Do Personality Profiles Differ in the Pakistani Software Industry and Academia - A Case Study
July 24, 2015 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Arif Raza, Zaka-ul-Mustafa, Luiz Fernando Capretz
arXiv ID
1507.06888
Category
cs.SE: Software Engineering
Citations
7
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Effects of personality profiles and human factors in software engineering (SE) have been studied from different perspectives, such as: software life cycle, team performance, software quality attributes, and so on. This study intends to compare personality profiles of software engineers in academia and industry. In this survey we have collected personality profiles of software engineers from academia and the local industry in Pakistan. According to the Myers- Briggs Type Indicator (MBTI) instrument, the most prominent personality type among Pakistani academicians is a combination of Introversion, Sensing, Thinking, and Judging (ISTJ). However the most dominant personality type among software engineers in the Pakistani software industry is a combination of Extroversion, Sensing, Thinking, and Judging (ESTJ). The results of study establish that software engineers working in industry are mostly Extroverts as compared to those in academia who tend to be Introverts. The dimensions: Sensing, Thinking, and Judging (STJ), however, remain common in the dominant personality types of software engineers, both in Pakistani software industry and academia.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted