The Soft Skills of Software Learning Development:the Psychological Dimensions of Computing and Security Behaviours

Ivory, Matthew (2022) The Soft Skills of Software Learning Development:the Psychological Dimensions of Computing and Security Behaviours. In: Proceedings of the ACM International Conference on Evaluation and Assessment in Software Engineering, EASE 2022. ACM International Conference Proceeding Series . ACM, New York, pp. 317-322. ISBN 9781450396134

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Abstract

When writing software code, developers typically prioritise functionality over security, either consciously or unconsciously through biases and heuristics. This is often attributed to tangible pressures such as client requirements, but little is understood about the psychological dimensions affecting security behaviours. There is an increasing demand for understanding how psychological skills affect secure software development and to understand how these skills themselves are developed during the learning process. This doctoral research explores this research space, with aims to identify important workplace-based skills for software developers; to identify and empirically investigate the soft skills behind these workplace skills in order to understand how soft skills can influence security behaviours; and, to identify ways to introduce and teach soft skills to computer science students to prepare the future generation of software developers. The motivations behind this research are presented alongside the work plan. Three distinct phases are introduced, along with planned analyses. Phase one is currently in the data collection stage, with the second phase in planning. Prior relevant work is highlighted, and the paper concludes with a presentation of preliminary results and the planned next steps.

Item Type:
Contribution in Book/Report/Proceedings
Additional Information:
© ACM, 2022. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the ACM International Conference on Evaluation and Assessment in Software Engineering, EASE 2022, 2022 http://doi.acm.org/10.1145/3530019.3535344
ID Code:
181009
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Deposited On:
07 Dec 2022 09:55
Refereed?:
Yes
Published?:
Published
Last Modified:
17 Dec 2022 01:55