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The Perspective of Agile Software Developers on Data Privacy
Universidade de Pernambuco (UPE), Brazil.
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.ORCID iD: 0000-0002-3646-235x
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.ORCID iD: 0000-0003-0619-6027
Universidade Federal de Pernambuco (UFPE), Brazil.
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2024 (English)In: Journal of Software: Evolution and Process, ISSN 2047-7473, E-ISSN 2047-7481Article in journal (Refereed) Epub ahead of print
Abstract [en]

Recent studies have shown that many software developers do not have sufficient knowledge and understanding of how to develop a privacy-friendly system. This may become a challenge in developing systems complying with data protection laws. To address this issue, we investigated the factors that influence developers' decision-making when developing privacy-sensitive systems.

We conducted an empirical study by means of a survey with 109 practitioners. Our data analysis is based on the principles of social cognitive theory, which includes personal, behavioral, and external environmental factors.

We identified six personal, five behavioral, and five external environment factors that affect how developers make decisions regarding privacy, including confusion between privacy and security and reliance on informal practices and organizational support gaps. These findings contribute to understanding how practitioners and companies consider privacy, showing improvements in formal training and structured support over previous studies yet highlighting persistent challenges in consistent privacy integration. 

Place, publisher, year, edition, pages
John Wiley & Sons, 2024.
Keywords [en]
empirical study, privacy, software development, Agile softwares, Data protection laws, Decisions makings, Empirical studies, Environmental factors, External environments, Sensitive systems, Social cognitive theory, Software developer, Differential privacy
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:bth-27356DOI: 10.1002/smr.2755ISI: 001389574100001Scopus ID: 2-s2.0-85212760764OAI: oai:DiVA.org:bth-27356DiVA, id: diva2:1924133
Part of project
SERT- Software Engineering ReThought, Knowledge Foundation
Funder
Knowledge Foundation, 20180010Available from: 2025-01-03 Created: 2025-01-03 Last updated: 2025-01-17Bibliographically approved

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Gorschek, TonyMendez, DanielFucci, Davide

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