Influence of Human Personality in Software Engineering
A Systematic Literature Review
Anderson S. Barroso
1,2
, Jamille S. Madureira da Silva
2,3
, Michel S. Soares
2
and Rogerio P. C. do Nascimento
2
1
Computing Department, Tiradentes University, Aracaju, Brazil
2
Computing Department, Federal University of Sergipe, São Cristóvão, Brazil
3
Computing Department, Federal Institute of Sergipe, Aracaju, Brazil
Keywords:
Personality Traits, Human Factors, Software Engineering, MBTI, Big Five, FFM.
Abstract:
Personality of software engineering professionals has been a continuous element of interest in academic re-
search. Researchers have applied different models of personality analysis in various software engineering
areas to identify improvement points, to promote job satisfaction and to better organize teams. This paper
aims to conduct a study, by means of a systematic literature review (SLR), to evaluate personality models ap-
plied in software engineering and to understand how human personality influences professional’s work. Three
main models, most frequently used, were identified (MBTI, BIG 5 and FFM) to evaluate software engineering
professionals. There is evidence of the influence of personality on the activities performed. However, some
results have suggested that the study of personality is not an easy task to be performed, because there are
contradictions in findings that challenges the validity of studies.
1 INTRODUCTION
Modern society has increasingly demanded quality
and productivity in all branches of industry and prod-
uct development. Software Engineering is no excep-
tion. It has been recognized that excellent individuals
in a software team makes a huge influence on the final
products quality, and that one developer can be orders
of magnitude more productive than other (Brooks,
1987) (Sudhakar et al., 2012) (Meyer et al., 2014).
Therefore, it is important to know how to create ef-
fective teams that will more effectively and efficiently
produce high quality software products (Richardson
et al., 2012) (Yilmaz et al., 2016).
According to Pressman and Maxim (Pressman and
Maxim, 2014), software is developed and used by
people, and supports interaction between people, thus
characteristics such as human behavior and coopera-
tion are fundamental to their development. The con-
cern with human aspects becomes of fundamental im-
portance for success of a software project.
Recently, Spinellis and Androutsellis prepared
an analysis of software development activities in
different companies (Spinellis and Androutsellis-
Theotokis, 2014). They concluded that the success
of a team depends on the targets set for its members,
the required controls, pre-defined standards and busi-
ness rules that directly influence the work of software
engineering teams.
Considering these factors, one needs to identify
technical and managerial issues of each individual in
order to arrange the best teams. One factor that stands
out is to evaluate the relationship between human per-
sonality and the activity to be performed by each pro-
fessional. According to Capretz (Capretz, 2003), hu-
man personality represents how people’s behavior in-
fluences decision-making and the ability to assimi-
late information, generating an important debate in
academia and industry.
In order to understand if human personality influ-
ences activities of software engineering profession-
als, this paper proposes a Systematic Literature Re-
view (SLR) (Kitchenham, 2004) with the objectives
of identifying, summarizing, and analyzing all mod-
els that have been proposed or have been used to rep-
resent influence of human personality in Software En-
gineering.
Results show that this topic has been researched
over the past 14 years, including several recent publi-
cations, which indicates the importance of the theme
of human personality in Software Engineering. An
example is work presented in (Yilmaz and O’Connor,
Barroso, A., Silva, J., Soares, M. and Nascimento, R.
Influence of Human Personality in Software Engineering - A Systematic Literature Review.
DOI: 10.5220/0006292000530062
In Proceedings of the 19th International Conference on Enterprise Information Systems (ICEIS 2017) - Volume 3, pages 53-62
ISBN: 978-989-758-249-3
Copyright © 2017 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
53
2012), carried out in industry and academia, with 63
developers, which showed through preliminary stud-
ies that there are more extroverts than introverts pro-
fessionals in software teams. Another example is the
work presented in (Ferreira, Vito and Natasha, N,
2014) which concluded that software testers have sig-
nificantly higher conscientiousness factor than other
software development professionals. This paper is or-
ganized as follows: Section 2 is about the method
followed in the SLR, Section 3 discussed the results
achieved and in Section 4 we conclude the study and
indicate perspectives for future work.
