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 contextsensitivity 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-analysisguided 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 contextsensitivity. We demonstrate this generality by following the same principle and developing a selective relational analysis.
| Original language | English |
|---|---|
| Title of host publication | PLDI 2014 - Proceedings of the 2014 ACM SIGPLAN Conference on Programming Language Design and Implementation |
| Publisher | Association for Computing Machinery |
| Pages | 475-484 |
| Number of pages | 10 |
| ISBN (Print) | 9781450327848 |
| DOIs | |
| Publication status | Published - 2014 Jan 1 |
| Externally published | Yes |
| Event | 35th ACM SIGPLAN Conference on Programming Language Design and Implementation, PLDI 2014 - Edinburgh, United Kingdom Duration: 2014 Jun 9 → 2014 Jun 11 |
Publication series
| Name | Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI) |
|---|
Conference
| Conference | 35th ACM SIGPLAN Conference on Programming Language Design and Implementation, PLDI 2014 |
|---|---|
| Country | United Kingdom |
| City | Edinburgh |
| Period | 14/6/9 → 14/6/11 |
Fingerprint
Keywords
- Context-sensitive analysis
- Static analysis
ASJC Scopus subject areas
- Software
Cite this
Selective context-sensitivity guided by impact pre-analysis. / Oh, Hakjoo; Lee, Wonchan; Heo, Kihong; Yang, Hongseok; Yi, Kwangkeun.
PLDI 2014 - Proceedings of the 2014 ACM SIGPLAN Conference on Programming Language Design and Implementation. Association for Computing Machinery, 2014. p. 475-484 (Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI)).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Selective context-sensitivity guided by impact pre-analysis
AU - Oh, Hakjoo
AU - Lee, Wonchan
AU - Heo, Kihong
AU - Yang, Hongseok
AU - Yi, Kwangkeun
PY - 2014/1/1
Y1 - 2014/1/1
N2 - 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 contextsensitivity 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-analysisguided 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 contextsensitivity. We demonstrate this generality by following the same principle and developing a selective relational analysis.
AB - 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 contextsensitivity 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-analysisguided 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 contextsensitivity. We demonstrate this generality by following the same principle and developing a selective relational analysis.
KW - Context-sensitive analysis
KW - Static analysis
UR - http://www.scopus.com/inward/record.url?scp=84901626665&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84901626665&partnerID=8YFLogxK
U2 - 10.1145/2594291.2594318
DO - 10.1145/2594291.2594318
M3 - Conference contribution
AN - SCOPUS:84901626665
SN - 9781450327848
T3 - Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI)
SP - 475
EP - 484
BT - PLDI 2014 - Proceedings of the 2014 ACM SIGPLAN Conference on Programming Language Design and Implementation
PB - Association for Computing Machinery
ER -