Using complexity, coupling, and cohesion metrics as early indicators of vulnerabilities

By Istehad Chowdhury, Mohammad Zulkernine. Journal of systems architecture, 2011

305 citations recorded by the source corpus.

Subfields: Information Systems, Software

View Paper: https://www.semanticscholar.org/paper/d81aa334dc3cd2ecd1cc4d4d4a7123ccb3bdbb9e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems

1. Sheng Wen
2. Qing-Long Han
3. Riccardo Scandariato
4. Wouter Joosen
5. Guanjun Lin
6. Jun Zhang
7. Yang Xiang
8. Hamid Reza Shahriari

In Software

1. Sheng Wen
2. Qing-Long Han
3. Guanjun Lin
4. Jun Zhang
5. Yang Xiang
6. Hamid Reza Shahriari
7. Seyed Mohammad Ghaffarian

Citations in the corpus

• Software Vulnerability Detection Using Deep Neural Networks: A Survey (2020, background): “Once these security-critical bugs are exploited by attackers, it may result in the violation of security policies, leading to security failure [20].”
• Predicting Vulnerable Software Components via Text Mining (2014, background): “The authors’ initial results demonstrated that there is a correlation (albeit weak) between complexity TABLE 1 Vulnerability Prediction Models in the Related Work Study Predictors used Vulnerability sources Prediction technique Applications Performance Shin et al. [5] software metrics, code churn, d”