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| Content Provider | ACM Digital Library |
|---|---|
| Author | Heo, Kihong Yi, Kwangkeun Lee, Wonchan Yang, Hongseok Oh, Hakjoo |
| Copyright Year | 2015 |
| Abstract | We present a method for selectively applying context-sensitivity during interprocedural program analysis. Our method applies context-sensitivity only when and where doing so is likely to improve the precision that matters for resolving given queries. The idea is to use a pre-analysis to estimate the impact of context-sensitivity on the main analysis’s precision, and to use this information to find out when and where the main analysis should turn on or off its context-sensitivity. We formalize this approach and prove that the analysis always benefits from the pre-analysis--guided context-sensitivity. We implemented this selective method for an existing industrial-strength interval analyzer for full C. The method reduced the number of (false) alarms by 24.4% while increasing the analysis cost by 27.8% on average. The use of the selective method is not limited to context-sensitivity. We demonstrate this generality by following the same principle and developing a selective relational analysis and a selective flow-sensitive analysis. Our experiments show that the method cost-effectively improves the precision in the these analyses as well. |
| Starting Page | 1 |
| Ending Page | 45 |
| Page Count | 45 |
| File Format | |
| ISSN | 01640925 |
| e-ISSN | 15584593 |
| DOI | 10.1145/2821504 |
| Volume Number | 38 |
| Issue Number | 2 |
| Journal | ACM Transactions on Programming Languages and Systems (TOPLAS) |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2015-12-22 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Static analysis Abstract interpretation Context-sensitive analysis |
| Content Type | Text |
| Resource Type | Article |
| Subject | Software |
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