frequent Frequent Frequent Frequent Frequent
Agile Practices: An Assessment of Perception of Value of Professionals on the 703
Quality Criteria in Performance of Projects
Inserted to the context of “new Software Engineering”,
the agile methodologies seek to avoid unfavorable situa-
tions in the project and focus on delivering value to cus-
tomers by compliance the quality requirements [2].
As a complement to the proposal, Ahmed et al. [12],
claims that the adoption of agile development method-
ologies has a positive impact not only on the productivity
of the team and the velocity at which the product is de-
livered to the customer but also over the quality of the
software product.
Huo et al. [35], contemplates that some agile practices
can be used in adaptations made in process models of qua-
lity of the traditional approach as a potential solution for
quality assurance, especially in early stages of the project.
However, that the propose of quality assurance using
agile methodologies should focus on identifying prac-
tices rather than the comparison between the two approa-
ches, because the initial conditions of development are
different, which highlights an empirical research unreal-
istic [35].
In this context, the present approach constitutes an im-
portant assessment tool to support agile software devel-
opers, whose experiences are considered as key elements
in creating value for its current and future software pro-
ducts and, as well as to deliver this value to a customer
more profitable and sustainable way possible.
6. Methodology
6.1. Research Methods
The study constitutes a quantitative survey conducted by
the survey in a sample of 109 participants working in dif-
ferent fronts of the process of software.
We used two types of samples: expert and propagating
geometric or snowball [36]. The use of those sampling
methods is justified due to: 1) participation of elements
that are experts or have expertise in software develop-
ment and 2) the inclusion of elements considered little
accessible or with compatible characteristics to the do-
main of the research that are difficult to find.
This profile of elements is usually best identified by
individuals who have close relationship, unknown to the
researcher.
The survey contained a total of 15 questions, divided
into three phases, which as shown in Figure 1: demogra-
phics, asses sment of perceptio n of agile p ractices and per-
ceived benefits and difficul ties.
The agile practices were grouped into three questions,
their use in the second stage of a project agile software:
practices for organizing teams and feedback; practices te-
chniques (rules, coding, testing and versioning); and prac-
tices for planning, control and compliance goals.
Figure 1. Example of a figure caption.
The data were collected for four months through the
web tool for creation of surveys called SurveyMonkey,
whose perception of the impact of agile practices on the
quality of software products were evaluated using a Likert
scale of six points, where the practice was evaluated by
the values: very high (6), high (5), satisfactory (4), regu-
lar (3), low (2) and very low (1). To avoid responses
flawed due to lack of knowledge, respondents were asked
to evaluate only the agile practices that have used or use.
6.2. Data Analysis
The user’s perception of value was analyzed using explo-
ratory statistical analysis techniques, which is used when
you want to discover trends, relations and patterns hidden
from the researcher in a collection analyzed data.
In the point of view of Software Engineering, the pros-
pect of value provides a good way to look at the process
of developing a product, creating strategies to achieve a
long-term profitable growth and a sustainable compete-
tive advantage for software companies [34].
Among the exploratory techniques used in this work
are the Descriptive Analysis and Factor Analysis.
Factor analysis is a technique of exploratory data ana-
lysis which consists of the data reduction or simplifica-
tion of its structure, in order to describe, if possible, the
covariance relationship among many variables in terms
of a fe w u nder l ying, b ut unob ser vab le, r ando m qua nti tie s
called factors [37].
The factor analysis is motivated by the argument which
variables can be grouped by correlations. In this research,
we will test if exists correlations between agile practices
and quality criteria, defining which are this practices and
if they could be grouped and represented by factors.
In particular, the factor analysis model is represented
by the Equa tion (1):
Cop yright © 2011 Sci Res. JSEA
Agile Practices: An Assessment of Perception of Value of Professionals on the 704 Quality Criteria in Performance of Projects
p
1111122 1 1
2211222 22
112 2
X
X
X
mm
mm
pp ppmm
FF lF
FF lF
FF lF





 
(1)
In this model, the coefficient ij is called loading of the
ith variable on the jth factor and the F(m × 1) is the matrix
of the factor loadings. In this context, the factor analysis
model assumes that these variables had linear relation
with new random variables Fn, where n = 1, 2, 3,···, n.
