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Conference object . 2019
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Conference object . 2019
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An Empirical Evaluation of the Relationship between Technical Debt and Software Security

Authors: Siavvas, Miltiadis; Tsoukalas, Dimitrios; Janković, Marija; Kehagias, Dionysios; Chatzigeorgiou, Alexander; Tzovaras, Dimitrios; Aničić, Nenad; +1 Authors

An Empirical Evaluation of the Relationship between Technical Debt and Software Security

Abstract

Technical Debt (TD) is commonly used in practice as a measure of software quality. Due to the potential overlap between software quality and software security, an interesting topic is to investigate whether TD can be used as a software security indicator as well. However, although some softwarerelated factors (e.g. software metrics) have been studied for their ability to indicate security risk in software products, no research attempts exist specifically focusing on TD. To this end, in the present study, we empirically evaluate the ability of TD to indicate security risks in software products. For this purpose, a relatively large code repository comprising 50 open-source software applications was constructed and analyzed using popular open-source static analysis tools, in order to calculate their TD and security level (i.e. vulnerability density). Subsequently, statistical analysis was employed, to assess the relationship between TD and software security. The results of the empirical study revealed a statistically significant positive and strong correlation between the TD and the vulnerability densities of the studied software products. This provides preliminary evidence for the ability of TD to be used as an indicator of software security. To the best of our knowledge, this is the first study that empirically evaluates the relationship between TD and software security.

Keywords

empirical study, software security, technical debt, static analysis, vulnerability prediction

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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