Overfitting in Automated Program Repair: Challenges and Solutions

Created by W.Langdon from gp-bibliography.bib Revision:1.8620

@PhdThesis{Le_Xuan-Bach:thesis,

• author = "Dinh Xuan Bach Le",
• title = "Overfitting in Automated Program Repair: Challenges and Solutions",
• school = "School of Information Systems, Singapore Management University",
• year = "2018",
• address = "Singapore",
• month = jun,
• keywords = "genetic algorithms, genetic programming, genetic improvement, program repair, APR, Program synthesis, Symbolic execution, Empirical study, SemFix, MaxSMT",
• URL = "https://ink.library.smu.edu.sg/etd_coll/177/",
• URL = "https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1177&context=etd_coll",
• size = "151 pages",
• abstract = "discusses the main problem and motivation of this dissertation. It also discusses a quantification of various research issues directly related to the dissertation. A summary of works done will also be presented along with the structure of the dissertation.",
• notes = "GP only in history of automatic bug fixing.

  Supervisor: David Lo

  https://sis.smu.edu.sg/newsletter/28876",

}

Genetic Programming entries for Xuan-Bach Dinh Le

Citations