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Too Many Issues: Automatically Prioritizing Analyzer Findings by Tracing Security Importance

  • ,
  • Katharina Großer
    ,
  • Marco Konersmann
    ,
  • Wasja Brunotte
    ,
  • Maike Ahrens
    ,
  • Kurt Schneider
  • Ruhr University Bochum
    ,
  • University of Koblenz
    ,
  • Ista SE
    ,
  • Leibniz University Hannover
Research Output:
Journal Article or Conference Article in Journal
Journal article
Peer-review

Open access

Publication Information

Output type

Research Output:
Journal Article or Conference Article in Journal
Journal article
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 1-38

Journal (Volume, Issue Number)

ACM Transactions on Software Engineering and Methodology

Publication milestones

  • Published - 17/06/2025

Publication status

Published - 17/06/2025

ISSN

1049-331X

Publication IDs

  • ORCID: /0000-0002-2604-0487/work/186147859
  • Scopus: 105031589661

Abstract

Code-based analyzers often find too many potentially security-related issues to address them all. Therefore, issues likely to lead to vulnerabilities should be fixed first. Such prioritization requires project-specific knowledge, such as quality requirements, security-related decisions, and design, which is not accessible to code analyzers. We present TraceSEC, an automated technique for prioritizing issues according to their security-related importance to the project. Its core concept is to incorporate available design artifacts and trace links between them, thus considering the project context that the code lacks. We reduce the problem of issue prioritization to a maximum flow problem and quantify the importance of each issue by the flow from user-defined quality aspects to the issue, i.e., quantifying its impact on project-specific security preferences. Our evaluation shows that TraceSEC effectively provides automated prioritization and can be tailored to project-specific quality goals. Its prioritization correlates stronger with manual expert prioritization than SonarQube rule severities, which are commonly used in practice. In particular, TraceSEC has a higher similarity for identifying high-priority issues. TraceSEC scales reasonably well for codebases up to 4 million lines of code, and the initial setup overhead is likely to be recouped after the first automated prioritization.

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