4.3 Article

Technical debt as an indicator of software security risk: a machine learning approach for software development enterprises

Journal

ENTERPRISE INFORMATION SYSTEMS
Volume 16, Issue 5, Pages -

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/17517575.2020.1824017

Keywords

Software engineering; technical debt; software security; vulnerability prediction; decision making

Funding

  1. European Union's Horizon 2020 Research and Innovation Programme through the SDK4ED project [780572]

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Vulnerability prediction is important for developing secure software by identifying and mitigating security risks early. The study suggests that technical debt indicators may have potential as security indicators, at both project and class levels.
Vulnerability prediction facilitates the development of secure software, as it enables the identification and mitigation of security risks early enough in the software development lifecycle. Although several factors have been studied for their ability to indicate software security risk, very limited attention has been given to technical debt (TD), despite its potential relevance to software security. To this end, in the present study, we investigate the ability of common TD indicators to indicate security risks in software products, both at project-level and at class-level of granularity. Our findings suggest that TD indicators may potentially act as security indicators as well.

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