Dynamic slicing with soot

Abstract

Slicing is a powerful technique that can help a developer to understand how the interaction of different parts of a program causes a specific outcome. Dynamic slicing uses runtime information to compute a precise slice for a given execution. However, dynamic slicing is not possible without a static analysis of the underlying code to reveal dependencies between the instructions that have been recorded. In this paper, we present a new algorithm for computing dynamic slices. We describe how the optimization framework Soot was used to compute specialized intraprocedural dependency graphs that better reflect the programmer's view of a program than previous approaches. Combining these dependency graphs with recorded execution traces allowed us to create debuggable dynamic slices. For this, a mapping of the debugger's model of the execution to the static code model of Soot was needed, and could be found with only few ambiguities. This results in the ability to produce a dynamic slice that can not only be visualized, but explored interactively and adjusted to better answer specific questions.