Genetic programming for automating the development of data management algorithms in information technology systems

  • Authors:

  • Gabriel A. Archanjo;Fernando J. Von Zuben

  • Affiliations:

  • Laboratory of Bioinformatics and Bioinspired Computing, School of Electrical and Computer Engineering, University of Campinas (Unicamp), SP, Brazil;Laboratory of Bioinformatics and Bioinspired Computing, School of Electrical and Computer Engineering, University of Campinas (Unicamp), SP, Brazil

  • Venue:
  • Advances in Software Engineering
  • Year:
  • 2012

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Abstract

Information technology (IT) systems are present in almost all fields of human activity, with emphasis on processing, storage, and handling of datasets. Automated methods to provide access to data stored in databases have been proposed mainly for tasks related to knowledge discovery and datamining (KDD). However, for this purpose, the database is used only to query data in order to find relevant patterns associated with the records. Processes modelled on IT systems should manipulate the records to modify the state of the system. Linear genetic programming for databases (LGPDB) is a tool proposed here for automatic generation of programs that can query, delete, insert, and update records on databases. The obtained results indicate that the LGPDB approach is able to generate programs for effectively modelling processes of IT systems, opening the possibility of automating relevant stages of data manipulation, and thus allowing human programmers to focus on more complex tasks.