Correction of Logical Errors in C programs using Genetic Algorithm Techniques

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

@Article{Murali:2009:IJRTE,
  author =       "Prakash Murali and Atul Sandur and Abhay Ashok Patil",
  title =        "Correction of Logical Errors in C programs using
                 Genetic Algorithm Techniques",
  journal =      "International Journal of Recent Trends in Engineering
                 (IJRTE)",
  year =         "2009",
  volume =       "1",
  number =       "2",
  pages =        "176--178",
  month =        may,
  keywords =     "genetic algorithms, genetic programming, SBSE, logical
                 error",
  ISSN =         "1797-9617",
  publisher =    "Academy Publisher in cooperation with the ACEEE",
  URL =          "http://ijrte.academypublisher.com/vol01/no02/ijrte0102176178.pdf",
  size =         "3 pages",
  abstract =     "In this paper, we propose a logical error correction
                 system for C programs. Although there has been
                 considerable research in the field of error detection,
                 there have been few advances in logical error
                 correction. Our solution combines statistical control
                 flow techniques for error detection and genetic
                 programming techniques for error correction. We assume
                 that logical errors are confined to expressions in the
                 input program. In this context, the expressions are
                 mined and statistically ranked on the basis of their
                 error relevance. This initial data forms the input to
                 the genetic algorithm that generates new and improved
                 expression sets for the input program. A main genetic
                 algorithm controls the evolution of expression sets
                 while the individual expressions are modulated by
                 genetic programming techniques. These sets of
                 expressions are tested with the standard test bench and
                 their fitness is declared to the genetic algorithm. The
                 genetic algorithm produces new generations of
                 expression sets until at least one set passes the
                 testing criteria. This algorithm can also be extended
                 to debug codes in other programming languages.",
}

Genetic Programming entries for Prakash Murali Atul Kumar Sujayendra Sandur Abhay Ashok Patil

Citations