2 PLAN AND EXECUTION OF
THE SYSTEMATIC
LITERATURE REVIEW
A SLR is conducted to catalog studies on professional
personality in software engineering in order to iden-
tify relevant primary studies related to this issue. The
review was carried out between June 18, 2016 and
July 20, 2016. Two phases of the SLR, (A) Plan-
ning and (B) Conduction are presented in this section.
First, two research questions were proposed as fol-
lows:
RQ1: What psychological models are used to
identify traits of personality of software engineer-
ing professionals?
RQ2: Activities performed by software engineer-
ing professionals are influenced by their personal-
ity?
These research questions are answered in Section
3.
2.1 Search Strategy
This research process includes a search in sources ac-
cessed on the web, thus manual query was discarded.
Most common found terms were used in publications
on the topic “Human Personality Influence in Soft-
ware Engineering”.
Initially, we conducted the search considering a
period of five years, finding 110 works. Whereas a
SLR must obtain potentially relevant primary stud-
ies (Kitchenham, 2004), we consider 110 instances
a low number, then we decided to extend the period
for 14 years. Thus, the search was conducted be-
tween 2003 and 2016. This choice is because even
though some models have been published since 1980,
we have identified that relevant work about human
personality in Software Engineering began to occur
in 2003.
We chose to carry out the search in three scien-
tific repositories: IEEE, both “Conference Publica-
tion” and “Journals & Magazines” sections; ACM,
in sections “Proceeding”, “Newsletter”, “Magazine”
and “Journal”, and Elsevier (Subject area: Computer
Science, Human-Computer / Publications, type: jour-
nals). We also use Google Scholar as a search support
tool.
In order to establish the search strategy, we ini-
tially identified the main keywords “Personality” and
“Software Engineering”. We have also identified syn-
onyms for these keywords. Thus, the final search
string was:
(Personality OR Motivation OR Behavior OR
Humans Aspects OR Satisfaction) AND (Software
Engineering OR Software Development OR
Programming OR Software Test OR Developer OR
Tester OR ICT Manager OR Project)
2.2 SLR Conduction
Three steps were considered in this SLR: (1) Selec-
tion process and evaluation quality of primary study,
(2) Inclusion and exclusion criteria, and (3) Informa-
tion extraction strategy.
After applying the search string, 391 papers were
found, distributed as follows: ACM (220), IEEE
(141), and Elsevier (30). Each item found in the
search process was analyzed by two researchers and
reviewed by two others. Two researchers were re-
sponsible for searching and performing a first scan
and the other two to perform a second check and ini-
tiate inclusion and exclusion process. Within this ap-
proach, the most important roles of a SLR, as quoted
by Kitchenham (Kitchenham, 2004), were consid-
ered. Figure 1 illustrates the number of publications
distributed by year.
2.2.1 Inclusion and Exclusion Criteria
Selection criteria are used to evaluate each study re-
covered from the search sources. Thus, the inclusion
criteria (I) used to include relevant studies in our sys-
tematic review are:
I1 - the primary study proposes or uses models to
identify human personality in Software Engineer-
ing;
I2 - the primary study proposes that the human
personality influences activities of software engi-
neering professionals.
Alternatively, the exclusion criteria (E) used to ex-
clude studies that do not contribute to answering the
research questions are:
ICEIS 2017 - 19th International Conference on Enterprise Information Systems
54
Figure 1: Number of publications by year.
E1 - the primary study does not address human
personality in Software Engineering;
E2 - the primary study does not propose or does
not use models for identifying human personality;
E3 - the primary study does not present an abstract
or its full text is not available;
E4 - the primary study is written in a different lan-
guage than English;
E5 - the primary study consists of a compilation
of works, for instance, from a conference or work-
shop.
After the adoption of the inclusion criteria, 122
works were selected as follows: ACM (61), IEEE
(48) and Elsevier (13). The next step was to read
the abstracts of 122 papers selected in the previous
step. The researchers, in consensus, selected 53 pa-
pers as follows: ACM (29), IEEE (21), and Else-
vier (3). Thereafter, we applied the exclusion criteria,
which resulted in 21 papers, distributed as follows:
ACM (9), IEEE (9), and Elsevier (3). Table 1 illus-
trates the steps for final paper selection.
