Advances in Automated Program Repair and a Call to Arms

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@InProceedings{Weimer:2013:SSBSE,
  author =       "Westley Weimer",
  title =        "Advances in Automated Program Repair and a Call to
                 Arms",
  booktitle =    "Symposium on Search-Based Software Engineering",
  year =         "2013",
  editor =       "Guenther Ruhe and Yuanyuan Zhang",
  volume =       "8084",
  series =       "Lecture Notes in Computer Science",
  pages =        "1--3",
  address =      "Leningrad",
  month =        aug # " 24-26",
  publisher =    "Springer",
  note =         "Invited keynote",
  keywords =     "genetic algorithms, genetic programming, SBSE,
                 GenProg",
  isbn13 =       "978-3-642-39741-7",
  URL =          "http://www.cs.ucl.ac.uk/staff/s.yoo/papers/Xie2013kx.pdf",
  DOI =          "doi:10.1007/978-3-642-39742-4_1",
  size =         "3 pages",
  abstract =     "In this keynote address I survey recent success and
                 momentum in the subfield of automated program repair. I
                 also encourage the search-based software engineering
                 community to rise to various challenges and
                 opportunities associated with test oracle generation,
                 large-scale human studies, and reproducible research
                 through benchmarks.

                 I discuss recent advances in automated program repair,
                 focusing on the search-based GenProg technique but also
                 presenting a broad overview of the subfield. I argue
                 that while many automated repair techniques are correct
                 by construction or otherwise produce only a single
                 repair (e.g., AFix [13], Axis [17], Coker and Hafiz
                 [4], Demsky and Rinard [7], Gopinath et al. [12], Jolt
                 [2], Juzi [8], etc.), the majority can be categorised
                 as generate and validate approaches that enumerate and
                 test elements of a space of candidate repairs and are
                 thus directly amenable to search-based software
                 engineering and mutation testing insights (e.g., ARC
                 [1], AutoFix-E [23], ARMOR [3], CASC [24], ClearView
                 [21], Debroy and Wong [6], FINCH [20], PACHIKA [5], PAR
                 [14], SemFix [18], Sidiroglou and Keromytis [22],
                 etc.). I discuss challenges and advances such as
                 scalability, test suite quality, and repair quality
                 while attempting to convey the excitement surrounding a
                 subfield that has grown so quickly in the last few
                 years that it merited its own session at the 2013
                 International Conference on Software Engineering
                 [3,4,14,18]. Time permitting, I provide a frank
                 discussion of mistakes made and lessons learnt with
                 GenProg [15].

                 In the second part of the talk, I pose three challenges
                 to the SBSE community. I argue for the importance of
                 human studies in automated software engineering. I
                 present and describe multiple how to examples of using
                 crowd sourcing (e.g., Amazon's Mechanical Turk) and
                 massive on-line education (MOOCs) to enable
                 SBSE-related human studies [10,11]. I argue that we
                 should leverage our great strength in testing to tackle
                 the increasingly-critical problem of test oracle
                 generation (e.g., [9]) - not just test data generation
                 - and draw supportive analogies with the subfields of
                 specification mining and invariant detection [16,19].
                 Finally, I challenge the SBSE community to facilitate
                 reproducible research and scientific advancement
                 through benchmark creation, and support the need for
                 such efforts with statistics from previous accepted
                 papers.",
}

Genetic Programming entries for Westley Weimer

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