The vector ε(p × 1) represents the random errors associated
at the measures [37].
That initial factor matrix indicates the relation between
the variables rarely results in factors that could be inter-
preted [38].
However, the analysis becomes feasibly useful in func-
tion of their ability to produce factors, through the meth-
ods of the rotation matrix, which transforms the factors
matrix into an array of rotated maximized, meaningful,
simpler and easier to interpret [38,39].
For this study we used the method of orthogonal rota-
tion Varimax, which is the most commonly used because
it focus in maximu m simplific ation of the columns o f the
array factor by maximizing the sum of variances of re-
quired charges of the factorial matrix [37,40].
The factors found are defined by the value of its in-
dexes, whose consideration is dependent on sample size.
For this research, the practices that have factor loadings
of 0.55 or higher are co nsidered significant, since the sam-
ple size is 109 respondents [36]. The validation tests were
made using the methods KMO and calculation of latent
root [36,37].
Once the analysis performed with SPSS (Statistical
Package for Social Sciences) version 18, it was possible
to identify practices correlated that represents the greatest
values in the perception of respondents regarding the
quality of software products being resized as factors of
impact.
Only the factors found using as variables the practices
with n > 35, were considered for the elaboration of a fac-
torial model for quality in agile development. This crite-
ria was considered for represent a most representative
sample of the study.
7. Results
7.1. Sample Characterization
The survey obtained a total of 109 respondents from coun-
tries in the world, as represented in Figure 1, with 77 re-
spondents from Brazil, 19 from United States and one re-
spondent for each of the respective countries: Germany,
Arge ntina, Australi a, Belgium, Colo mbia, De nmark France,
India, Italy, Poland, Switzerland, Serbia and Venezuela.
Regarding the stage of adoption of agile methodolo-
gies, represented in Figure 2, 34% responded that the use
of agile methods in your company is well defined, but no
formal performance measurement practices in relation to
quality criteria. About 24% of respondents said that the
process of agile methodologies is Partially implemented
in your company. The category Defined as formal and con-
tinuous improvement measurements obtained 23% of re-
sponses. The category Initial/ad hoc obtained 19% of res-
ponses.
7.2. Validity and Reliability
The first step of the validation phase consists in treat the
data collected, separating the variables which had more
evaluations of the variables which had few evaluations.
This treatment has fundamental to get a more representa-
tive sample to the analysis, once the evaluations of the all
practices was facultative. Table 2 shows all the practices
and the number of evaluations received by each item. For
this analysis it’s only considered practices with n > 35 in
order to build a more representative sample for the study.
The val id a ti on o f d a ta ge ne ra t e d b y the a na l ysis c a n be
tested by the KMO method (Kaiser-Meyer-Olkin). The
KMO value founded was 0.816, that according to Maroco
(2010), corresponds to a test whose analysis generated
has good quality, as the demonstration in Table 3.
The information described in Table 2 indicate that the
KMO index = 0.680, approximately 0.7, validates the ana-
lysis with a good recommendation. The Bartlett test shows
a significance value p < 0.0001. Therefore we conclude
that the variables are significantly correlated.
7.3. Factor Analys i s
Regarding the number of factors observed, the factor
analysis, represented in Table 4, sho ws a struct ure o f six
Figure 2. Example of a figure caption.
Cop yright © 2011 Sci Res. JSEA
Agile Practices: An Assessment of Perception of Value of Professionals on the 705
Quality Criteria in Performance of Projects
Table 2. Agile practices and the number of evaluations by
the quality cri teria.
