Name
Abstract | ||
|---|---|---|
Pointer information, indispensable for static analysis tools, is expensive to compute and query. We provide a query-efficient persistence technique, Pestrie, to mitigate the costly computation and slow querying of precise pointer information. Leveraging equivalence and hub properties, Pestrie can compress pointer information and answers pointer related queries very efficiently. The experiment shows that Pestrie produces 10.5X and 17.5X smaller persistent files than the traditional bitmap and BDD encodings. Meanwhile, Pestrie is 2.9X to 123.6X faster than traditional demand-driven approaches for serving points-to related queries. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2594291.2594314 | PLDI |
Keywords | Field | DocType |
pointer information,persistent pointer information,hub property,costly computation,query-efficient persistence technique,traditional demand-driven approach,precise pointer information,traditional bitmap,leveraging equivalence,bdd encodings,points-to related query,algorithms,languages | Tagged pointer,Pointer (computer programming),Static program analysis,Computer science,Theoretical computer science,Equivalence (measure theory),Bitmap,Smart pointer,Pointer swizzling,Computation | Conference |
Volume | Issue | ISSN |
49 | 6 | 0362-1340 |
Citations | PageRank | References |
2 | 0.36 | 29 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiao Xiao | 1 | 16 | 1.59 |
| Qirun Zhang | 2 | 107 | 8.40 |
| Jinguo Zhou | 3 | 42 | 2.65 |
| Charles Zhang | 4 | 512 | 28.97 |