[Context] The popularity of tools for software quality analysis has increased over the years, with special attention to tools that calculate technical debt based on violations of a set of rules. SonarQube is one of the most used tools and provides an estimation of the time needed to remediate technical debt. However, practitioners are still skeptical about the accuracy of its remediation time estimation. [Objective] In this paper, we analyze the accuracy of SonarQube remediation time on a set of 15 open source Java projects. [Method] We designed and conducted a case study where we asked 65 novice developers to remove rule violations and reduce the technical debt of 15 projects. [Results] The results point out that SonarQube remediation time, compared to the actual time for reducing technical debt, is generally overestimated, and that the most accurate estimation relates to code smells, while the least accurate concerns bugs. [Conclusions] Practitioners and researchers could benefit from the results of this work to understand up to which extent technical debt is overestimated and have a more accurate estimation of the remediation time.?
On the Accuracy of SonarQube Technical Debt Remediation Time
Romano S.
2019-01-01
Abstract
[Context] The popularity of tools for software quality analysis has increased over the years, with special attention to tools that calculate technical debt based on violations of a set of rules. SonarQube is one of the most used tools and provides an estimation of the time needed to remediate technical debt. However, practitioners are still skeptical about the accuracy of its remediation time estimation. [Objective] In this paper, we analyze the accuracy of SonarQube remediation time on a set of 15 open source Java projects. [Method] We designed and conducted a case study where we asked 65 novice developers to remove rule violations and reduce the technical debt of 15 projects. [Results] The results point out that SonarQube remediation time, compared to the actual time for reducing technical debt, is generally overestimated, and that the most accurate estimation relates to code smells, while the least accurate concerns bugs. [Conclusions] Practitioners and researchers could benefit from the results of this work to understand up to which extent technical debt is overestimated and have a more accurate estimation of the remediation time.?I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
