Automated Software Transplantation

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Barr:2015:ISSTA,
  author =       "Earl T. Barr and Mark Harman and Yue Jia and 
                 Alexandru Marginean and Justyna Petke",
  title =        "Automated Software Transplantation",
  booktitle =    "International Symposium on Software Testing and
                 Analysis, ISSTA 2015",
  year =         "2015",
  editor =       "Tao Xie and Michal Young",
  pages =        "257--269",
  address =      "Baltimore, Maryland, USA",
  month =        "14-17 " # jul,
  organisation = "ACM Special Interest Group on Software Engineering",
  publisher =    "ACM",
  note =         "ACM SIGSOFT Distinguished Paper Award",
  keywords =     "genetic algorithms, genetic programming, genetic
                 improvement, Automated software transplantation,
                 autotransplantation",
  isbn13 =       "978-1-4503-3620-8",
  URL =          "http://crest.cs.ucl.ac.uk/autotransplantation/",
  URL =          "http://crest.cs.ucl.ac.uk/autotransplantation/downloads/autotransplantation.pdf",
  URL =          "http://www.human-competitive.org/sites/default/files/barr-harman-jia-marginean-petke-text.txt",
  DOI =          "doi:10.1145/2771783.2771796",
  acmid =        "2771796",
  size =         "13 pages",
  abstract =     "Automated transplantation would open many exciting
                 avenues for software development: suppose we could
                 autotransplant code from one system into another,
                 entirely unrelated, system. This paper introduces a
                 theory, an algorithm, and a tool that achieve this.
                 Leveraging lightweight annotation, program analysis
                 identifies an organ (interesting behaviour to
                 transplant); testing validates that the organ exhibits
                 the desired behavior during its extraction and after
                 its implantation into a host. While we do not claim
                 automated transplantation is now a solved problem, our
                 results are encouraging: we report that in 12 of 15
                 experiments, involving 5 donors and 3 hosts (all
                 popular real-world systems), we successfully
                 autotransplanted new functionality and passed all
                 regression tests. Autotransplantation is also already
                 useful: in 26 hours computation time we successfully
                 autotransplanted the H.264 video encoding functionality
                 from the x264 system to the VLC media player; compare
                 this to upgrading x264 within VLC, a task that we
                 estimate, from VLC's version history, took human
                 programmers an average of 20 days of elapsed, as
                 opposed to dedicated, time",
  notes =        "Winner 2016 HUMIES

                 mutrans
                 http://crest.cs.ucl.ac.uk/autotransplantation/MuScalpel.html#scripts
                 muScalpel
                 http://crest.cs.ucl.ac.uk/autotransplantation/downloads/muScalpel.tar.gz

                 Pidgin Cflow SOX VLC Idct: Mytar Webserver TuxCrypt
                 Cflow x264

                 http://issta2015.cs.uoregon.edu/papers.php also known
                 as \cite{Barr:2015:AST:2771783.2771796}",
}

Genetic Programming entries for Earl Barr Mark Harman Yue Jia Alexandru Marginean Justyna Petke

Citations