Figure 3 shows the number of publications by
country. Note that the U.S. has the highest number
of publications in searched period, followed by New
Zealand with 3 and Pakistan with 2.
2.2.2 Information Extraction Strategy
For each selected study, the process of assessing
the quality of primary studies was executed, and
the following data were extracted: date of execu-
tion of study; description treatment of observed risks;
description of performed study; experimental study
project; threats to validity: internal, external, con-
Table 1: Selection Steps.
Steps Repositories T
AC IE EL
After search
string
(2003-2016)
220 141 30 391
After inclu-
sion criteria
61 48 13 122
After read-
ing the
abstracts
29 21 3 53
After exclu-
sion criteria
9 9 3 21
AC=ACM; IE=IEEE; EL=Elsevier; T=Total
Figure 2: Number of publications by country.
struction, conclusion; results of the study; lessons
learned; future perspectives; additional comments.
After analysis, the authors of this paper came to
consensus on what would be selected and defined the
final list of twenty one papers that are presented in
Table 2.
Influence of Human Personality in Software Engineering - A Systematic Literature Review
55
Table 2: Included Primary Studies.
ID Author Year Venue
01 (Capretz, 2003) 2003 International Journal of Human-Computer Studies
02 (Gorla and Lam, 2004) 2004 Communications of the ACM
03 (Darcy and Ma, 2005) 2005 Annual Hawaii International Conference on System Sci-
ences
04 (Peslak, 2006) 2006 ACM SIGMIS CPR Conference on Computer Personnel
Research:
05 (Chao and Atli, 2006) 2006 Agile Conference
06 (Aronson et al., 2006) 2006 Journal of Engineering and Technology Management
07 (Rutherfoord, 2006) 2006 Conference on Information Technology Education
08 (Mourmant and Gallivan, 2007) 2007 ACM SIGMIS CPR Conference on Computer Personnel
Research
09 (Gomez and Acuna, 2007) 2007 International Conference on Software Engineering &
Knowledge Engineering
10 (Feldt et al., 2008) 2008 International Workshop on Cooperative and Human As-
pects of Software Engineering
11 (Salleh et al., 2009) 2009 International Symposium on Empirical Software Engineer-
ing and Measurement
12 (Shoaib et al., 2009) 2009 International Multitopic Conference
13 (Salleh et al., 2010) 2010 ACM/IEEE International Conference on Software Engi-
neering
14 (Hannay et al., 2010) 2010 IEEE Transactions on Software Engineering
15 (Salleh et al., 2011) 2011 IEEE-CS Conference on Software Engineering Education
and Training
16 (Raza, A and Capretz, L F, 2012) 2012 Journal of Software Engineering
17 (Yilmaz and O’Connor, 2012) 2013 EUROMICRO Conference on Software Engineering and
Advanced Applications
18 (Ferreira, Vito and Natasha, N,
2014)
2014 International Conference on Computer Science & Educa-
tion
19 (Kanij et al., 2015) 2015 International Workshop on Cooperative and Human As-
pects of Software Engineering
20 (Gulati et al., 2016) 2016 ACM SIGSOFT Software Engineering
21 (Smith et al., 2016) 2016 Int. Workshop on Coop. and Human Aspects of Soft. Eng.
(CHASE)
3 ANALYSIS OF RESULTS
Before discussing the results, it is of utmost im-
portance to understand that personality encompasses
non-intellectual, psychological characteristics that are
informative about an individual, and that helps to
describe the differences between people. It is also
thought to be organized, relatively enduring, an influ-
ence on the person’s interactions with others and in-
fluences their adaptation to their social environment.
Criteria by which people differ from each other are
called psychological traits. Traits are representative
factors to predict one’s behaviour patterns, feeling,
thinking and related activities (Kanij et al., 2015).
There are several conclusions that can be drawn
from these findings that seem worthwhile for further
discussion.
This SLR identified MBTI as the most popular
model to analyze software developer personalities.
However, studies differ on the use of experimen-
tal projects (Yilmaz and O’Connor, 2012). In addi-
tion, research on the software developer’s personal-
ity should distinguish more carefully between models
Big 5 and FFM, as they differ in certain characteris-
tics (McCrae and John, 1998) (Zillig et al., 2002).
