- author = "William B. Langdon and David R. White and Mark Harman and Yue Jia and Justyna Petke",
- title = "{API}-Constrained Genetic 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 = "224--230",
- address = "Raleigh, North Carolina, USA",
- month = "8-10 " # oct,
- publisher = "Springer",
- keywords = "genetic algorithms, genetic programming, genetic improvement, SBSE, image segmentation, $50K OpenCV Challenge, library C++ source code, bikes computer vision benchmark dataset",
- isbn13 = "978-3-319-47106-8",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/Langdon_2016_SSBSE.pdf",
-
DOI = "
doi:10.1007/978-3-319-47106-8_16",
- size = "6 pages",
- abstract = "ACGI respects the Application Programming Interface whilst using genetic programming to optimise the implementation of the API. It reduces the scope for improvement but it may smooth the path to GI acceptance because the programmer's code remains unaffected; only library code is modified. We applied ACGI to C++ software for the state-of-the-art OpenCV SEEDS superPixels image segmentation algorithm, obtaining a speed up of up to 13.2percent (sd 1.3percent) to the 50K Challenge winner announced at CVPR 2015.",
-
notes = "Simple blue example of grammar based Genetic
Improvement
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/gp-code/opencv_gp.tar.gz
SSBSE-2016 challenge track. Example images http://www.cs.ucl.ac.uk/staff/W.Langdon/ssbse2016/acgi/
Mutations chosen equally between insert, delete, replace and swap.
gismo",
