- author = "Fan Wu and Mark Harman and Yue Jia and Jens Krinke",
- title = "{HOMI}: Searching Higher Order Mutants For Software Improvement",
- booktitle = "Proceedings of the 8th International Symposium on Search Based Software Engineering, SSBSE 2016",
- year = "2016",
- editor = "Federica Sarro and Kalyanmoy Deb",
- volume = "9962",
- series = "LNCS",
- pages = "18--33",
- address = "Raleigh, North Carolina, USA",
- month = "8-10 " # oct,
- publisher = "Springer",
- note = "best paper",
- keywords = "genetic algorithms, genetic programming, genetic improvement, SBSE",
- isbn13 = "978-3-319-47106-8",
-
DOI = "
doi:10.1007/978-3-319-47106-8_2",
- size = "16 pages",
- abstract = "This paper introduces HOMI, a Higher Order Mutation based approach for Genetic Improvement of software, in which the code modification granularity is finer than in previous work while scalability remains. HOMI applies the NSGA-II algorithm to search for higher order mutants that improve the non-functional properties of a program while passing all its regression tests. Experimental results on four real-world C programs shows that up to 14.7percent improvement on time and 19.7percent on memory are found using only First Order Mutants. By combining these First Order Mutants, HOMI found further improvement in Higher Order Mutants, giving an 18.2percent improvement on the time performance while keeping the memory improvement. A further manual analysis suggests that 88percent of the mutation changes cannot be generated using line based plastic surgery Genetic Improvement approaches.",
-
notes = "GP?
co-located with ICSME-2016 https://ssbse.info/2016/
gismo",