However, there are limitations that have to be
taken into consideration. First, one should consider
that this revision may have lost some relevant work,
moreover, the quality of the studies used in this analy-
sis were not homogeneous. Another factor that should
be taken into consideration is that issues such as
methodologies used in the studies, sample size and
use of statistical methods were not taken into account
in the analysis. In case the work had a psycholog-
ical model applied to Software Engineering, it was
enough for this research. This behavior may limit the
ICEIS 2017 - 19th International Conference on Enterprise Information Systems
56
conclusions drawn from the reported results.
3.1 RQ1: What Psychological Models
are Used to Identify Traits of
Personality of Software Engineering
Professionals?
In response to RQ1, the twenty-one selected articles
were read, and by consensus the researchers found
that during the period under study 3 psychological
models are considered essentials to assessing the per-
sonality of software engineering professionals. An-
other 3 models were used only once in the researched
period 5.
3.1.1 MBTI - Myers-Briggs Type Indicator
The MBTI model is the most applied one to iden-
tify software developers and is based on the model of
Carl Jung (Myers et al., 1985) (Myers et al., 1998).
MBTI divides human personality into three dimen-
sions: how do people relate to the world; the way
information is known and; the way information is pro-
cessed.
The MBTI is a personal characteristics identifica-
tion tool, which enables identifying the characteris-
tics, strengths and aspects of development. Thus, the
model identifies four pairs of preferences known as
dichotomies (Myers et al., 1985) (Myers et al., 1998),
briefly explained as follows.
Dichotomy Attitude (E-I): (I) Introversion: tend
to be involved with ideas. Prefer to think before act-
ing. Need time to think and recover energy. In gen-
eral, they are not very sociable; (E) Extroversion: tend
to act. Enjoy performing various activities. Act first
and think later. When inactive, their energy decreases.
They are generally sociable.
Dichotomy Functions (S-N and T-F): (S) Sensing:
they rely more on tangible things, concrete, sensory
information. They prefer details and facts. For them
the meaning is in data. They need a lot of informa-
tion; (N) Intuition: they prefer abstract and theoret-
ical information, which can be associated with other
information. They like to interpret data based on prior
knowledge. They work well with incomplete and de-
ductible information; (T) Thinking: they take deci-
sions based on logic and look for rational arguments;
(F) Feeling: they take decisions based on their feel-
ings rather than emotions.
Dichotomy Lifestyle (J-P): (J) Judging: they feel
calm when decisions are taken; (P) Perceiving: they
feel tranquil when leaves open decisions.
Combination of these 4 pairs can result in 16
different personalities. Personality type is made
up of four letters. First letter represents the atti-
tude dichotomy ((I) Introversion or (E) Extroversion),
the second and third letters represent functions di-
chotomy ((S) Sensory or (I) Intuitive - (T) Thinking
or (F) Feeling) and the fourth letter is the Lifestyle di-
chotomy ((J) Judging or (P) Perceiving) (Myers et al.,
1998), as depicted in Fig. 3.
Figure 3: MBTI Personality Types.
In theory, each of sixteen different kinds of per-
sonality measured by MBTI can be seen as a set
of patterns that indicates how the individual behaves
(Ferreira, Paula G and Silva, F, 2008).
3.1.2 BIG 5 Personality Dimensions
Another important model to evaluate personality is
the Big Five Personality Dimensions (Big 5) (Gold-
berg, 1990).
The Big Five model was originally created in
the 1970s by two independent research teams - Paul
Costa and Robert McCrae (at the National Institutes
of Health) and Warren Norman (at the University of
Michigan) / Lewis Goldberg (At the University of
Oregon) (Norman, 1967) - who have followed differ-
ent paths to achieve the same results, meaning that
most human personality traits can be reduced to ve
large dimensions regardless of language or culture.
In order to identify the five dimensions, the
researchers conducted interviews with hundreds of
questions to thousands of people and then analyzed
data using a statistical procedure known as factorial
analysis, which is used to reduce a large amount of
information to a synthetic and relevant set (McCrae
and John, 1998) (Norman, 1967).
