Name
Abstract | ||
|---|---|---|
AbstractUnderstanding program behaviors is important to verify program properties or to optimize programs. Static analysis is a widely used technique to approximate program behaviors via abstract interpretation. To evaluate the quality of static analysis, researchers have used three metrics: performance, precision, and soundness. The static analysis quality depends on the analysis techniques used, but the best combination of such techniques may be different for different programs. To find the best combination of analysis techniques for specific programs, recent work has proposed parametric static analysis. It considers static analysis as black-box parameterized by analysis parameters, which are techniques that may be configured without analysis details. We formally define the parametric static analysis, and we survey analysis parameters and their parameter selection in the literature. We also discuss open challenges and future directions of the parametric static analysis. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1145/3464457 | ACM Computing Surveys |
Keywords | DocType | Volume |
Static analysis, parametric analysis, analysis techniques, abstraction | Journal | 54 |
Issue | ISSN | Citations |
7 | 0360-0300 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jihyeok Park | 1 | 2 | 4.09 |
| Hongki Lee | 2 | 13 | 2.38 |
| Sukyoung Ryu | 3 | 185 | 25.77 |