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This paper presents a theory of dynamic slicing, which reveals that the relationship between static and dynamic slicing is more subtle than previously thought. The definitions of dynamic slicing are formulated in terms of the projection theory of slicing. This shows that existing forms of dynamic slicing contain three orthogonal dimensions in their slicing criteria and allows for a lattice-theoretic study of the subsumption relationship between these dimensions and their relationship to static slicing formulations.

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Although the slicing of programs written in a high-level language has been widely studied in the literature, very little work has been published on the slicing of binary executable programs. The lack of existing solutions is really hard to understand since the application domain for slicing binaries is similar to that for slicing high-level languages. In this paper we present a method for the interprocedural static slicing of binary executables. We applied our slicing method to real size binaries and achieved an interprocedural slice size of between 56%-68%. We used conservative approaches to handle unresolved function calls and branching instructions. Our current implementation contains an imprecise (but safe) memory dependence model as well. However, this conservative slicing method might still be useful in analysing large binary programs. In the paper we suggest some improvements to eliminate useless edges from dependence graphs as well.

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The first step in dealing with an input that triggers a fault in a software is simplifying it as much and as automatically as possible, since a minimal test case can ensure the efficient use of human developer resources. The well-known minimizing Delta Debugging algorithm is widely used for automated test case simplification but even its last published revision is more than a decade old. Thus, in this paper, we investigate how it performs nowadays, especially (but not exclusively) focusing on its parallelization potential. We present new improvement ideas, give algorithm variants formally and in pseudo-code, and evaluate them in a large-scale experiment of more than 1000 test minimization sessions featuring real test cases. Our results show that with the help of the proposed improvements, Delta Debugging needs only one-fourth to one-fifth of the original execution time to reach 1-minimal results.

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