The Big 5 consists of five personality traits that
are universal to the human population: (i) Insurgency:
Influence of Human Personality in Software Engineering - A Systematic Literature Review
57
refers to the orientation of an individual in relation to
others. Individuals with insurgency traits tend to be
talkative, bold, assertive and sociable; (ii) Agreeable-
ness: refers to the sympathy and social interaction of
a person. They are nice guys, get along well with oth-
ers, they are reliable and useful; (iii) Conscientious-
ness: refers to the organization. Conscientious indi-
viduals are suitable for hard working; they are orga-
nized and able to complete tasks in the proposed time;
(iv) Neuroticism: Refers to stress, anxiety, fear, and
the volatility of a person. Individuals with this trait
tend to not let emotion interfere with their work; (v)
Openness to experience: Refers to imagination, cu-
riosity and wit of an individual. Individuals with this
trait tend to be curious, open-minded and arts con-
noisseur (Goldberg, 1990).
Those features are understood as a complete de-
scription of the persona, are stable over a period of ten
years and may vary among cultures (Goldberg, 1990).
3.1.3 FFM - Five Factor Model
FFM is a variation of the Big 5 model. If on one hand
the descriptions of the ve characteristics are similar
to those of Big 5, on the other hand these two models
differ in terms of the theoretical basis, of causality and
measurement. While Big 5 assumes that personality
traits are important for social interaction, FFM pro-
vides a comprehensive model of causes and contexts.
FFM assumes, in a bio-social context, the influence
of genetic and environmental causality. Big 5 model
comprises a circular measurement model in contrast
to the FFM which is based on hierarchical measure-
ments (McCrae and John, 1998). The five factors
FFM are: (i) Extroversion: refers to a person involved
with the outside world. Extroverts feel comfortable in
social relations, are enthusiastic, friendly and active;
(ii) Agreeableness: refers to co-operation ability of an
individual; (iii) Conscientiousness: refers to how in-
dividuals manage, regulate and direct their impulses;
(iv) Neuroticism: refers to how an individual expe-
riences negative feelings. Those who have low neu-
roticism are emotionally stable, calm, confident and
secure; (v) Openness to experience: refers to an indi-
vidual’s imaginative and creative traits (McCrae and
John, 1998)(Salleh et al., 2009).
These three models were used in the period sur-
veyed to assess personality of software developers,
software testers, students and teachers by means of
surveys and experiments. A relationship between the
selected works and the theoretical models is presented
in Table 3. For the sake of data comprehension, we
used the IDs defined in Table 2.
3.1.4 Additional Models
Other less relevant models, such as Job Diagnostic
Survey (JDS) were found that measure how work im-
pacts people’s lives in an organization or society in
general (Morris and Venkatesh, 2010).
The Personal Style Inventory (PSI) consists of
8 traits, including 5 Big 5 models, plus Assertive-
ness, Image Management, Optimism, Tough Minded-
ness, Work Drive and Customer Service Orientation
(Lounsbury et al., 2003). This study found that these
characteristics significantly affect job satisfaction.
Temperament Classification Keirsey (KTS) is a
self-rated personality test designed to help people un-
derstand themselves and others. It is closely associ-
ated with the Myers-Briggs Indicator (MBTI) type.
However, the difference is that MBTI is concerned
about the thinking and feelings of people while KTS
is concerned about their obvious behaviors. In the
classification of personality types, the MBTI focuses
on contrasting extraversion and introversion, while
KTS emphasizes the sensation / intuition perspective
(Salleh et al., 2014).
3.2 RQ2: Are Activities Performed by
Software Engineering Professionals
Influenced by Their Personality?
On RQ2, identified through reading selected articles,
some points are raised by authors and leverage the dis-
cussion on the topic.
According to works presented in (Mourmant and
Gallivan, 2007), (Ferreira, Vito and Natasha, N,
2014) and (Kanij et al., 2015), constant technologi-
cal change, new methodological paradigms, outsourc-
ing services and distribution of work teams, chal-
lenges to understand personalities of software devel-
opers, Open source development, evolution of tasks
complexity, globalization, new business models, and
constantly changing activities have also their share of
contribution.