Agile Pr actices Number of An swers about Q uality
Small teams 86
Multifunctional teams 59
Solo programmer 44
Product Owner 50
Scrum Master 50
Lead programmer 41
Teams by features 33
Several t eams working in pa rallel 26
Small teams in large teams 30
Daily meeting 58
Stand-up meeting 62
Itera tion planning meeting 60
Retrospective 56
Pro duct backl og 57
Client on-site 58
User cases 47
Scenarios 31
Vision document 40
Evocative document 22
User story 44
Spike solutions 21
Domain model 26
Study of b usin ess objec tive 28
UML Diagrams 41
Refactoring 41
Pair pr o gramm ing 37
Collective ownership code 32
Screening bu gs 40
Tests after development 24
Individual ownership code 24
Funct ional te s ts 44
Development guide by test 35
Unit tests 40
Auto m ated tes ts 33
Continuous integration 39
Fixed iterations 49
Burndown charts 34
Kanban 46
Planning games 31
Velocity 26
Estim at ions by features 34
Progress reports 2 2
Table 3. The KMO coefficient of factor analysis and Bart-
lett’s sphericity test for representative sampling of the qual-
ity criteria.
Validity tests used Results
Kaiser-Meyer-Olkin Measure of sampling adequacy 0.680
Bartlet t’s test of sphericit y (Q2 approximation) –1.457
df 300
Sig. 0.000
a. df = degrees of Freedo m; sig = signif i can ce.
Table 4. Percentage of explained variance for representati ve
analysis for the qualit y criteria.
Initial Eigenvalues
Factors Total Variance% Cumulative%
1 5.542 39.116 39.116
2 2.234 6.232 45.347
3 2.003 5.314 50.662
4 1.558 4.678 55.340
5 1.329 4.606 59.946
6 1.097 4.389 64.335
factors explaining 64.3%, approximately 64% of the vari-
ance of the questionnaire, considering eigenvalues greater
than or equals to 1, as recommended the latent root crite-
ria [36,40].
With the discovery of six latent factors, the analysis
solution is shown in Table 5 which provides the agile prac-
tices of higher perceived value of quality professionals in
the facto rs ch os en .
From the results found in factor analysis, it was possi-
ble to extract six factors, as shown in Figure 3.
Factor 1—Backlog with continuous integration:
this first factor presents high factorial weights in prac-
tices related to the phase of planning of the features of the
project, where the team sets during the planning meeting
of the iterative cycle, the implementations of higher pri-
orit y and which deliver customer value. The practices had
higher factorial weights justify a positive perception of
value from the respondents regarding the creation of a
prioritized list of features in the iteration planning meet-
ing, that must be worked and integrated in small releases
and continuously evaluated qualitatively at the meeting
of the Iteration Retrospective, in order to create a impro-
ve plan for the next features to be worked.
Factor 2—Agile requirements analysis: this se-
cond factor has factorial weights high significant in the
perception of practices related to the execution and ana-
lysis of test of features specified in the users stories. An
User story is an agile practice where the requirements are
specified from the customer’s point of view, in a simple
Cop yright © 2011 Sci Res. JSEA
Agile Practices: An Assessment of Perception of Value of Professionals on the
Quality Criteria in Performance of Projects
Cop yright © 2011 Sci Res. JSEA
706
Table 5. Solution of t he factorial anal ysis of representative sa mple of agi le practi ces on the quality cri teria.
