abstract = "Genetic Improvement is an evolutionary-based
technique. Despite its relatively recent introduction,
several successful applications have been already
reported in the scientific literature: it has been
demonstrated able to modify the code complex programs
without modifying their intended behaviour; to increase
performance with regards to speed, energy consumption
or memory use. Some results suggest that it could be
also used to correct bugs, restoring the software's
intended functionalities. Given the novelty of the
technique, however, instances of Genetic Improvement so
far rely upon ad-hoc, language-specific
implementations. In this paper, we propose a general
framework based on the software engineering's idea of
mutation testing coupled with Genetic Programming, that
can be easily adapted to different programming
languages and objective. In a preliminary evaluation,
the framework efficiently optimizes the code of the md5
hash function in C, Java, and Python.",