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20232026
most citedDetecting Security-Relevant Methods using Multi-label Machine Learning

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR2026

From Detection to Prevention: Explaining Security-Critical Code to Avoid Vulnerabilities

Ranjith Krishnamurthy, Oshando Johnson, Goran Piskachev +1

Security vulnerabilities often arise unintentionally during development due to a lack of security expertise and code complexity. Traditional tools, such as static and dynamic analy…

cs.SE2025

Explaining Software Vulnerabilities with Large Language Models

Oshando Johnson, Alexandra Fomina, Ranjith Krishnamurthy +3

The prevalence of security vulnerabilities has prompted companies to adopt static application security testing (SAST) tools for vulnerability detection. Nevertheless, these tools f…

cs.SE2024

Supporting Error Chains in Static Analysis for Precise Evaluation Results and Enhanced Usability

Anna-Katharina Wickert, Michael Schlichtig, Marvin Vogel +3

Context: Static analyses are well-established to aid in understanding bugs or vulnerabilities during the development process or in large-scale studies. A low false-positive rate is…

cs.LG2024★ 1 cited

Detecting Security-Relevant Methods using Multi-label Machine Learning

Oshando Johnson, Goran Piskachev, Ranjith Krishnamurthy +1

To detect security vulnerabilities, static analysis tools need to be configured with security-relevant methods. Current approaches can automatically identify such methods using bin…

cs.SE2023

slash: A Technique for Static Configuration-Logic Identification

Mohannad Alhanahnah, Philipp Schubert, Thomas Reps +2

Researchers have recently devised tools for debloating software and detecting configuration errors. Several of these tools rely on the observation that programs are composed of an…