Agile practices F1 F2 F3 F4 F5 F6
Small teams 0.168 0.292 0.099 –0.053 0.146 0.278
Multifunctional teams 0.015 0.378 –0.111 0.053 0.195 0.557
Solo programmer –0.058 –0.156 0.026 0.040 –0.076 0.061
Product owner 0.291 0.224 0.157 0.176 0.028 0.626
Scrum master 0.226 0.104 0.494 0.259 0.264 0.182
Lead programmer 0.096 0.163 0.203 0.253 0.140 –0.003
Daily meeting 0.207 0.174 0.004 –0.001 –0.103 –0.068
Stand-up meeting 0.286 –0.294 0.139 –0.120 –0.037 0.374
Iteration Planning meeting 0.664 0.153 –0.036 0.051 0.081 –0.028
Retrospective 0.784 0.108 –0.102 0.114 0.272 0.147
Product backlog 0.587 0.239 0.244 –0.040 0.032 0.071
Client on-site 0.291 0.692 –0.049 0.245 –0.044 0.070
Use cases –0.076 –0.062 0.636 0.024 0.395 0.235
Vision document 0.279 0.181 0.141 –0.098 0.705 –0.028
User story 0.320 0.623 0.029 0.065 0.404 0.317
UML diagrams 0.032 0.005 0.847 –0.047 –0.021 –0.047
Refactoring 0.196 0.249 –0.042 0.008 –0.115 0.291
Pair pr o gramm ing –0.027 0.11 9 –0.037 0.468 0.118 0.213
Screening bugs 0.285 0.051 0.119 0.783 –0.106 0.026
Functional tests 0.063 0.576 0.556 0.165 –0.116 –0.040
Development guide by test 0.051 0.287 –0.032 0.725 0.035 0.170
Unit Tests 0.168 –0.031 –0.061 0.452 –0.185 0.587
Continuous integration 0.663 0.068 0.010 0.291 –0.184 0.308
Iterations fixed 0.516 0.098 0.191 0.195 0.131 0.321
Kanban 0.039 0.466 0.002 0.125 –0.012 0.155
Potentially Shippable 0.011 0.031 0.157 0.022 0.105 0.149
Figure 3. Agile grouped into factors that represent the user’s
percepti on of v a lue and quality.
language and description. In this case, the data in-
dicate which this practice plays an important and active
role in the definitions of the projects and that the features
cre- ated from the stories users are properly tested
thro ugh the use of functional tests.
Factor 3—Modeling the testing process: this third
factor has factorial weights high significant in practices
related to the modeling of testing phase. The practices
had higher weight factor justifying the positive perceived
value of the respondents in the generation of use cases
and UML diagrams to build test cases adapted to the ag-
ile process in their companies.
Factor 4—Preventing bugs with test cases: this
fourth factor has factorial weights high significant in prac-
tices related to the use of test cases for the correction of
errors arising from the acceptance tests. The practices
that obtained higher factorial weights justifying the posi-
tive perception of value of respondents to the develop-
ment of test cases to implement the features ill -defined in
the planning phase and not properly functional identified
in screening of errors of acceptance tests by the user.
Factor 5—Vision document: the fifth factor pre-
sents factorial weights high significant related to the use
of a vision document as an artifact which reports system
technical’s perspectives, process preceding the analysis
of the domain model. In this case, the Vision Document,
despite being built using si mple language, yet has a more
technical aspect of a user story.
Factor 6—M ultifunctional d evelopment t eams gui-
ded by tests: this sixth factor presents factorial weights
high significant in practices related to the formation of a
Agile Practices: An Assessment of Perception of Value of Professionals on the 707
Quality Criteria in Performance of Projects
cross-functional team which implements unit tests of the
more valuable features defined in accordance with the re-
presentant of the customers, the Product Owner. A team
with different abilities to execute tests could bring posi-
tive results because they will search for fail ures in the sys-
tem from different aspects. The practices had higher fac-
torial weights justifying the positive perception of value
of the respondents to practice cross-functional teams in-
cluding the customer in a more representative way.
8. Discussion
From this conceptualization of perception of value, for
the criteria quality of software products, we can construct
a possible scenario of use of agile practices: the teams
formed are cross-functional teams jointly with a customer
representative defines a business model structured in dia-
grams and a document client’s vision in relation to bu-
siness planning meeting in the cycle.
Once carried out the details of planning and architect-
ture, the increment is developed through the test cases,
followed by the unit tests and functional tests. After cor-
recting the errors found in the screening of errors, the
codes are integrated continuously.
This scenario describes that, from the perspective of
using agile practices, the quality of the software product
can be worked in three aspects: (a) bigger involvement of
the staff, (b) agile management of the requirements pro-
posed and (c) code developed.