Some researchers have found that software devel-
opers with independent tasks that require a certain de-
gree of creativity tend to be introverts (Capretz, 2003)
(Darcy and Ma, 2005), while developers who perform
tasks that require collaboration and leadership tend to
be extroverts (Salleh et al., 2009).
On the other hand, there are inconsistencies be-
tween the results as reported in (Feldt et al., 2008) to
identify that there is shortage validity in personality-
software associations, and (Gorla and Lam, 2004)
when describing that lack guidance for the IT depart-
ment regarding the selection of personnel. In other
words, the personality often interferes on the software
ICEIS 2017 - 19th International Conference on Enterprise Information Systems
58
Table 3: Overview of Studies.
MODEL ID METHODS/PARTICIPANTS LOCAL
MBTI 01 Survey / 100 developers and students U.S.A.
02 Survey with 92 students China
04 Experiment with 55 students U.S.A.
07 Experiment with 22 students U.S.A.
08 Experiment with 1.471 students France
12 Experiment with 71 students Pakistan
16 Survey with 52 developers and 18 instructors Pakistan
17 Experiment with 63 developers Ireland
18 Survey (not portrayed) South Africa
BIG 5 03 Experiment with 29 students U.S.A.
05 Experiment with 60 developers and 68 students U.S.A.
09 Experiment with 105 students Spain
10 Survey with 47 developers Sweden
14 Experiment with 196 developers United Kingdom
15 Experiment with 137 students New Zealand
19 Survey with 200 developers Australia
20 Survey with 66 students India
21 Survey with 797 professionals U.S.A.
FFM 06 Survey with 143 developers U.S.A.
11 Experiment with 54 students New Zealand
13 Experiment with 453 students New Zealand
development simply because the developer was not
analyzed properly at the time of hiring. Some authors
say that while personality affects job satisfaction, its
influence on software development still remains un-
clear (Mourmant and Gallivan, 2007) (Salleh et al.,
2011).
The MBTI model was applied to individuals
(Capretz, 2003), to groups (Peslak, 2006), to students
(Rutherfoord, 2006), to professional software devel-
opers’ (Gorla and Lam, 2004) and software quality
(Barroso et al., 2016) . Most of the analyzed studies
compared the effect of developers personality in rela-
tion to job satisfaction, individual forms of work and
teamwork.
The effect of personality traits of students as-
sessed with MBTI, as well as their effectiveness at ex-
ploratory testing is discussed in (Shoaib et al., 2009).
The authors concluded that extrovert personality traits
are positively correlated with effective exploratory
testing. Exploratory testing is a specialized testing
technique. Thus, based on the findings of this study,
while it can be predicted that extraverts can be good
exploratory testers, whether extraverts will be good
testers in general remains an open question.
There is also research performed on analysing
the personality traits of software engineers in gen-
eral. Authors of paper (Hannay et al., 2010) analysed
five research studies conducted from 1985 to 2010
using MBTI to determine the personality types of
software engineers. Combined results indicate think-
ing and judging type assessed with MBTI were over-
represented among software engineers. A systematic
literature review on personality research with soft-
ware engineers published in (Feldt et al., 2008) found
the majority of personality research examined pair
programming and team effectiveness, and MBTI was
used in most of the research.
Two studies compared personality types between
industry and academy (Raza, A and Capretz, L F,
2012) (Yilmaz and O’Connor, 2012) and concluded
that the most common types of personalities are INTJ,
ISTJ, ESTP and ESTJ (Fig. 2).
Studies such as (Gorla and Lam, 2004) and
(Mourmant and Gallivan, 2007) identified the ISTJ
type as the most common among software develop-
ers. The Big 5 model, which has gained prominence
in software engineering research in recent years, the
model has been applied to individuals and teams
(Gomez and Acuna, 2007). Researchers use the Big
5 model to analyze cooperation between software de-
velopers and to examine pair programming (Chao and
Atli, 2006) (Hannay et al., 2010) (Salleh et al., 2011).
These studies, however, showed contradictory influ-
ence of personality in relation to performance, while
study (Salleh et al., 2011) claim that certain personal-
ity traits, such as satisfaction, significantly affect the
developer’s performance. In addition, studies (Chao
and Atli, 2006) and (Hannay et al., 2010) found no
correlation that, statistically, provided evidence of the
influence.
