Agile Practices: An Assessment of Perception of Value of Professionals on the Quality Criteria in Performance of Projects

doi:10.4236/jsea.2011.412082

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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)

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.

Agile Practices: An Assessment of Perception of Value of Professionals on the

Quality Criteria in Performance of Projects

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):

Agile Practices: An Assessment of Perception of Value of Professionals on the 704 Quality Criteria in Performance of Projects

1111122 1 1

2211222 22

112 2

pp ppmm

FF lF









 

(1)

In this model, the coefficient ℓij 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.

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

Agile Practices: An Assessment of Perception of Value of Professionals on the

Quality Criteria in Performance of Projects

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

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-

Agile Practices: An Assessment of Perception of Value of Professionals on the

Quality Criteria in Performance of Projects

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.