  To detect large-variance code clones (i.e. clones with relatively more
differences) in large-scale code repositories is difficult because most current
tools can only detect almost identical or very similar clones. It will make
promotion and changes to some software applications such as bug detection, code
completion, software analysis, etc. Recently, CCAligner made an attempt to
detect clones with relatively concentrated modifications called large-gap
clones. Our contribution is to develop a novel and effective detection approach
of large-variance clones to more general cases for not only the concentrated
code modifications but also the scattered code modifications. A detector named
LVMapper is proposed, borrowing and changing the approach of sequencing
alignment in bioinformatics which can find two similar sequences with more
differences. The ability of LVMapper was tested on both self-synthetic datasets
and real cases, and the results show substantial improvement in detecting
large-variance clones compared with other state-of-the-art tools including
CCAligner. Furthermore, our new tool also presents good recall and precision
for general Type-1, Type-2 and Type-3 clones on the widely used benchmarking
dataset, BigCloneBench.
