Name
Abstract | ||
|---|---|---|
The static detection of divide-by-zero, a common programming error, is particularly prone to false positives because conventional static analysis reports a divide-by-zero bug whenever it cannot prove the safety property - the divisor variable is not zero in all executions. When reasoning the program semantics over a large number of under-constrained variables, conventional static analyses significantly loose the bounds of divisor variables, which easily fails the safety proof and leads to a massive number of false positives. We propose a static analysis to detect divide-by-zero bugs taking additional evidence for under-constrained variables into consideration. Based on an extensive empirical study of known divide-by-zero bugs, we no longer arbitrarily report a bug once the safety verification fails. Instead, we actively look for affirmative evidences, namely source evidence and bound evidence, that imply a high possibility of the bug to be triggerable at runtime. When applying our tool Wit to the real-world software such as the Linux kernel, we have found 72 new divide-by-zero bugs with a low false positive rate of 22%. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1145/3510003.3510066 | 2022 ACM/IEEE 44TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING (ICSE 2022) |
DocType | ISSN | Citations |
Conference | 0270-5257 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yiyuan Guo | 1 | 0 | 0.68 |
| Jinguo Zhou | 2 | 0 | 0.34 |
| Peisen Yao | 3 | 3 | 2.40 |
| Qingkai Shi | 4 | 44 | 7.50 |
| Charles Zhang | 5 | 512 | 28.97 |