An Improved Assessment of Personality Traits in Software Engineering

Interdisciplinary Journal of Information, Knowledge, and Management
Volume 2, 2007
An Improved Assessment of Personality Traits in
Software Engineering
A. S. Sodiya
H. O. D. Longe
University of Agriculture,
University of Lagos,
Abeokuta, Nigeria
Lagos, Nigeria
sinaronke@yahoo.co.uk
hodlonge@yahoo.co.uk
S. A. Onashoga
O. Awodele
University of Agriculture,
Babcock University, Ilishan,
Abeokuta, Nigeria
Ogun, Nigeria
bookyln@yahoo.com
delealways@yahoo.com
L. O. Omotosho
Bowen University, Iwo, Nigeria
inedune@yahoo.com
Abstract
The success or otherwise of Software Engineering (SE) activities depends on the interactions
among software engineers. Consequently, effective interactions depend largely on personality
traits, which is a consistent and long-lasting tendency in behaviour. In psychology, five major
trait factors (The Big Five Factors) have been generally used to assess personality of people. But,
these might not be adequate in SE because of the required technical and cognitive skills. In this
work, we first present Cognitive Ability as an additional factor that must be measured in order to
adequately assess personality in SE. A research survey was conducted in order to capture person-
ality requirements in SE. Based on the result of the survey conducted, we develop a model for
assessing personality traits in SE. We then design an assessment technique that is based on re-
sponses to some well-structured and deductive on-line questions. The implementation of the
model using Visual Basic resulted in a much-needed tool that can guide intending software engi-
neers in choosing area of specialization in SE based on their personality traits.
Keywords: Software Engineering, Software Engineers, Personality Trait, Psychology
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Introduction
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Improved Assessment of Personality Traits
that is delivered on time, within budget and with the required quality (Hughes & Cotterell, 2002).
This implies that for the overall project to be successful, each team’s goal or subproject must also
be successful. The success or otherwise of a team depends largely on the interactions among the
members. Effective interactions among members are influenced by the personality traits possess
by members. A personality trait is defined as a consistent, long-lasting tendency in behavior
(Kalat, 1999).
Consequently, one may conclude or infer that the major development tool in any software project
is people. Getting the people, not only with the right technical skills, but also with the right per-
sonalities is paramount to the success of any software project. Howard (2001) stated that knowing
the qualifications, technical skills, and experience of team members is well and good, but equally
important is to understand the different working personalities of software developers. The secret
of productivity is to match the requirements of a particular project with the personalities of mem-
bers.
Effective team formation in software development is difficult to achieve and requires careful
amalgamation of personality traits. It is then important to have an efficient way for assessing the
personalities of software engineers so as to predict their conformity to the task and responsibili-
ties of software development. Young et al., (2005) mentioned that an informal discussion (inde-
pendently held) with another member of staff in an organisation had revealed a case of good
“programmer” with sound analytical skills who had left the company because he could not work
within a team focus.
This study presents a technique for personality traits assessment in software engineering. A tool is
then developed using Visual Basic to capture personality characteristics of software engineers.
The tool requires responding to an expert on-line questionnaire and determines personality status
of software engineers in relation to their nature of jobs. The questions are indirect and structured
in a way that respondents do not actually know their relationships with a particular trait.
The structure of this paper is as follows. The next section discusses previous related works. A
review of personality trait and software development and the architectural design are presented in
the third section. The implementation of the personality assessment technique is presented in the
fourth section. We present future work and conclusion in the fifth section.
Related Works
The study of personality started over 100 years by researchers in psychology. A recent work on
personality is on meta-analytic review of Big Five personality factors and accident involvement
in occupational and non-occupational setting. This research was conducted by Clark and Robert-
son (2005) and reported a meta-analysis of relationship between accident involvement and the
