Co-evolutionary automatic programming for software development
Created by W.Langdon from
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- @Article{Arcuri2010,
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author = "Andrea Arcuri and Xin Yao",
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title = "Co-evolutionary automatic programming for software
development",
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journal = "Information Sciences",
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year = "2014",
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volume = "259",
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pages = "412--432",
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ISSN = "0020-0255",
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DOI = "doi:10.1016/j.ins.2009.12.019",
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URL = "http://www.sciencedirect.com/science/article/B6V0C-4Y34WFM-2/2/6700572128cf209a061759f28c5b7020",
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keywords = "genetic algorithms, genetic programming, SBSE, STGP,
Automatic programming, Automatic refinement,
Co-evolution, Software testing",
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size = "21 pages",
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abstract = "Since the 1970s the goal of generating programs in an
automatic way (i.e., Automatic Programming) has been
sought. A user would just define what he expects from
the program (i.e., the requirements), and it should be
automatically generated by the computer without the
help of any programmer. Unfortunately, this task is
much harder than expected. Although transformation
methods are usually employed to address this problem,
they cannot be employed if the gap between the
specification and the actual implementation is too
wide. In this paper we introduce a novel conceptual
framework for evolving programs from their
specification. We use genetic programming to evolve the
programs, and at the same time we exploit the
specification to co-evolve sets of unit tests. Programs
are rewarded by how many tests they do not fail,
whereas the unit tests are rewarded by how many
programs they make to fail. We present and analyse
seven different problems on which this novel technique
is successfully applied.",
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notes = "competitive co-evolution. MaxValue, AllEqual, Triangle
Classification, Swap, Order, Sorting, Median. One
variable called result write_result read_result. Simple
first order logic specification. Java, ECJ. Random
sampling SSP, ensemble N-version programming.",
- }
Genetic Programming entries for
Andrea Arcuri
Xin Yao
Citations