Study (Smith et al., 2016) performed a survey
about the beliefs, practices, and personalities of soft-
Influence of Human Personality in Software Engineering - A Systematic Literature Review
59
ware engineers in a large software company, with 797
professionals. They found no significant personality
differences between developers and testers. Managers
tend to be more aware and extroverted.
Authors of paper (Gulati et al., 2016) studied the
relationship between students performance in Soft-
ware Engineering and their personality. They have
also found no positive evidences. FFM model has
been applied in Software Engineering research, for in-
dividuals and teams (Salleh et al., 2009) (Salleh et al.,
2010). Topics ranged from the development of new
products as reported in (Aronson et al., 2006) and
to identify the dependencies between programming
methods, as reported in (Salleh et al., 2009). A set of
experiences related to students were executed in dif-
ferent dimensions of model proposed in (Salleh et al.,
2009) (Salleh et al., 2010) and (Salleh et al., 2011). In
this case, neither the conscientiousness nor the neu-
roticism affects academic students.
As it was observed, studies using the FFM model
were performed in an academic environment, and
found no significant effects of personality on the
performance of performed activities (Darcy and Ma,
2005) (Salleh et al., 2009) (Salleh et al., 2010) (Salleh
et al., 2011), while industry studies identified signifi-
cant influences of personality.
4 THREATS TO VALIDITY
This section describes concerns that must be im-
proved in future replications of this study. To organize
this section, the threats to validity were classified us-
ing the Internal, External and Construct (Wohlin et al.,
2012).
Construct Validity:
The main constructs in this re-
view are the two basic concepts “Personality” and
“Software engineering”.
For the first concept, we use term “Personality or
Motivation or Behavior or Humans Aspects or Satis-
faction” to make sure that all selected papers are re-
lated to term searched.
For the second concept, the terms “Software Engi-
neering, Software Development, Programming, Soft-
ware Test, Developer, Tester, ICT Manager, Project”
are used to ensure high coverage of potentially rele-
vant papers on the influence to software engineering
activities from database search.
A complementary manual search was discard due
to the fact there are not conferences and journals
specifically focused on the joint use of these concepts.
This threat is partially mitigated by including the gen-
eral intervention term “personality” along with “Soft-
ware engineering” in the terms for the search in three
reputable databases.
Internal Validity: Some subjective decisions may
have occurred during selection and data extraction.
Some papers did not provide a clear description or
proper objectives and results, making difficult the ob-
jective application of the inclusion and exclusion cri-
teria. To minimize selection and extraction system-
atic mistakes, the processes was performed by four
reviewers, and any conflicts were discussed and re-
solved by all the authors.
External Validity: The search process described in
Section 2.1 was defined after several trial searches and
validated with the consensus of all authors. We tested
the coverage and representativeness of retrieved stud-
ies, including automatic database search and referral
scanning.
5 CONCLUSION AND FUTURE
WORKS
This paper helps to synthesize available evidence in
the literature on the study of the influence of hu-
man personality in software engineering and can help
academia and industry in their daily work. We have
found that there are at least three theoretical psy-
chological models to identify human personality that,
over the past fifteen years, have been applied to stud-
ies that analyze human personality of students, devel-
opers and instructors of Software Engineering.
Currently, based on results provided by this SLR
study, a controlled experiment has been performed
with students in order to assess the influence of hu-
man personality in software developed by them. The
idea is to identify if the human personality influences
quality of software. The MBTI and Big Five models
found in this SLR have been used in order to assess
the psychological profile, and to assess the quality of
software products using object-oriented metrics.
Upcoming works can search other repositories,
and other keywords could be added to the search
string. Moreover, it is worth highlighting that SLR
conduction is not a trivial task because of the amount
of papers that must be read. Besides that, relevant pri-
mary studies written in languages other than English
were disregarded in this research.
ACKNOWLEDGEMENTS
The authors would like to thank the Brazilian re-
search agency CNPq (grant 445500/2014-0) for finan-
cial support.
ICEIS 2017 - 19th International Conference on Enterprise Information Systems
60
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