Big Five personality dimensions. Another is the work of Schmukle and Egloff (2005), which ana-
lysed the extent of occasion specific effects on Implicit Association Tests (IATs) for assessing
implicit self-concepts of personality traits. In order to compare the results obtained from different
traits; both anxiety and extraversion were assessed. A short five-factor personality inventory de-
veloped from the International Personality Item Pool (IPIP) was implemented as online question-
naire by Buchanan, Johnson, and Golberg (2005). The result of this work shows an acceptable
measure of the Five-factor model for use in internet-mediated research. A number of other per-
sonality scales have been implemented as on-line instruments. Studies on personality assessment
started over 40 years ago in psychology with works like MMPI & MMPI-2 (Hathaway &
Mckinley, 1940; Helmes & Reddon, 1993) and 16-PF Test (Cattell, 1965).
However, nowadays, the effects of personality traits are being examined across all disciplines.
This is because personality is concerned with human beings, who are key actors or resources in
all spheres of lives. Some of the disciplines where personality traits would certainly have signifi-
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Sodiya, Longe, Onashoga, Awodele, & Omotosho
cant influence on performance are the application areas of Information System, Software engi-
neering or Computer Science.
Wang and King (2006) explored the characteristics of human factors and their influences in engi-
neering. He presented a similar work that applies Real-Time Process Algebra (RPTA) to describe
the motivations and attitudes in software engineering (Wang, 2005). Wynekoop and Walz (1998)
examined the differences in personality profiles of key IT personnel and found out that there are
clear differences. Similar to this, is the work of Chilton and Hardgrave (2004), which assessed the
behavioural skills (Technical and Managerial) and determined the relationship between these
skills and personality traits.
Houghton (2004) introduced a theoretical framework for understanding the role of personal traits
in collaboration in virtual contexts. The work stated that individual traits and dyadic complemen-
tarities are mediating factors in interpersonal trust and willingness to use new technologies and
significantly affect the initiation, duration, and productivity of computer-mediated collaboration.
Another interesting work is conducted by Dick and Zarnett (2002) on paired programming and
personality traits. The work was carried out to determine whether the members have personality
traits that are needed for maximum performance. The work then suggested that the team members
in Paired or Extreme programming should be selected based on personality traits that are benefi-
ciary to paired programming approach. Howard (2001) emphasized in his paper the need to check
whether software engineers have got the right personality for the job.
We have seen that a lot of previous work stressing the need to assess the personality trait of IT
personnel, but none has really provided a technique for doing this. Also, Software Engineers have
their typical fields like designing, programming, testing, etc., it is important to determine whether
they have the right personalities for the chosen field.
This is a major interest in this work.
Design Methodology
Personality Traits
A personality trait is a consistent and long-lasting tendency in behaviour. There are different per-
sonality traits that people normally exhibit. The Big five personality factors as proposed by Gold-
berg (1990) are used widely to classify personality traits and are used as the basis for the assess-
ment model in section 4. The Big five personality factors consist of Neuroticism, Extraversion,
Agreeableness, Conscientiousness and Openness to experience. SE is a technical and complex
activity that requires a high level of cognitive ability. The success and otherwise of software de-
velopment depends on cognitive factors such as mindset, abstract thinking, analytic, visualization
capability, and so on. Consequently, the Big five personality factors can not be adequately used to
assess personality trait in SE. In this work, we have introduced an additional factor called Cogni-
tie Ability, to the Big five factors. The new SE-Personality assessment factors are represented in
Figure 1.
a.
Neuroticism:- This is the tendency to experience unpleasant emotions relatively eas-
ily. Its components are anxiety, hostility, depression, self-consciousness, and impul-
siveness. The opposite is emotional stability or self-control.
People who are high in this factor have the following features:-
They are faced with effect of decreasing cognitive and performance capaci-
ties (Mathews et al., 1991)
They have increasing probability of errors

