• ISSN: 2010-0248
    • Abbreviated Title: Int. J. Innov.  Manag. Technol.
    • Frequency: Bimonthly
    • DOI: 10.18178/IJIMT
    • Editor-in-Chief: Prof. Jin Wang
    • Executive Editor: Ms. Nina Lee
    • Abstracting/ Indexing: Google Scholar, Ulrich's Periodicals Directory,  Crossref and ProQuest, Electronic Journals Library.
    • E-mail: ijimt@ejournal.net
IJIMT 2013 Vol.4(5): 512-517 ISSN: 2010-0248
DOI: 10.7763/IJIMT.2013.V4.453

Code Generator Amelioration Using Genetic Algorithm Techniques

P. Cockshott and Y. Gdura
Abstract— Genetic algorithms (GAs) are based on techniques inspired by some aspects of natural science such as inheritance, reproduction and mutation, and they are used as optimization technique for searching large solution spaces. In computer science, for example, they could be used in data sorting and searching, circuit design and to improve application performance the quality of designed tools such as code generation. This paper looks at the possibility of using genetic algorithms to ameliorate the automatic construction of code generators. Experimental evidence is provided that the use of such algorithms can improve the quality of automatically constructed code generators.

Index Terms— Genetic algorithms, compilers, code-selection, permutation problem.

P. Cockshott is with the School of Computer Science, University of Glasgow, USA (e-mail: wpc@dcs.gla.ac.uk).
Y. Gdura was with Computer Engineering Department, University of Tripoli, USA (e-mail: ygdura@tripoliuniv.edu.ly).


Cite: P. Cockshott and Y. Gdura, " Code Generator Amelioration Using Genetic Algorithm Techniques," International Journal of Innovation, Management and Technology vol. 4, no. 5, pp. 512-517, 2013.

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