Is a False Positive really False Positive?
Hongjun Choi, Hyuk Lee, Jin‐Young Choi
Abstract
Hongjun Choi, Hyuk Lee, Jin‐Young Choi
Abstract
As the number of devices with software increases, software reliability and security has become more critical. To improve reliability and security, developers and test engineers use static analysis tools to find defects early in the development process. However, it takes a lot of time and effort to determine whether alarms from performing static analysis are true or false positive. In this paper, we argue that all integer overflow generated by static analysis tools are weaknesses and should eventually be corrected. To show that our argument is reasonable, we explain static analysis results for binary search program code and CWE:190 example code in terms of reliability and security. It is unnecessary to identify whether the integer overflow generated by static analysis tools is true or false positive.
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As the number of devices with software increases, software reliability and security has become more critical. To improve reliability and security, developers and test engineers use static analysis tools to find defects early in the development process. However, it takes a lot of time and effort to determine whether alarms from performing static analysis are true or false positive. In this paper, we argue that all integer overflow generated by static analysis tools are weaknesses and should eventually be corrected. To show that our argument is reasonable, we explain static analysis results for binary search program code and CWE:190 example code in terms of reliability and security. It is unnecessary to identify whether the integer overflow generated by static analysis tools is true or false positive.
Key concepts: Static analysis, Computer science, Reliability (semiconductor), Software security assurance, Software quality, Integer (computer science), Reliability engineering, Static program analysis