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Improved Assessment of Personality Traits
They are more distracted from the task at hand (Hansen, 1989)
They have tendency to experience greater stress symptoms
They tend to be pre-occupied with their anxieties and worries
There is also evidence that they do not seek active control of the environment
(Judge, 1993)

Neuroticism
Neurotic
Extraversion
Agreea
Agre bl
ea -
SE-
SE PERS
PERS
eness
FAC
FA TO
T R
O S
eness
Openness
Openn
To
Exper
E
ie
i nc
n e
c
Consci
Consc entio
enti us
u nes
s
s
nes
Cognit
Cogni ive Ab
i
ililty
t

Figure 1: SE- Six personality assessment factors
b.
Extraversion:- This is the tendency to seek simulation and enjoy the company of
other people. Its components include warmth, sociable, assertive, energetic, adven-
turous, and enthusiastic.
People who are high in this factor have the following features:-
They are sensitive to monotony (Thiffault & Bergeron, 2003)
They are high sensation seekers and have a greater tendency to take risks (Jonah,
1997)
They demonstrate significantly poorer performance on vigilance tasks (Koelega,
1992)
c.
Conscientiousness:- This is the tendency to show self-discipline, to be dutiful, and to
strive for achievement and competence. Its components also include self-discipline,
consultative, competence, order, dutifulness and thorough.
People who are high in this factor have the following features:-
They are always thorough in decision-making style (Clarke & Robertson, 2005)
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Sodiya, Longe, Onashoga, Awodele, & Omotosho
They follow rules and regulations (Arthur & Doverspike, 2001)
They are interested in goal targeting and systematic approach
They are always interested in providing adequate cost-benefit analysis and con-
tingency planning (West et al., 1993)
They are less vulnerable to cognitive failures
d.
Agreeableness:-
This is the tendency to be compassionate towards others and not
antagonistic. Its components include pleasant, tolerant, tactful, helpful, trust, respect-
ful, sympathetic and modest.
People who are high in this factor have the following features:-
They are generally easy to get along with (Hough, 1992)
They are salient in situations that involve interaction or cooperation with others
(Barrick & Mount, 1991)
They are less aggressive
They are emotionally stable
They are trustworthy and compliance (Clarke & Robertson, 2005)
e.
Openness to experience:- This is the tendency to enjoy new intellectual experi-
ences and ideas. Its components include imaginative, curious, unconventional,
broadminded and cultured.
People who are high in this factor have the following features:-
They have positive disposition towards learning (Salgado, 2002)
They tend to be liable to rule violations, experimentation and improvisation (Clarke & Robertson,
2005)
They are less suitable for safety critical tasks
f.
Cognitive Ability:- This is a factor added to the big five factors because of the re-
quirement of SE. It has the following components:-
i.
Abstract level thinking:- This is the ability to conceive an idea or concept without
any relation to any practical instance. It can be simply put as theoretical analysis.
ii.
Mindset:- A fixed mental attitude or disposition that predetermines a person’s re-
sponses to and interpretation of the situation. It typically has to do with the col-
lective responses and interpretation of the situation by individuals.
iii.
Analytic:- This is reasoning or capable of reasoning in clear and consistent man-
ner. It is reasoning and or acting from a perception of the parts and interrelations
of actions.
iv.
Concentration capability:- This is the ability to provide constant and productive
undivided attention to events.
v.
Expressiveness:- Ability to present one’s ideas in acceptable forms to others.
vi.
Visualisation capability:- The ability to provide a technique or method for seeing
the unseen. It is also the ability to use metal model to describe or represent
events.

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Improved Assessment of Personality Traits
Review of Software Development Stages
Since this work is based on SE, we present a review of activities in SE in order to appreciate the
significance of personality traits. Figure 2 shows the stages in SE and Table 3 presents the sum-
mary of activities in SE.

SOFTWARE DEVELOPMENT
KEY SOFTWARE ENGINEERS
STAGES
Management of
Software management
Software Engineering
engineers
Process
E1
Requirement
Requirement
Engineering
Engineers
E2
I/O designer

Program designer
Database designer
E3
System Design
Interface designer
Security designer
Coding
Programmer
E4
Testing
Tester
and

E5
Implementation
Implementer
Evaluation
And
Evaluator
E6
Evolving

Figure 2: Representation of Software Development Stages and Software Engineers
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Sodiya, Longe, Onashoga, Awodele, & Omotosho
It can also be seen from Figure 2 that the different categories of software engineers are repre-
sented using E1, E2, E3, E4, E5, and E6.
Table 1: Summary of activities and engineers in software engineering
S/
Processes Sub-products/
Roles
Summary of activities
No
Products
1. Software
Successful
a. Project manager
- Project
engineering
software product b. Project-level process designer
organization
process
c. Project plan & estimation engi-
- Staffing
management
neer
- Planning and
d. Quality engineers
estimating
e. Project team coordinator
- Coordination
f.
Software development organi-
- Quality control
zation manager
g. Software environment and
tools manager
h. Software environment and
tools maintenance
2. Requirement System
a. Requirement capture engineer
- Fact findings
analysis
specification
b. Customer solution engineer
- Investigating the
c. Requirement analyst
current system
d. System analyst
- Modeling the
e. System requirement
current system
specification analyst
- Logical models of
f. Project control and
the required system
requirement manager
3. System
design System
a. Software engineering
- Structuring and
architecture
process designer
partitioning of the
b. Interface designer
design into
c. Software engineering
software sub-
methodology designer
components
d. Domain engineer
- Detailed design of
e. System architect
the components
- Formation of the
system structure
and relationships
4. Coding
Working
a. Algorithm developer
- Programming
software
b. Programmer
components of the
modules
system
- Unit testing

