Using genetic programming for the induction of novice procedural programming solution algorithms

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Nelishia Pillay",
  title =        "Using genetic programming for the induction of novice
                 procedural programming solution algorithms",
  booktitle =    "SAC '02: Proceedings of the 2002 ACM symposium on
                 Applied computing",
  year =         "2002",
  ISBN =         "1-58113-445-2",
  pages =        "578--583",
  publisher =    "ACM Press",
  address =      "Madrid, Spain",
  publisher_address = "New York, NY, USA",
  month =        mar,
  organisation = "SIGAPP: ACM Special Interest Group on Applied
  keywords =     "genetic algorithms, genetic programming, intelligent
                 programming tutors",
  URL =          "",
  DOI =          "doi:10.1145/508791.508903",
  size =         "7 pages",
  abstract =     "a genetic programming system for the induction of
                 solutions to novice procedural programming problems.
                 This genetic programming system will form part of a
                 generic architecture for the development of intelligent
                 programming tutors for the procedural and
                 object-oriented programming paradigms. An account of
                 the primitives and system parameters needed for the
                 derivation of solutions to problems for each of the
                 introductory procedural programming topics is provided.
                 This is followed by an analysis of the solutions
                 induced by the genetic programming system. Finally, the
                 paper discusses the future work that will be carried as
                 part of the initiative to evaluate genetic programming
                 as a means of inducing solutions to novice procedural
                 and object-oriented programming problems.",
  notes =        "Arrays, recursion, modules, strong type (STGP)
                 integer, real string, char, boolean, acyclic graphs,
                 parse trees, stacks, linear. Multi-tree genome. Steady
                 state, driving screen (ASCII control codes?)
                 \cite{langdon:book}, string manipulation: length,
                 concat, delete, insert, copy, equal. write and change
                 named memory. Indexed memory: aread, alen. IF, switchi
                 switchc (switch or case). iterative control structures:
                 for while dowhile (iteration loops) counter variable,
                 iteration variable. Input and output structures:
                 screen, place(x,y,output_value). Recursion: recur,
                 variable arity? (population size=700). {"}26 novice
                 procedural programming problems{"}. cultural learning

Genetic Programming entries for Nelishia Pillay