| Title | Dynamic inference of abstract types |
| Publication Type | Conference Paper |
| Year of Publication | 2006 |
| Authors | Guo PJ, Perkins JH, McCamant S, Ernst MD |
| Conference Name | ISSTA 2006, Proceedings of the 2006 International Symposium on Software Testing and Analysis |
| Pagination | 255–265 |
| Date or Month Published | July |
| Conference Location | Portland, ME, USA |
| Abstract | An abstract type groups variables that are used for related purposes in a program. We describe a dynamic unification-based analysis for inferring abstract types. Initially, each run-time value gets a unique abstract type. A run-time interaction among values indicates that they have the same abstract type, so their abstract types are unified. Also at run time, abstract types for variables are accumulated from abstract types for values. The notion of interaction may be customized, permitting the analysis to compute finer or coarser abstract types; these different notions of abstract type are useful for different tasks. We have implemented the analysis for compiled x86 binaries and for Java bytecodes. Our experiments indicate that the inferred abstract types are useful for program comprehension, improve both the results and the run time of a follow-on program analysis, and are more precise than the output of a comparable static analysis, without suffering from overfitting. |
| Downloads | https://plse.cs.washington.edu/daikon/ DynComp implementation (distributed as part of Daikon)
https://homes.cs.washington.edu/~mernst/pubs/abstract-type-issta2006.pdf PDF
|
| Citation Key | GuoPME2006 |