5.
System testing and
Complete
a. User testing coordinator
- Integrating
integration
software product b. Software testing
subcomponents
engineer
together
c. System integration and
- Integration testing
configuration engineer
- System testing to
ensure that the
system meets its
requirements

6. Delivery
and Working/
a. Delivered system manager
- Installing the
Maintenance
Implemented
b. Maintenance engineer
system in `live`
software
c. Technical trainer
environment
d. User technical supporter
- Training the users
e. System service evaluator
- Maintenance
- Implementing
enhancements as
demanded by
changes in users’ needs


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Improved Assessment of Personality Traits
Cogno-Personality Model for Software Engineering
Research Survey
To adequately construct the Cogno-Personality Assessment Model for Software Engineering
(CPAMSE), a research survey was conducted in order to capture information about personality
requirements for different roles in SE.
a.
Data gathering techniques
A well-structured questionnaire was administered to 112 software project team leaders in 19
software development organisations in Nigeria. The essence of this selection is to gather infor-
mation about personality traits of software engineers within these teams and their effects on team
performance from team leaders. The 112 team leaders gave personality and performance informa-
tion on 489 software engineers.
b.
Summary of survey result
The summary of the survey result is presented in Table 2. The required levels of personality traits
suggested by the team leaders in order to attain high performance for different roles in SE are
given in column five. The levels of trait (Low, Medium, High) were indicated by the teams lead-
ers of these engineers. According to Table 2, row 1 means that out of 489 software engineers con-
sidered, 36 were software process engineers. Out of these 36, 33 of them had high performance
rating. Out of these 33, 30(91%) had the trait level for Neuroticism to be low. The remaining
3(9%) had the trait level for Neuroticism to either be medium or high. The same explanation goes
to for others. With this result, we concluded that software process engineers must have a trait
level for neuroticism to be low.

Table 2: Summary of Personality Assessment Survey Result
Roles Total
Personality High Performance
Number of
Traits
No. for High
Level of Trait
Engineers
Performance
Software process 36
N
33
Low (30 – 91%)
management
E
32
Low (27 – 84%)
O
30
Medium(26 – 87%)
CC
29
Medium(28 – 97%)
C
31
Medium(28 – 90%)
A
31
High(25 – 81%)
Requirements
67
N 65 Low(55
–
85%)
Analysis
E
63
Medium(60 – 95%)
O 61 Low(54
–
89%)
CC
63
High(51 – 81%)
C
64
High(50 – 78%)
A
65
High(48 – 74%)
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Sodiya, Longe, Onashoga, Awodele, & Omotosho
System Design
64
N 57 Low(51
–
89%)
E 61 Low(60
–
98%)
O 62 Low(62
–
100%)
CC
59
High(53 – 90%)
C
60
High(49 – 82%)
A
63
High(45 – 71%)
Coding 183 N
167
Low(121 – 72%)
E
165
Low(142 – 86%)
O
175
Low(171 – 98%)
CC
177
High(173 – 98 %)
C
169
Medium(129 – 76%)
A 180 High(168
–
93%)
System Testing
87
N 86 Low(76
–
88%)
and Integration
E
84
Medium(71 – 85%)
O
80
High(62 – 78%)
CC
79
High(64 – 81%)
C
85
Medium(81 – 95%)
A
86
High(77 – 90%)
Delivery and
52
N 46 Low(41
–
89%)
Maintenance
E 47 Low(42
–
89%)
O
42
Medium(40 – 95%)
CC
42
Medium(34 – 81%)
C
41
High(35 – 85%)
A
48
High(42 – 88%)




The Model – CPAMSE
The result of this survey is then used to construct the Cogno-Personality Assessment Model for
Software Engineering (CPAMSE) as shown in Figure 3.

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Improved Assessment of Personality Traits


Neuroticism(N)
S


1






E1,E2,E3,E4,E5,E6

Agreeableness (A)
0

Extraversion (E)
1
E1, E2,E3,E4,E5,E6
1



E2,E5

E1, E3, E4,E6

0

0

Conscientiousness ( C )

Openness to ex-

1
Cogno-Personality
perience (O)
E2,E3,E6
1

Model for SE

E5
E1,E4,E5

E1,E6


0
E2,E3,E4

Cognitive Capability (CC)
0

1

E2,E3,E4,E5

E1,E6



0


Key:

Low


Medium

High


Figure 3: Cogno-personalityAssessment Model for SE (CMSE)
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