@inproceedings{beckert2017semslice,
title = {{SemSlice}: Exploiting Relational Verification for
Automatic Program Slicing},
author = {Bernhard Beckert and Thorsten Bormer and Stephan Gocht and
Mihai Herda and Daniel Lentzsch and Mattias Ulbrich},
booktitle = {13th International Conference on Integrated Formal Methods
({iFM} 2017)},
series = {Lecture Notes in Computer Science},
volume = {10510},
pages = {312--319},
publisher = {Springer},
year = {2017},
month = sep,
pages = {312--319},
doi = {10.1007/978-3-319-66845-1_20}
%%SNIP
, abstract = {We present SemSlice, a tool which automatically produces very precise slices for C routines.
Slicing is the process of removing statements from a program such that defined aspects of its
behavior are retained. For producing precise slices, i.e., slices that are close to the minimal
number of statements, the program's semantics must be considered. SemSlice is based on automatic
relational regression verification, which SemSlice uses to select valid slices from a set of
candidate slices. We present several approaches for producing candidates for precise slices.
Evaluation shows that regression verification (based on coupling invariant inference) is a
powerful tool for semantics-aware slicing: precise slices for typical slicing challenges can be
found automatically and fast.}
}