  A branch of automated program repair (APR) techniques look at finding and
reusing existing code for bug repair. ssFix is one of such techniques that is
syntactic search-based: it searches a code database for code fragments that are
syntactically similar to the bug context and reuses such retrieved code
fragments to produce patches. Using such a syntactic approach, ssFix is
relatively lightweight and was shown to outperform many other APR techniques.
In this paper, to investigate the true effectiveness of ssFix, we conducted
multiple experiments to validate ssFix's built-upon assumption (i.e., to see
whether it is often possible to reuse existing code for bug repair) and
evaluate its code search and code reuse approaches. Our results show that while
the basic idea of ssFix, i.e., reusing existing code for bug repair, is
promising, the approaches ssFix uses are not the best and can be significantly
improved. We proposed a new repair technique sharpFix which follows ssFix's
basic idea but differs in the code search and reuse approaches used. We
evaluated sharpFix and ssFix on two bug datasets: Defects4J and
Bugs.jar-ELIXIR. The results confirm that sharpFix is an improvement over
ssFix. For the Defects4J dataset, sharpFix successfully repaired a total of 36
bugs and outperformed many existing repair techniques in repairing more bugs.
For the Bugs.jar-ELIXIR dataset, we compared sharpFix, ssFix, and four other
APR techniques, and found that sharpFix has the best repair performance. In
essence, the paper shows how effective a syntactic search-based approach can be
and what techniques should be used for such an approach.
