Approximate Oracles and Synergy in Software Energy Search Spaces

Created by W.Langdon from gp-bibliography.bib Revision:1.4504

  author =       "Bobby R. Bruce and Justyna Petke and Mark Harman and 
                 Earl T. Barr",
  journal =      "IEEE Transactions on Software Engineering",
  title =        "Approximate Oracles and Synergy in Software Energy
                 Search Spaces",
  note =         "Early Access",
  keywords =     "genetic algorithms, genetic programming, genetic
                 improvement, search-based software engineering, SBSE,
                 synergy, Energy consumption, Energy measurement,
                 antagonism, oracle, approximation",
  ISSN =         "0098-5589",
  URL =          "",
  URL =          "",
  DOI =          "doi:10.1109/TSE.2018.2827066",
  size =         "20 pages",
  abstract =     "Reducing the energy consumption of software systems
                 though optimisations techniques such as genetic
                 improvement is gaining interest. However, efficient and
                 effective improvement of software systems requires a
                 better understanding of the code-change search space.
                 One important choice practitioners have is whether to
                 preserve the system's original output or permit
                 approximation with each scenario having its own search
                 space characteristics. When output preservation is a
                 hard constraint, we report that the maximum energy
                 reduction achievable by the modification operators is
                 2.69percent (0.76percent on average). By contrast, this
                 figure increases dramatically to 95.60percent
                 (33.90percent on average) when approximation is
                 permitted, indicating the critical importance of
                 approximate output quality assessment for code
                 optimisation. We investigate synergy, a phenomenon that
                 occurs when simultaneously applied source code
                 modifications produce an effect greater than their
                 individual sum. Our results reveal that 12.0percent of
                 all joint code modifications produced such a
                 synergistic effect though 38.5percent produce an
                 antagonistic interaction in which simultaneously
                 applied modifications are less effective than when
                 applied individually. This highlights the need for more
                 advanced search-based approaches.",
  notes =        "To be presented at ESEC/FSE 2018 Journal-First

                 also known as \cite{8338061}",

Genetic Programming entries for Bobby R Bruce Justyna Petke Mark Harman Earl Barr