In describing the use of the practices on the factors, we
find tha t i n gene ral , the facto r s sho w a b e havio r to war d a
use of practices in planning phase, which include the use
of practices which value the custo mer needs as documents
in a simple language, and in architecture and develop-
ment phase, which include modeling and development
guided by tests. These practices have a positive view by
the practitioner s and users of agile methodologies, the agi-
lists and this results aims to approach a better approxi-
mation of current scenario of use of agile practices.
In a way, it can be said that the employment of these
factors in the development cycle of software projects,
collectively or individually, can contribute to the impro-
vement of quality in software products to be developed
using agile methodologies.
9. Conclusions
Agility b ecomes incre asingly i mportant in the current sce -
nario of software development. And in face of a competi-
tive market, it becomes important to search for agile and
adaptive solutions can represent a path to deliver soft-
ware quickly, with quality, on time, with reduced scope
of work and affordable costs.
The objective of this study was to analyze the relation-
ship between the use of agile practices and the quality of
software products. This was achieved once as the results
showed the perception of value to practitio ners with agile
principles and practices used in the current world market.
By combining practices evaluated by the user as posi-
tive for succes s in qualit y criteria, t he study showed tha t the
focus in choosing the best agile practices and not a speci-
fic methodology may be a step of maturity for organiza-
tions to adopt the agile culture with less risk and barriers.
For researchers, this study contributes to achieving a
mapping of agile practices by referencing the plurality of
methods on the market and opening up greater possibili-
ties in the research of perceived value to the user with ag-
ile practi ces. T he result s hows that a gile prac tic es, a nd com-
bined into factors used in the various phases of the project,
can contribute positively in achieving quality in three as-
pects: bigger involvement of the staff, agile management
of the requirements propos ed and code developed.
For practitioners of agile methodologies, this study su-
ggests combinations of widely used agile practices in the
software market and, if destined for suitability and com-
pliance of quality standards in software projects, consi-
dering their needs and strategies, suggests a performance
positive for those who adopt .
Regarding the statistical analysis, these were used tak-
ing care to ensure representativeness of the samples as to
its size, and using appropriate methods and statistical as-
sumptions required and the data type and purpose of the
research.
In summary, this study contributes to improve the un-
derstanding on the use of agile practices in the context of
software development. Research in this area are highly
relevant to a better understand and direct the organiza-
tions to enhance investme nts in resources, effo rts and agile
practices to achieve excellence in processes and software
products. Thus, the authors suggest the following future
work:
An examination of quantitative character, and why
not qualitative, in which to should analyze the perceived
value of use of developers on agile practices applied in a
specific context, just as requirements elicitation practices,
practices focused in testing, refactoring or improving of
code.
Deve lop stat istic al a nalys is usin g ot her t ech nique s of
analysis such as confirmatory methods of analysis, using
techniques such as PLS (Partial Least Square).
10. Limitations
This study aimed to analyze the relationship between agile
practices and software quality. To meet the objective of the
study, data analysis took care to use descriptive methods
Cop yright © 2011 Sci Res. JSEA
Agile Practices: An Assessment of Perception of Value of Professionals on the 708 Quality Criteria in Performance of Projects
robust, and to make inferences, conduct them on repre-
sentative samples. However, the sample size, the struc-
tu re of the questionnaire, and the delineation of self-choice
did not allow using other statistical methods that could
answer more questions than those specified.
11. Acknowledgements
We would like to thank The National Council for Scien-
tific and Technological Development (Conselho Nacional
de Desenvolvimento Científico e Tecnológico—CNPq),
from Brazil, which provided support for the work in this
paper.
REFERENCES
[1] O. Salo and P. Abrahamsson, “Agile Methods in Euro-
pean Embedded Software Development Organizations: A
Survey Study of Extreme Programming and Scrum,” IET
Software, Vol. 2, No. 1, 2008, pp. 58-64.
doi:10.1049/iet-sen:20 070038
[2] Beck, et al., “Agile Manifesto,” 2001.
http://www.agilemanifesto.org/
[3] L. Cao and B. Ramesh, “Agile Software Development:
Ad Hoc Practices or Sound Principles?” IT Professional,
Vol. 9, No. 2, 2007, pp. 41-47.
do i:10.1109/MITP.2007.27
[4] T. Dybå and T. Dingsøyr, “Empirical Studies of Agile
Software Development: A Systematic Review,” Informa-
tics, Software Technology, Vol. 50, No. 9-10, 2008, pp.
