@inproceedings (Langdon:1995:GPdata,
  author =	{W. B. Langdon},
  title =	{Evolving Data Structures Using Genetic Programming},
  booktitle =	{Genetic Algorithms: Proceedings of the Sixth International Conference (ICGA95)},
  year =	1995,
  editor = 	{L.  Eshelman},
  pages = 	{295--302},
  address = 	{San Francisco, CA., USA},
  month = 	{July},
  organisation ={},
  publisher = 	{Morgan Kaufmann},
  note =	{},
  keywords =    {Automatic Programming, Machine Learning, 
Genetic Programming, Genetic Algorithms, Artificial Evolution,
Data Structures, Object Oriented Programming, 
Push down Stack, First-in first-out (FIFO) Queue,
Automatically Defined Functions (ADF), Pareto fitness, Demes},
  ISBN =        {1-55860-370-0},
  url =         {ftp://cs.ucl.ac.uk/genetic/papers/GPdata_icga-95.ps},
  size = 	{8 pages},
  abstract =	{Genetic programming (GP) is a subclass of genetic
algorithms (GAs), in which evolving programs are directly represented
in the chromosome as trees. Recently it has been shown that programs
which explicitly use directly addressable memory can be generated
using GP.
 
It is established good software engineering practice to ensure that
programs use memory via abstract data structures such as stacks,
queues and lists.  These provide an interface between the program and
memory, freeing the program of memory management details which are
left to the data structures to implement.  The main result presented
herein is that GP can automatically generate stacks and queues.
Typically abstract data structures support multiple operations, such
as put and get. We show that GP can simultaneously evolve all the
operations of a data structure by implementing each such operation
with its own independent program tree. That is, the chromosome
consists of a fixed number of independent program trees. Moreover,
crossover only mixes genetic material of program trees that implement
the same operation. Program trees interact with each other only via
shared memory and shared ``Automatically Defined Functions'' (ADFs).
 
ADFs, ``pass by reference'' when calling them, Pareto selection,
``good software engineering practice'' and partitioning the genetic
population into ``demes'' where also investigated whilst evolving the
queue in order to improve the GP solutions. 
},
  notes =	{Discussed on GP mailing list 6--13 Jan 95, subj: GPdata. 
Mainly as Langdon:1995:GPdataRN but with more details on pareto selection}
)