1. What are the contributions in "Static value analysis of python programs by abstract interpretation" ?
The authors propose a static analysis by abstract interpretation for a significant subset of Python to infer variable values, run-time errors, and uncaught exceptions.. As Python lacks a formal specification, the authors first present a concrete collecting semantics of reachable program states.. The authors then propose a nonrelational flow-sensitive type and value analysis based on simple abstract domains for each type, and handle non-local control such as exceptions through continuations.. The authors show how to infer relational numeric invariants by leveraging the type information they gather.. Finally, the authors propose a relational abstraction of generators to count the number of available elements and prove that no StopIteration exception is raised.. Nevertheless, the authors are able to present preliminary experimental results on analyzing actual, if small, Python code from a benchmarking application and a regression test suite.
read more
2. What have the authors stated for future works in "Static value analysis of python programs by abstract interpretation" ?
The authors also wish to enrich the abstractions used in their analyzer, targeting in particular abstractions proposed for JavaScript [ 2,13,14 ] and Java [ 24 ].
read more