833-859.
[5] C. Mann and F. Maurer, “A Case Study on the Impact of
Scrum on Overtime and Customer Satisfaction,” Agile De-
velopment Conference, IEEE Computer Society, Washing-
ton DC, 2005, pp. 70-79
[6] S. Nerur, R. Mahapatra and G. Mangalara, “Ch allen ges of
Migrating to Agile Methodologies,” Communication of
the ACM, Vol. 48, No. 5, 2005, pp. 72-78.
doi:10.1145/1060710.1060712
[7] P. Abrahamsson, K. Conboy and X. Wang, “‘Lots Done,
More to Do’: The Current State of Agile Systems Devel-
opment Resear ch,” European Journal of Information Sys-
tems, Vol. 18, No. 4, 2009, pp. 281-284.
doi:10.1057/ejis.2009.27
[8] H. Svensson and M. Höst, “Views from an Organization
on How Agile Development Affects Its Collaboration with
a Software De velopmen t Team,” Lecture Notes in Compu-
ter Science, Vol. 354 7, 2 005, pp. 4 8-501.
doi:10.1007/11497455_38
[9] A. Sillitti, M. Ceschi, B. Russo and G. Succi, “Managing
Uncertainty in Requirements: A Survey in Documenta-
tion-Driven and Agile Companies,” Proceedings of the
11th International Software Metrics Symposium, Como, 1
September 2005, p. 17. doi:10.1109/METRICS.2005.29
[10] T. Chow and D.-B. Cao, “A Survey Study of Critical
Success Fact ors in Agile Software Projects,” The Journal
of Systems and Software, Vol. 81, No. 6, 2008, pp. 961-
971. doi:10.1016/j.jss.2007.08.020
[11] G. Lee and W. Xi a, “To ward Agile an Integrated Analysis
of Quantitative and Qualitative Field Data on Software
Development Agility,” MIS Quarterly, Vol. 34, No. 1, 2010,
pp. 87-114.
[12] A. Ahmed, S. Ahmad, Dr. N. Ehsan, E. Mirza and S. Z.
Sarwar, “Agile Software Development: Impact on Pro-
ductivity and Quality,” Proceedings of the 2010 IEEE
ICMIT, Singapore, 2-5 June 2010, pp. 287-291.
[13] D. Rombach, “The Dilemma of Software Development,”
Quality Connection, 2002.
[14] A. Sampaio, A. Vasconcelos, R. Pedro and F. Sampaio,
“Assessing Agile Methods: An Empirical Study,” Journal
of the Brazilian Computer Society, Vol. 10, No. 2, 2004,
pp. 22-4 1. doi:10.1007/BF03192357
[15] P. Abrahamsson, O. Salo, J. Ronkainen and J. Warsta,
“Agile Software Development Methods Review and Ana-
lysis,” VIT Publications, Finlândia, 2002.
[16] A. Cockburn, “Agile Software Development: The Coop-
erative Game,” 2nd Edition, Addison-Wesley Professional,
Boston, 20 06.
[17] R. Charette, “Fair Fight? Agile Versus Heavy Methodo-
logies,” Agile Methodologies, the Great Debate, Cutter
Consortium, Arlington, 2001.
[18] L. Cao, K. Mohan, P. Xu and B. Ramesh, “A Framework
for Adapting Agile Development Methodologies,” Euro-
pean Journal of Information Systems, Vol. 18, 2009, pp.
332-343. doi:10.1057/ejis.2009.26
[19] J. Shore and S. Warden, “The Art of Agile Development,”
O’Reilly Me dia , Se bas topol, 2007.
