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| Content Provider | ACM Digital Library |
|---|---|
| Author | Yu, Hongtao Xue, Jingling Zhang, Zhaoqing Feng, Xiaobing Huo, Wei |
| Abstract | We present a practical and scalable method for flow- and context-sensitive (FSCS) pointer analysis for C programs. Our method analyzes the pointers in a program level by level in terms of their points-to levels, allowing the points-to relations of the pointers at a particular level to be discovered based on the points-to relations of the pointers at this level and higher levels. This level-by-level strategy can enhance the scalability of the FSCS pointer analysis in two fundamental ways, by enabling (1) fast and accurate flow-sensitive analysis on full sparse SSA form using a flow-insensitive algorithm and (2) fast and accurate context-sensitive analysis using a full transfer function and a meet function for each procedure. Our level-by-level algorithm, LevPA, gives rises to (1) a precise and compact SSA representation for subsequent program analysis and optimization tasks and (2) a flow- and context-sensitive MAY/MUST mod (modification) set and read set for each procedure. Our preliminary results show that LevPA can analyze some programs with over a million lines of C code in minutes, faster than the state-of-the-art FSCS methods. |
| Starting Page | 218 |
| Ending Page | 229 |
| Page Count | 12 |
| File Format | |
| ISBN | 9781605586359 |
| DOI | 10.1145/1772954.1772985 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2010-04-24 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Pointer analysis Alias analysis |
| Content Type | Text |
| Resource Type | Article |
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