@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.}
}