[20] P. Ågerfalk and B. Fitzgerald, “Flexible and Distributed
Software Processes: Old Petunias in New Bowls?” Com-
munications of the ACM, Vol. 49, No. 10, 2006, pp. 27-
34.
[21] A. Koscianski an d M. S. Soares, “Qual idade d e Software:
Aprenda as Metodologias e Técnicas Mais Modernas Para
o Desenvolvimento de Software,” 2nd Edition, Novatec
Editora , São Pa ulo, 2007.
[22] K. Beck, “Extreme Programming Explained,” Addison-
Wesley Professional, Boston, 1999.
[23] K. Beck and M. Fowler, “Planning Extreme Program-
ming,” Addison-Wesley Professional, Boston, 2000.
[24] K. Schwaber and M. Beedle, “Agile Software Develop-
ment with Scrum,” Prentice Hall, São Paulo, 2002.
[25] J. Highsmith, “Agile Software Development Ecosystems,”
Addis on-We s ley Pea rson Educ a tion, Bos ton, 2002.
[26] S. R. Palmer and J. M. Felsing, “A Practical Guide to
Feature-Dri ven Development (the Coad Seri es),” Prentice
Hall PTR, São Paulo, 2002.
[27] J. Staplet on, “DSDM Dyna mic S ystems Dev elop ment Me -
thod,” A ddis on-Wesley, H a r low , 1997.
[28] A. Cockburn, “Agile Software Development,” Addison-
Wesley, Reading, 2002.
[29] K. Beck, “Test Driven Development: By Example,” Ad-
Cop yright © 2011 Sci Res. JSEA
Agile Practices: An Assessment of Perception of Value of Professionals on the
Quality Criteria in Performance of Projects
Cop yright © 2011 Sci Res. JSEA
709
dison-Wesley Professional, Boston, 2002.
[30] Pmbok® Guide, “Project Management Body of Knowledge
(PMBOK® Guide),” 4th Edition, Newtow n Square, 2008.
[31] C. F. Kemerer and M. C. Paulk, “The Impact of Design
and Code Reviews on Software Quality: An Empirical
Study Based on PSP Data,” IEEE Transactions on Soft-
ware Engineering, Vol. 35, No. 4, 2009, pp. 534-550.
doi:10.1109/TSE.2009.27.
[32] P. Kötler, “Administração de Marketing,” 10th Edition,
Prentice Hall, São Paulo, 2000, p. 764.
[33] K. Schwaber, “Agile Project Management with Scrum,”
Microsoft Press, Redmond, 2004 .
[34] S. Biffl, A. Aurum, B. Boehm, H. Erdogmus and P. Grün-
bacher, “Value-Based Software Engineering,” Springer-
Verlag, Berlin, 2006, p. 388. doi:10.1007/3-540-29263-2
[35] M. Huo, J. Verner, L. Zhu and M. Babar, “Software Qu al -
ity and Agile Methods,” Proceedings of the 28th Annual
International Computer Software and Applications Con-
ference, IEEE Computer Society, Hong Kong, 2004, pp.
520.
[36] J. F. Hair, B. Black, B. Babin, R. E. Anderson and R. L.
Tatham, “Análise Multivariada de Dados,” 6th Edition,
Bookman, Porto Alegre, 2009, p. 688.
[37] R. A. Johnson and D. W. Wichern, “Applied Multivariate
Statistical Analysis,” 6th Edition, Prentice Hall, São Paulo,
2007, p. 800.
[38] S. A. Mingoti, “Análise de Dados Através de Métodos de
Estatística Multivariada: Uma Abordagem Aplicada,” Edi-
tora UFMG , Be lo H oriz onte , 2005.
[39] N. K. Malhotra, “Pesquisa de Marketing: Uma Orientação
Aplica da, ” Editora B ookm an, Porto Alegre, 2001.
[40] J. Maroco, “Análise Estatística com a Utilização do SPSS,”
3rd Edition, Silabo, Lisboa, 2007, p. 822.